We have read with great interest the article investigating the relationship between computed tomography (CT) findings of the patients with fibrotic-like patterns and telomere length after four months of acute COVID-19 infection. According to the literature and our experience, post-COVID interstitial lung disease is a potential public health problem. Thus, we aimed to share our concerns about the fibrotic-like patterns in this group of patients.
Post-COVID fibrosis is not as the same as the other interstitial lung diseases. In the article, the authors describe CT findings of fibrotic-like patterns as limited to reticulation, honeycomb cysts, and traction bronchiectasis. However, post-COVID fibrosis CT findings were shown to be more varied and may include parenchymal bands, irregular densities, and ground-glass areas (1–3). As we move towards the future, all of us need to create a common language, a lingua franca in the definition of post-COVID fibrosis. To achieve this, we need brainstorming and close cooperation.
It will also be helpful to elaborate the characteristics of the non-fibrotic pattern in the table. The clinical importance of the ground glass areas, which persist four months after active infection but not defined as fibrotic, is unknown. We consider that these patterns cannot be separated from fibrotic-like patterns precisely. Additionally, we can also classify parenchymal bands as fibrosis-like appearance. In our experience...
We have read with great interest the article investigating the relationship between computed tomography (CT) findings of the patients with fibrotic-like patterns and telomere length after four months of acute COVID-19 infection. According to the literature and our experience, post-COVID interstitial lung disease is a potential public health problem. Thus, we aimed to share our concerns about the fibrotic-like patterns in this group of patients.
Post-COVID fibrosis is not as the same as the other interstitial lung diseases. In the article, the authors describe CT findings of fibrotic-like patterns as limited to reticulation, honeycomb cysts, and traction bronchiectasis. However, post-COVID fibrosis CT findings were shown to be more varied and may include parenchymal bands, irregular densities, and ground-glass areas (1–3). As we move towards the future, all of us need to create a common language, a lingua franca in the definition of post-COVID fibrosis. To achieve this, we need brainstorming and close cooperation.
It will also be helpful to elaborate the characteristics of the non-fibrotic pattern in the table. The clinical importance of the ground glass areas, which persist four months after active infection but not defined as fibrotic, is unknown. We consider that these patterns cannot be separated from fibrotic-like patterns precisely. Additionally, we can also classify parenchymal bands as fibrosis-like appearance. In our experience, subpleural parenchymal bands are not uncommon. Furthermore, respiratory symptoms may persist in patients with parenchymal bands. So, this pattern should be considered as a part of fibrotic-like pattern.
Another challenge is the lack of proof regarding fibrosis development due to COVID-19 infection. For example, honeycomb cysts are an indicator of irreversible fibrosis, and it is uncertain whether they are present in the previous CT images or not. A similar condition may apply to irregular reticulation and traction bronchiectasis. The development of fibrotic patterns may also differ from the images during the active infection (4). It may be instructive to examine the process by which signs of active involvement evolve into fibrosis, as well as the development of a fibrotic-like pattern.
We need a more precise interpretation of the development of fibrotic-like patterns. Therefore, we suggest analysing subtypes of post-COVID fibrosis, compare present findings on CT with long-term follow-up images. Also, it might be beneficial to show, if possible, that there is no fibrotic pattern in the CTs before acute Covid 19 infection.
References
1. Huang W, Wu Q, Chen Z, Xiong Z, Wang K, Tian J, et al. The potential indicators for pulmonary fibrosis in survivors of severe COVID-19. Vol. 82, Journal of Infection. 2021.
2. Myall KJ, Mukherjee B, Castanheira AM, Lam JL, Benedetti G, Mak SM, et al. Persistent Post-COVID-19 Interstitial Lung Disease. An Observational Study of Corticosteroid Treatment. Ann Am Thorac Soc. 2021;18(5).
3. Shah AS, Wong AW, Hague CJ, Murphy DT, Johnston JC, Ryerson CJ, et al. A prospective study of 12-week respiratory outcomes in COVID-19-related hospitalisations. Vol. 76, Thorax. 2021.
4. Guan CS, Wei LG, Xie RM, Lv Z Bin, Yan S, Zhang ZX, et al. CT findings of COVID-19 in follow-up: Comparison between progression and recovery. Diagnostic Interv Radiol. 2020;26(4):301–7.
We thank N. Hürsoy and colleagues for their interest in our study of patients four months after severe COVID-19 [1]. We agree that there needs to be continued development of terms describing the radiographic appearance of post-COVID fibrotic-like patterns. We acknowledge that without the benefit of histopathology or serial imaging, our ability to define pulmonary fibrosis is limited.
The authors posit that parenchymal bands, irregular densities, and ground glass opacities, may be considered fibrotic-like patterns. We have included irregular densities, characterized as reticulations or traction bronchiectasis, as fibrotic-like changes. We did not include parenchymal bands [2], as these can be associated with atelectasis, which is common in COVID and can disappear over time [3]. Similarly, we did not include isolated ground glass opacities as fibrotic-like changes, as these have been found to decrease over time in CT lung cancer screening cohorts [4] and in other post COVID-19 cohorts [5, 6].
A priori, we evaluated for both previously established interstitial lung abnormality categories [7], as well as categories of radiographic abnormalities reported in Acute Respiratory Distress Syndrome (ARDS) survivors using an established scoring system [8]. This inclusive approach should facilitate meta-analyses and comparisons with future studies of COVID-19 survivors, interstitial lung disease studies, and studies of non-COVID ARDS survivors. Fu...
We thank N. Hürsoy and colleagues for their interest in our study of patients four months after severe COVID-19 [1]. We agree that there needs to be continued development of terms describing the radiographic appearance of post-COVID fibrotic-like patterns. We acknowledge that without the benefit of histopathology or serial imaging, our ability to define pulmonary fibrosis is limited.
The authors posit that parenchymal bands, irregular densities, and ground glass opacities, may be considered fibrotic-like patterns. We have included irregular densities, characterized as reticulations or traction bronchiectasis, as fibrotic-like changes. We did not include parenchymal bands [2], as these can be associated with atelectasis, which is common in COVID and can disappear over time [3]. Similarly, we did not include isolated ground glass opacities as fibrotic-like changes, as these have been found to decrease over time in CT lung cancer screening cohorts [4] and in other post COVID-19 cohorts [5, 6].
A priori, we evaluated for both previously established interstitial lung abnormality categories [7], as well as categories of radiographic abnormalities reported in Acute Respiratory Distress Syndrome (ARDS) survivors using an established scoring system [8]. This inclusive approach should facilitate meta-analyses and comparisons with future studies of COVID-19 survivors, interstitial lung disease studies, and studies of non-COVID ARDS survivors. Furthermore, it allows for future post-hoc analyses if alternate definitions of fibrotic-like patterns in COVID-19 survivors are established. Additionally, we showed that objective quantitative analyses closely agreed with visual assessments (Figure S2). These types of quantitative imaging analyses may facilitate the convergence of data from multiple centers if imaging protocols become more standardized [9].
Efforts are underway to characterize pulmonary impairments and radiographic abnormalities in our cohort over time in order to assess longitudinal evolution. We acknowledge that our findings do not exclude the possibility of pre-existing lung disease and we therefore look forward to reviewing independent studies, such as the Collaborative Cohort of Cohorts for COVID-19 Research (C4R) [10] project, which will provide better understanding of radiographic changes by comparing chest imaging studies before and after SARS-CoV-2 infection.
1. McGroder, C.F., et al., Pulmonary fibrosis 4 months after COVID-19 is associated with severity of illness and blood leucocyte telomere length. Thorax, 2021.
2. Pulmonary Parenchymal Band. Available from: https://www.ncbi.nlm.nih.gov/medgen/978776.
3. Kong, M., et al., Evolution of chest CT manifestations of COVID-19: a longitudinal study. J Thorac Dis, 2020. 12(9): p. 4892-4907.
4. Jin, G.Y., et al., Interstitial lung abnormalities in a CT lung cancer screening population: prevalence and progression rate. Radiology, 2013. 268(2): p. 563-71.
5. Nagpal, P., et al., Case Studies in Physiology: Temporal Variations of the Lung Parenchyma and Vasculature in Asymptomatic COVID-19 Pneumonia: A Multi-Spectral CT Assessment. J Appl Physiol (1985), 2021.
6. Liu, D., et al., The pulmonary sequalae in discharged patients with COVID-19: a short-term observational study. Respir Res, 2020. 21(1): p. 125.
7. Hatabu, H., et al., Interstitial lung abnormalities detected incidentally on CT: a Position Paper from the Fleischner Society. Lancet Respir Med, 2020. 8(7): p. 726-737.
8. Burnham, E.L., et al., Chest CT features are associated with poorer quality of life in acute lung injury survivors. Crit Care Med, 2013. 41(2): p. 445-56.
9. Nagpal, P., et al., Quantitative CT imaging and advanced visualization methods: potential application in novel coronavirus disease 2019 (COVID-19) pneumonia. BJR Open, 2021. 3(1): p. 20200043.
10. Collaborative Cohort of Cohorts for COVID-19 Research. Available from: https://c4r-nih.org/content/overview.
We have read the paper by Barker et al. (1) with interest. We congratulate the authors for conducting and publishing their prospective cohort study evaluating the effect of COPD discharge bundle on pulmonary rehabilitation (PR) referral and uptake following hospitalisation for acute exacerbation of COPD (AECOPD).
The authors have shown that the COPD discharge bundle had a positive effect on PR referral compared with a no bundle (17.5% (40 of 228) referral rate vs 0%(0 of 63)). This figure is lower than the expected 30% referral rate to PR following AECOPD (2). However, the paper offers no potential reasons for the lower referral rate.
The study had two bundle groups:
• COPD discharge bundle delivered by a current PR practitioner
• COPD discharge bundle delivered by a practitioner with no involvement in PR
Compared to delivery by a practitioner with no PR involvement, completion of the bundle delivery by a current PR practitioner resulted in higher referral and pick-up rates (60% vs 12% and 40% vs 32%, respectively). These results support the concept of integrating PR and hospital services.
Unfortunately, the completion rate (number of subjects who completed PR divided by the number of referrals) was disappointingly low. Also, there was no difference between the two bundle groups (13% (2 of 15) vs 12% (3 of 25)), as stated in the supplementary data.
It seems that patients' willingness or ability to complete PR is not af...
We have read the paper by Barker et al. (1) with interest. We congratulate the authors for conducting and publishing their prospective cohort study evaluating the effect of COPD discharge bundle on pulmonary rehabilitation (PR) referral and uptake following hospitalisation for acute exacerbation of COPD (AECOPD).
The authors have shown that the COPD discharge bundle had a positive effect on PR referral compared with a no bundle (17.5% (40 of 228) referral rate vs 0%(0 of 63)). This figure is lower than the expected 30% referral rate to PR following AECOPD (2). However, the paper offers no potential reasons for the lower referral rate.
The study had two bundle groups:
• COPD discharge bundle delivered by a current PR practitioner
• COPD discharge bundle delivered by a practitioner with no involvement in PR
Compared to delivery by a practitioner with no PR involvement, completion of the bundle delivery by a current PR practitioner resulted in higher referral and pick-up rates (60% vs 12% and 40% vs 32%, respectively). These results support the concept of integrating PR and hospital services.
Unfortunately, the completion rate (number of subjects who completed PR divided by the number of referrals) was disappointingly low. Also, there was no difference between the two bundle groups (13% (2 of 15) vs 12% (3 of 25)), as stated in the supplementary data.
It seems that patients' willingness or ability to complete PR is not affected by the referral source, i.e. whether the referral was received by a practitioner involved in PR or not. A previous publication has demonstrated a 47% completion rate for PR referrals following AECOPD, with a 72% completion rate for those who started the programme (2).
We are curious whether the authors have explored the potential reasons for the lower completion rate in their study. Causes could include dissatisfaction with the provided programme, a patient’s anxiety, and lack of perceived benefit from PR participation.
References
1. Barker RE, Kon SS, Clarke SF, et alCOPD discharge bundle and pulmonary rehabilitation referral and uptake following hospitalisation for acute exacerbation of COPDThorax Published Online First: 02 March 2021. doi: 10.1136/thoraxjnl-2020-215464
2. Jones SE, Green SA, Clark AL, et alPulmonary rehabilitation following hospitalisation for acute exacerbation of COPD: referrals, uptake and adherenceThorax 2014;69:181-182.
We thank Dr Abdulqawi for interest in our work (1). He comments that the referral, uptake and completion rates for pulmonary rehabilitation in the current study were lower than in a previous study by Jones and colleagues (2). We would caution against retrospective comparison with unmatched historical controls due to confounding factors such as differences in patient characteristics and practice pathways that may contribute to inaccurate point estimates.
We hypothesised that the COPD discharge bundle would impact on referral rates. Strengths of the current work include the prospective real-world nature of the study, with the research team having no involvement in treatment allocation. The clinical team delivering the bundle were blinded to the study objectives, thus minimising any Hawthorne effect.
Dr Abdulqawi raises the point that pulmonary rehabilitation completion rates were low in the current study (albeit based on a low denominator). The reasons for non-completion of PR are often complex and multi-factorial (3) and may not be directly related to referral source. However, what is clear is that without a referral for pulmonary rehabilitation, uptake and completion rates are zero.
1. Barker RE BL, Maddocks M, Nolan CM, Patel S, Walsh JA, Polgar O, Wenneberg J, Kon SSC, Wedzicha JA, Man WDC, Farquhar M. Integrating Home-Based Exercise Training with a Hospital at Home Service for Patients Hospitalised with Acute Exacerbations of COPD: Developing the M...
We thank Dr Abdulqawi for interest in our work (1). He comments that the referral, uptake and completion rates for pulmonary rehabilitation in the current study were lower than in a previous study by Jones and colleagues (2). We would caution against retrospective comparison with unmatched historical controls due to confounding factors such as differences in patient characteristics and practice pathways that may contribute to inaccurate point estimates.
We hypothesised that the COPD discharge bundle would impact on referral rates. Strengths of the current work include the prospective real-world nature of the study, with the research team having no involvement in treatment allocation. The clinical team delivering the bundle were blinded to the study objectives, thus minimising any Hawthorne effect.
Dr Abdulqawi raises the point that pulmonary rehabilitation completion rates were low in the current study (albeit based on a low denominator). The reasons for non-completion of PR are often complex and multi-factorial (3) and may not be directly related to referral source. However, what is clear is that without a referral for pulmonary rehabilitation, uptake and completion rates are zero.
1. Barker RE BL, Maddocks M, Nolan CM, Patel S, Walsh JA, Polgar O, Wenneberg J, Kon SSC, Wedzicha JA, Man WDC, Farquhar M. Integrating Home-Based Exercise Training with a Hospital at Home Service for Patients Hospitalised with Acute Exacerbations of COPD: Developing the Model Using Accelerated Experience-Based Co-Design. Int J Chron Obstruct Pulmon Dis. 2021;16:1035-49.
2. Jones SE, Green SA, Clark AL, Dickson MJ, Nolan AM, Moloney C, et al. Pulmonary rehabilitation following hospitalisation for acute exacerbation of COPD: Referrals, uptake and adherence. Thorax. 2014;69(2):181-2.
3. Jones SE, Barker RE, Nolan CM, Patel S, Maddocks M, Man WD. Pulmonary rehabilitation in patients with an acute exacerbation of chronic obstructive pulmonary disease. J Thorac Dis. 2018;1(1):S1390-S9.
The paper by Hopkinson et al (1) provides unique and important data on smoking prevalence and COVID-19 symptoms, but their conclusion does not reflect the data well. The authors conclude “these data are consistent with people who smoke being at an increased risk of developing symptomatic COVID-19”. The study includes over 150,000 people with self-reported COVID-19 symptoms and over two million without such symptoms. It also includes data on over 25,000 people who were tested for SARS-CoV-2 and their test results. Based on our analysis of these more relevant data, we interpret the study differently. Our conclusion would be “these data are consistent with smokers having an increased risk of symptoms such as cough and breathlessness, but a decreased risk of having SARS-CoV-2 infection”.
The difficulty in interpreting these results is that both symptoms and testing are likely colliders in a causal model of smoking and COVID-19. The data reported on SARS-CoV-2 test results make it possible to compare smoking prevalence by age-group and sex in three groups: those who tested positive for SARS-CoV-2 (n=7,123); those who tested negative (n=16,765); and untested asymptomatic users (n=2,221,088, called “standard users” by the authors). Overall smoking prevalence was less in those tested (8.9%) than in all users of the app (11.0%). This might be thought of as a surprising finding – smoking-related symptoms should lead to testing – but can probably be explained by most asymptom...
The paper by Hopkinson et al (1) provides unique and important data on smoking prevalence and COVID-19 symptoms, but their conclusion does not reflect the data well. The authors conclude “these data are consistent with people who smoke being at an increased risk of developing symptomatic COVID-19”. The study includes over 150,000 people with self-reported COVID-19 symptoms and over two million without such symptoms. It also includes data on over 25,000 people who were tested for SARS-CoV-2 and their test results. Based on our analysis of these more relevant data, we interpret the study differently. Our conclusion would be “these data are consistent with smokers having an increased risk of symptoms such as cough and breathlessness, but a decreased risk of having SARS-CoV-2 infection”.
The difficulty in interpreting these results is that both symptoms and testing are likely colliders in a causal model of smoking and COVID-19. The data reported on SARS-CoV-2 test results make it possible to compare smoking prevalence by age-group and sex in three groups: those who tested positive for SARS-CoV-2 (n=7,123); those who tested negative (n=16,765); and untested asymptomatic users (n=2,221,088, called “standard users” by the authors). Overall smoking prevalence was less in those tested (8.9%) than in all users of the app (11.0%). This might be thought of as a surprising finding – smoking-related symptoms should lead to testing – but can probably be explained by most asymptomatic testing being in healthcare workers among whom smoking is less common. Importantly, smoking prevalence was appreciably lower in those who tested positive for SARS-CoV-2 (7.4%) than in both those who tested negative (9.3%) and in untested users (10.8%). The lower prevalence of smokers in app-users who tested positive was observed in all but one age-sex strata. In Table 1 https://shorturl.at/ovDL1 we reproduce the stratum-specific prevalence and provide two sets of odds ratios: one relative to participants who tested negative; and the other relative to standard users. If smoking causes similar symptoms to COVID-19 (e.g. persistent cough and shortness of breath) then using symptoms as a “test” for COVID-19 will more often lead to a false-positive in smokers than in non-smokers. This would explain the finding that the authors focus on, but it also means that one might expect lower prevalence of smoking in true-positives (i.e. those who test positive for SARS-CoV-2) than in false-positives (i.e. those who test negative). However, a different explanation is needed to explain the lower prevalence in test positive than in untested asymptomatic users. That might be because current smokers are at lower risk of SARS-CoV-2 infection, or it might be because asymptomatic smokers were less likely to be tested than asymptomatic non-smokers.
We note that the numbers of prevalent smokers in the authors’ Table 1 do not correspond to the percentages. This presumably is due to some users not completing the question regarding smoking. It is interesting to note that there were more people tested than those with either a positive or negative result. If, by subtraction, one calculates the prevalence of smoking among those tested who do not have a result, one finds that the prevalence of smoking is significantly (P<0.05) greater than amongst both those with a negative result (risk ratio 1.14) and those with a positive result (risk ratio 1.45).
These data are consistent with the unexpected observation made across a considerable number of studies that smokers have a decreased risk of COVID-19 (2). As with these previous observations, the results of this study could be an artefact of reporting and selection biases, but they certainly do not disprove the ‘protection’ hypothesis. The authors state that they have data to differentiate ex-smokers from current smokers, but unfortunately do not present them. Others have reported higher risk of COVID-19 in ex-smokers than in never smokers but also higher than in current smokers (2). As ex-smokers can be expected to lose the hypothetical protective effect of smoking but retain the health impact of their previous smoking, this makes the hypothesis more plausible. The fact that studies using similar approaches have detected a much higher risk in smokers to develop laboratory-confirmed influenza than non-smokers (3) also suggest that the finding of lower incidence of COVID-19 in smokers may not be just a methodological artefact. Several tentative hypotheses were proposed to explain the possible protective effect of smoking, including effects of nicotine on ACE receptors (4), effects on immune system of tobacco mosaic virus that typically colonizes airways of smokers (5), and thermic effects of regular inhalation of hot smoke on virus replication (2, 6).
There is no doubt that the harms of smoking hugely outweigh any benefits and that efforts to help smokers quit are important even in the time of pandemic. However, if current smoking causes a lowering of risk, then it is imperative to understand the mechanisms, because a better understanding could lead to new ways to reduce the risk of infection in the general population. Better data are urgently needed to clarify this potentially very important issue.
References:
1. Hopkinson NS, Rossi N, El-Sayed_Moustafa J, et al. Thorax Epub ahead of print. doi:10.1136/thoraxjnl-2020-216422
2. David Simons, Lion Shahab, Jamie Brown, Olga Perski. (2020). The association of smoking status with SARS-CoV-2 infection, hospitalisation and mortality from COVID-19: A living rapid evidence review with Bayesian meta-analyses (version 9). Qeios. doi:10.32388/UJR2AW.10.
3. Lawrence H, Hunter A, Murray R, Lim WS, McKeever T. Cigarette smoking and the occurrence of influenza - Systematic review. J Infect. 2019 Nov;79(5):401-406. doi: 10.1016/j.jinf.2019.08.014. Epub 2019 Aug 26. PMID: 31465780.
4. Farsalinos K, Angelopoulou A, Alexandris N, et al. COVID-19 and the nicotinic cholinergic system. Eur Respir J 2020 56: 2001589; DOI: 10.1183/13993003.01589-2020
5. de Bernardis E, Busà L. A putative role for the tobacco mosaic virus in smokers' resistance to COVID-19. Med Hypotheses. 2020;143:110153. doi:10.1016/j.mehy.2020.110153
6. Conti C, de Marco A, Mastromarino P, Tomao P, Santoro MG. Antiviral Effect of Hyperthermic Treatment in Rhinovirus Infection. Antimicrob Agents Chemother 1999; 43: 822–9.
We thank the authors for their letter in response to our paper(1). We disagree however that the data among the tested subgroup are more informative than our other findings. This is because the small subgroup (1.1% of app users - 0.7% negative, 0.3% positive, 0.1% result unknown) who reported that they had undergone testing for COVID-19 at this relatively early stage in the pandemic (the month from 24th March 2020) were heavily selected. Testing policies focused on healthcare workers and others interacting with healthcare - in particular, patients tested who may have been attending healthcare settings for other, non-COVID-19 related, conditions. As numerous health conditions are smoking-related this would tend to increase the exposure of smokers without COVID-19 to testing. For these reasons, as discussed in the paper, the finding that smoking rates were lower in those testing positive is likely to be due to sampling bias. Rather than being “more relevant”, extrapolation from this subgroup to population risk is entirely inappropriate.
The letter does appear to misunderstand the groups presented – the “standard user” group were not asymptomatic during the study. Rather, as set out in the first paragraph of the results, they were individuals who at the point of registration with the Zoe COVID Symptom Study App did not think that they already had COVID-19. Among this group of “standard users” current smokers were more likely to report the onset of new symptoms suggesting...
We thank the authors for their letter in response to our paper(1). We disagree however that the data among the tested subgroup are more informative than our other findings. This is because the small subgroup (1.1% of app users - 0.7% negative, 0.3% positive, 0.1% result unknown) who reported that they had undergone testing for COVID-19 at this relatively early stage in the pandemic (the month from 24th March 2020) were heavily selected. Testing policies focused on healthcare workers and others interacting with healthcare - in particular, patients tested who may have been attending healthcare settings for other, non-COVID-19 related, conditions. As numerous health conditions are smoking-related this would tend to increase the exposure of smokers without COVID-19 to testing. For these reasons, as discussed in the paper, the finding that smoking rates were lower in those testing positive is likely to be due to sampling bias. Rather than being “more relevant”, extrapolation from this subgroup to population risk is entirely inappropriate.
The letter does appear to misunderstand the groups presented – the “standard user” group were not asymptomatic during the study. Rather, as set out in the first paragraph of the results, they were individuals who at the point of registration with the Zoe COVID Symptom Study App did not think that they already had COVID-19. Among this group of “standard users” current smokers were more likely to report the onset of new symptoms suggesting a diagnosis of COVID-19. For presenting with “classic” COVID-19 symptoms (cough, fever, breathlessness) the adjusted OR[95%CI] was 1.14[1.10 to 1.18]; for presenting >5 symptoms 1.29[1.26 to 1.31]; for >10 symptoms 1.50[1.42 to 1.58].
Among the 157,000 people who did think that they already had COVID-19 at the time of registration, 13.79% were current smokers compared to 10.96% among all users, further supporting increased susceptibility from tobacco use.
As we set out in the paper, the pattern of association between reported symptoms did not vary between smokers and non-smokers and therefore cannot be explained by the presence of specific symptoms related to smoking.
It is also worth highlighting those reporting that they had tested positive for SARS-CoV-2, a higher symptom burden was reported among smokers and smokers were also twice as likely to have needed to attend hospital because of COVID-19 (OR 2.11 [1.41 to 3.11]) compared to non-smokers, a further marker of increased susceptibility.
Our results are also consistent with the OPENSAFELY study based on data from the primary care records of 17.3 million adults in the UK which found that, adjusted for age and sex, current smoking was associated with a hazard ratio for COVID-19-related death of 1.14 (1.05–1.23)(2).
The tobacco industry kills an estimated 8.7 million people per year globally and places substantial burdens on livelihoods and ecosystems, particularly in low and middle income countries.(3, 4) We believe that our data do show that smokers are at an increased risk from COVID-19, but regardless of any direct link, steps to bring smoking to an end must continue,(5, 6) both because of the enormous broader health harms and because of the effect that acute smoking-related illness has on health system capacity and resilience.
REFERENCES
1. Hopkinson NS, Rossi N, El-Sayed Moustafa J, Laverty AA, Quint JK, Freidin M, et al. Current smoking and COVID-19 risk: results from a population symptom app in over 2.4 million people. Thorax. 2021.
2. Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584(7821):430-6.
3. Murray CJL, Aravkin AY, Zheng P, Abbafati C, Abbas KM, Abbasi-Kangevari M, et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2020;396(10258):1223-49.
4. Zafeiridou M, Hopkinson NS, Voulvoulis N. Cigarette Smoking: An Assessment of Tobacco’s Global Environmental Footprint Across Its Entire Supply Chain. Environmental science & technology. 2018;52(15):8087-94.
5. Hopkinson NS. The path to a smoke-free England by 2030. BMJ (Clinical research ed). 2020;368:m518-m.
6. Britton J, Arnott D, McNeill A, Hopkinson N. Nicotine without smoke—putting electronic cigarettes in context. BMJ. 2016;353.
There is no question that the harms of smoking hugely outweigh any potential health benefits. Many people, ourselves included, assumed at the beginning of the pandemic that greater susceptibility to COVID-19 would be another harm of tobacco smoking to be added to the long list. Surprisingly, most of the epidemiological data published over the last year do not support this claim. Indeed whereas ex-smokers are consistently found to be at increased risk of both SARS-CoV-2 infection and severe COVID-19, current smokers are consistently at lower risk than ex-smokers and in many studies they appear to be at a lower risk than never smokers. The lower infection rate in smokers compared to non-smokers and ex-smokers has been found across 62 studies (1, 2), including now a full cohort with a dose-response pattern (3).
The authors’ response does not counter the observation that among nearly 27,000 individuals who had a SARS-CoV-2 test in their study, smoking prevalence was lower in those who tested positive than in those who tested negative.
In the OpenSAFELY study (4) too, the direction of the association between smoking and death from COVID-19 depends critically on what adjustments are made. The primary analysis appears to be based on a fully adjusted Cox regression model in which the hazard ratio for current smokers relative to never smokers was 0.89 (95% CI 0.82-0.97). The value (1.14; 1.05-1.23) cited by Hopkinson and colleagues is after adjusting for age and sex...
There is no question that the harms of smoking hugely outweigh any potential health benefits. Many people, ourselves included, assumed at the beginning of the pandemic that greater susceptibility to COVID-19 would be another harm of tobacco smoking to be added to the long list. Surprisingly, most of the epidemiological data published over the last year do not support this claim. Indeed whereas ex-smokers are consistently found to be at increased risk of both SARS-CoV-2 infection and severe COVID-19, current smokers are consistently at lower risk than ex-smokers and in many studies they appear to be at a lower risk than never smokers. The lower infection rate in smokers compared to non-smokers and ex-smokers has been found across 62 studies (1, 2), including now a full cohort with a dose-response pattern (3).
The authors’ response does not counter the observation that among nearly 27,000 individuals who had a SARS-CoV-2 test in their study, smoking prevalence was lower in those who tested positive than in those who tested negative.
In the OpenSAFELY study (4) too, the direction of the association between smoking and death from COVID-19 depends critically on what adjustments are made. The primary analysis appears to be based on a fully adjusted Cox regression model in which the hazard ratio for current smokers relative to never smokers was 0.89 (95% CI 0.82-0.97). The value (1.14; 1.05-1.23) cited by Hopkinson and colleagues is after adjusting for age and sex only. Interestingly if one looks at the hazard of COVID-19 related death in current smokers relative to ex-smokers it is 0.75 and 0.80 in the fully-adjusted and the age-and-sex adjusted analyses respectively (and both are significantly less than 1.00 because the confidence intervals for former and current smokers don’t overlap).
Hopkinson et al. argue that the finding of lower smoking rates among positive cases was due to over-testing smokers attending healthcare facilities for other reasons. As we pointed out in our letter, smoking prevalence in the tested group was lower than in those not tested, which reduces the likelihood of such confounding. This does not rule out a possibility of confounding altogether, but we think the risk of confounding is much greater in the approach that the authors used, i.e. focusing on symptoms rather than on actual infections. Smokers are more likely to have symptoms and so they will obviously be over-represented in such samples.
If smoking reduces the risk of COVID-19 infection, it would of course not lead to encouraging smoking, but to identifying the active ingredient of the effect and the development of new preventive measures that could be of global importance.
1. Simons, D., Shahab, L., Brown, J., and Perski, O. (2020) The association of smoking status with SARS‐CoV‐2 infection, hospitalization and mortality from COVID‐19: a living rapid evidence review with Bayesian meta‐analyses (version 7). Addiction, https://doi.org/10.1111/add.15276.
2. Simons D, Shahab L, Brown J, Perski O. The association of smoking status with SARS-CoV-2 infection, hospitalisation and mortality from COVID-19: A living rapid evidence review with Bayesian meta-analyses (version 11, 2. March 2021) Qeios ID: UJR2AW.13; https://doi.org/10.32388/UJR2AW.13
3. Paleiron N, Mayet A, Marbac V, et al. Impact of Tobacco Smoking on the risk of COVID-19.A large scale retrospective cohort study [published online ahead of print, 2021 Jan 9]. Nicotine Tob Res. 2021;ntab004. doi:10.1093/ntr/ntab004
4. Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584(7821):430-6.
The idea that smoking might have a protective effect against COVID-19 is an intriguing, man bites dog type of story, which gives it a certain attraction. Happily, it appears to be false and the assumption of harm has turned out to be correct[1-5].
Our data show clearly that in the 2.4 million Zoe COVID Symptom Study App users, people who smoked were at increased risk of symptomatic COVID-19[2] and were at risk of more severe disease, which is consistent with a systematic review of patients hospitalized with COVID-19[4]. Our findings are also consistent with The UCL COVID-19 Social Study3 which found increased risk of test confirmed COVID-19 (OR=2.14 (1.49–3.08)) and with the COVIDENCE study where smokers had an OR of1.42 (0.99-2.05) for test-confirmed COVID-19[1].
The OpenSafely dataset based on data from the primary care records of 17.3 million adults in the UK found that, adjusted for age and sex, also identifies smoking as a risk factor - current smoking was associated with a hazard ratio for COVID-19-related death of 1.14 (1.05–1.23)5. The apparently protective effect in the “fully adjusted” model is due to over-correction producing collider bias.
Since any protective effect of smoking in COVID-19 appears to be illusory, pursuing a mechanism for it is unlikely to be productive.
References
1 Holt H, Talaei M, Greenig M, et al. Risk factors for developing COVID-19: a population-based longitudinal study (COVIDENCE UK). medRxiv 2021:2021.2003...
The idea that smoking might have a protective effect against COVID-19 is an intriguing, man bites dog type of story, which gives it a certain attraction. Happily, it appears to be false and the assumption of harm has turned out to be correct[1-5].
Our data show clearly that in the 2.4 million Zoe COVID Symptom Study App users, people who smoked were at increased risk of symptomatic COVID-19[2] and were at risk of more severe disease, which is consistent with a systematic review of patients hospitalized with COVID-19[4]. Our findings are also consistent with The UCL COVID-19 Social Study3 which found increased risk of test confirmed COVID-19 (OR=2.14 (1.49–3.08)) and with the COVIDENCE study where smokers had an OR of1.42 (0.99-2.05) for test-confirmed COVID-19[1].
The OpenSafely dataset based on data from the primary care records of 17.3 million adults in the UK found that, adjusted for age and sex, also identifies smoking as a risk factor - current smoking was associated with a hazard ratio for COVID-19-related death of 1.14 (1.05–1.23)5. The apparently protective effect in the “fully adjusted” model is due to over-correction producing collider bias.
Since any protective effect of smoking in COVID-19 appears to be illusory, pursuing a mechanism for it is unlikely to be productive.
References
1 Holt H, Talaei M, Greenig M, et al. Risk factors for developing COVID-19: a population-based longitudinal study (COVIDENCE UK). medRxiv 2021:2021.2003.2027.21254452
2 Hopkinson NS, Rossi N, El-Sayed Moustafa J, et al. Current smoking and COVID-19 risk: results from a population symptom app in over 2.4 million people. Thorax 2021 https://pubmed.ncbi.nlm.nih.gov/33402392/
3 Jackson SE, Brown J, Shahab L, et al. COVID-19, smoking and inequalities: a study of 53 002 adults in the UK. Tobacco Control 2020:tobaccocontrol-2020-055933
4 Reddy RK, Charles WN, Sklavounos A, et al. The effect of smoking on COVID-19 severity: A systematic review and meta-analysis. Journal of medical virology 2021; 93:1045-1056
5 Williamson EJ, Walker AJ, Bhaskaran K, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020; 584:430-436
With great interest we have read the study by Deshayes et al. The authors present two cases of silvernitrate (AgNO3) aspiration in laryngectomized patients.
1) In both cases the applicator tip broke off.
2) The authors conclude that treatment should comprise oral antibiotics and one should refrain from bronchial washing with sodium chloride solution.
With this response we would like to reply to both points addressed above.
1.
Five years ago we were confronted with the aspiration of an AgNO3 applicator tip in a laryngectomized patient. After the incident we analyzed the case to prevent future AgNO3 applicator tip aspiration. The AgNO3 pencil, used in both our case and the cases in the current article, is specifically designed to treat dermal lesions like verruca which requires repeated use. The pencil therefore contains a relatively large volume of AgNO3. AgNO3 is a brittle substance. When the pencil is used with a little too much pressure there is risk for the tip to break, and when used in a tracheostomy, there is risk for aspiration.
Our case led us to immediately stop using the AgNO3 pencils for treatment of granulation tissue in a tracheostomy. We strongly recommend the use of disposable AgNO3 cutaneous sticks for the treatment of granulation tissue around a tracheostomy. The disposable sticks contains less volume of AgNO3. Moreover, the stick is easier to use in narrow spaces like a tracheostomy.
2.
Aspiration of AgNO3 i...
With great interest we have read the study by Deshayes et al. The authors present two cases of silvernitrate (AgNO3) aspiration in laryngectomized patients.
1) In both cases the applicator tip broke off.
2) The authors conclude that treatment should comprise oral antibiotics and one should refrain from bronchial washing with sodium chloride solution.
With this response we would like to reply to both points addressed above.
1.
Five years ago we were confronted with the aspiration of an AgNO3 applicator tip in a laryngectomized patient. After the incident we analyzed the case to prevent future AgNO3 applicator tip aspiration. The AgNO3 pencil, used in both our case and the cases in the current article, is specifically designed to treat dermal lesions like verruca which requires repeated use. The pencil therefore contains a relatively large volume of AgNO3. AgNO3 is a brittle substance. When the pencil is used with a little too much pressure there is risk for the tip to break, and when used in a tracheostomy, there is risk for aspiration.
Our case led us to immediately stop using the AgNO3 pencils for treatment of granulation tissue in a tracheostomy. We strongly recommend the use of disposable AgNO3 cutaneous sticks for the treatment of granulation tissue around a tracheostomy. The disposable sticks contains less volume of AgNO3. Moreover, the stick is easier to use in narrow spaces like a tracheostomy.
2.
Aspiration of AgNO3 is rare, so there is no clinical evidence that proves for or against bronchial washing with sodium chloride solution. From a theoretical perspective there is an argument to advise bronchial washing with sodium chloride solution after AgNO3 aspiration. As previously concluded, AgNO3 is activated when it is dissolved in water. AgNO3 is neutralized when in contact with sodium chloride solution (AgNO3 → AgCl + NaNO3). Correspondingly, the manufacturer advices to repeatedly wash the stomach with sodium chloride solution after AgNO3 ingestion. The authors conclude that one should not wash with sodium chloride solution due to the risk for spread of AgNO3 and potential secondary stenosis. Corresponding to the manufacturer information AgNO3 is neutralized when dissolved in sodium chloride solution. Based on theory and manufacturer information we advise thorough bronchial washing with sodium chloride solution after AgNO3 aspiration.
We read the interesting report by Mason et al, “Respiratory exacerbations are associated with muscle loss in current and former smokers”.[1] In this study, the authors demonstrated that exacerbations are associated with accelerated loss of pectoralis muscles (PMs) in two large observational cohorts and quantified the impact of each annual exacerbation as the equivalent of 6 months of age-expected decline.
Skeletal muscle loss is one of the major systemic manifestations associated with mortality in patients with COPD. Not only systemic muscle loss but also loss of specific muscle groups are associated with clinical outcomes such as exacerbations and mortality in patients with COPD.[2, 3] Moreover, muscle loss can occur heterogeneously.[4] This may be partially because each muscle group has its physiological function or biological characteristics such as muscle fiber composition. This supports that loss of specific muscle groups may have different implications in the clinical course of COPD.
We previously analyzed the cross-sectional area of erector spinae muscles (ESMCSA) and that of PMs (PMCSA) in male patients with COPD using chest CT.[3] ESMs are ones of antigravity muscles which are involved in maintaining an upright posture. PMs play an important role in the movement of upper limbs. Both muscles also act as accessory inspiratory muscles. ESMs are composed of 60% type 1 fibers and 40% of type 2 fibers and PMs are composed in the reverse...
We read the interesting report by Mason et al, “Respiratory exacerbations are associated with muscle loss in current and former smokers”.[1] In this study, the authors demonstrated that exacerbations are associated with accelerated loss of pectoralis muscles (PMs) in two large observational cohorts and quantified the impact of each annual exacerbation as the equivalent of 6 months of age-expected decline.
Skeletal muscle loss is one of the major systemic manifestations associated with mortality in patients with COPD. Not only systemic muscle loss but also loss of specific muscle groups are associated with clinical outcomes such as exacerbations and mortality in patients with COPD.[2, 3] Moreover, muscle loss can occur heterogeneously.[4] This may be partially because each muscle group has its physiological function or biological characteristics such as muscle fiber composition. This supports that loss of specific muscle groups may have different implications in the clinical course of COPD.
We previously analyzed the cross-sectional area of erector spinae muscles (ESMCSA) and that of PMs (PMCSA) in male patients with COPD using chest CT.[3] ESMs are ones of antigravity muscles which are involved in maintaining an upright posture. PMs play an important role in the movement of upper limbs. Both muscles also act as accessory inspiratory muscles. ESMs are composed of 60% type 1 fibers and 40% of type 2 fibers and PMs are composed in the reversed ratio.[5] Both ESMCSA and PMCSA were significantly associated with age, body mass index (BMI), and disease severity in our study.[3] However, compared to PMCSA, ESMCSA showed a better association with physical activity and a significant association with mortality of patients with COPD.[3, 6] And in a subsequent longitudinal analysis of ESMCSA, we demonstrated that both ESMCSA at baseline and accelerated decline in ESMCSA, which was defined as over 10% decline in three years of interval, were independently associated with all-cause mortality. And we also demonstrated that accelerated decline of ESMCSA was significantly associated with frequent exacerbations and the percentage of the wall area of bronchi (WA%).[7]
These findings raise the question of whether different clinical factors are associated with a decrease in ESMCSA and PMCSA, respectively. To address this, we performed a post-hoc analysis of our prospective cohort study,[3, 7] and 102 male patients with COPD who undertook chest CT with three years of the interval were analyzed (Age; 71.3±8.3 years, GOLD stage; I/II/III/IV 20/47/28/7). Both ESMCSA and PMCSA significantly decreased in three years of interval (ESMCSA; 30.52±6.93 cm2 at baseline vs. 28.92±6.84 cm2 at follow-up, p<0.0001, PMCSA; 26.51±7.36 cm2 vs. 25.79±7.62 cm2, p=0.035). And the percentage of decrease in ESMCSA (([ESMCSA at baseline] – [ESMCSA at follow-up]) / [ESMCSA at baseline], %ΔESM) and that in PMCSA (%ΔPM) were significantly but mildly correlated (r=0.25, p=0.0097), which supports heterogeneous nature of muscle loss in patients with COPD. Concerning this, it is quite curious whether correlations between ESMCSA decline and PMCSA decline in their two large cohort studies were also heterogeneous.
Next, we compared clinical parameters associated with accelerated muscle loss using the cut-off value of double the mean value of %ΔESM (10%) or %ΔPM (5%). Patients with accelerated decline in PMCSA showed significantly greater decrease in BMI ([BMI at baseline] – [BMI at follow-up], ΔBMI) (p=0.0002), lower Charlson index (p=0.031) and higher WA% (p=0.040). Multivariate logistic regression analysis revealed that accelerated decline in ESMCSA was associated with WA% (Odds Ratio (OR) 1.39 [95% confidence interval (CI); 1.11-1.80], p=0.0039) and the number of moderate-to-severe exacerbations during follow-up (OR 1.37 [1.03-1.91], p=0.032).[7] On the other hand, accelerated decline in PMCSA was associated only with ΔBMI (OR 2.12 [1.28-3.53], p=0.0038).
The present analysis confirmed that muscle loss can occur heterogeneously and may reflect different aspects of patients with COPD. ESMs rather than PMs were more susceptible to decrease by frequent exacerbations. On the contrary, accelerated loss of PMs was significantly associated with accelerated weight loss.
As shown in Mason’s article, exacerbations of COPD cause skeletal muscle loss, however, following physical inactivity also affects skeletal muscle loss.[8] From this perspective, antigravity muscle which reflects physical activity will decrease more compared to other types of muscles.[3, 4] We can speculate that frequent exacerbations may contribute to accelerated loss of ESMs via physical inactivity. Accelerated loss of PMs, consist of a higher percentage of type 2 muscle fiber, may decrease due to exacerbations but it could be an indirect phenomenon. This may be partially because type 2 muscle fibers are more vulnerable to fasting than type 1 muscle fibers.[9]
Unlike Mason’s study, frequent exacerbations were not associated with accelerated decline in PMCSA in our analysis. This discrepancy was probably due to the small cohort. And the absolute value of PMCSA in the COPDGene or ECLIPSE cohort was higher than that of ours,[1, 3] which may be partially because patients with younger age and higher BMI were enrolled in those large cohorts. These differences in characteristics between our cohort and those cohorts might affect the results. Further analysis in those large cohorts would be expected to elucidate whether a rapid decline in PMCSA would be associated with mortality and whether ESMs would be more susceptible to frequent exacerbations than PMs. To be honest, we previously confirmed the validity of reported predictors of mortality,[3] which supports the validity and generalizability of the findings in our cohort. And an accelerated decline in ESMCSA demonstrated a significant association with not only exacerbations but also mortality even in our relatively small cohort. A decrease in ESMCSA is also shown to be significant for mortality in idiopathic pulmonary fibrosis.[10] Taken together, the clinical significance of evaluating ESMCSA would be suggested.
In conclusion, the present post-hoc analysis revealed that frequent exacerbations of COPD can contribute to accelerated loss of ESMs rather than PMs and it may come from physical inactivity. And it was also suggested that accelerated loss of PMs was significantly associated with nutrition status rather than frequent exacerbations. In a longitudinal analysis of skeletal muscle, it would be useful to analyze specific muscle groups according to physiological function and biological characteristics.
References
1. Mason SE, Moreta-Martinez R, Labaki WW, et al. Respiratory exacerbations are associated with muscle loss in current and former smokers. Thorax. 2021.
2. Guerri R, Gayete A, Balcells E, et al. Mass of intercostal muscles associates with risk of multiple exacerbations in COPD. Respir Med. 2010;104(3):378-88.
3. Tanimura K, Sato S, Fuseya Y, et al. Quantitative Assessment of Erector Spinae Muscles in Patients with Chronic Obstructive Pulmonary Disease. Novel Chest Computed Tomography-derived Index for Prognosis. Ann Am Thorac Soc. 2016;13(3):334-41.
4. Ikezoe T, Mori N, Nakamura M, et al. Effects of age and inactivity due to prolonged bed rest on atrophy of trunk muscles. Eur J Appl Physiol. 2012;112(1):43-8.
5. Johnson MA, Polgar J, Weightman D, et al. Data on the distribution of fibre types in thirty-six human muscles. An autopsy study. J Neurol Sci. 1973;18(1):111-29.
6. Tanabe N, Sato S, Tanimura K, et al. Associations of CT evaluations of antigravity muscles, emphysema and airway disease with longitudinal outcomes in patients with COPD. Thorax. 2021;76(3):295-7.
7. Tanimura K, Sato S, Sato A, et al. Accelerated Loss of Antigravity Muscles Is Associated with Mortality in Patients with COPD. Respiration. 2020;99(4):298-306.
8. Pitta F, Troosters T, Probst VS, et al. Physical activity and hospitalization for exacerbation of COPD. Chest. 2006;129(3):536-44.
9. Wang Y, Pessin JE. Mechanisms for fiber-type specificity of skeletal muscle atrophy. Curr Opin Clin Nutr Metab Care. 2013;16(3):243-50.
10. Nakano A, Ohkubo H, Taniguchi H, et al. Early decrease in erector spinae muscle area and future risk of mortality in idiopathic pulmonary fibrosis. Sci Rep. 2020;10(1):2312.
Statement of Ethics
The Ethics Committee of Kyoto University approved this study (approval No. E182), and all subjects provided written informed consent prior to participating.
Dear Editor,
We have read with great interest the article investigating the relationship between computed tomography (CT) findings of the patients with fibrotic-like patterns and telomere length after four months of acute COVID-19 infection. According to the literature and our experience, post-COVID interstitial lung disease is a potential public health problem. Thus, we aimed to share our concerns about the fibrotic-like patterns in this group of patients.
Post-COVID fibrosis is not as the same as the other interstitial lung diseases. In the article, the authors describe CT findings of fibrotic-like patterns as limited to reticulation, honeycomb cysts, and traction bronchiectasis. However, post-COVID fibrosis CT findings were shown to be more varied and may include parenchymal bands, irregular densities, and ground-glass areas (1–3). As we move towards the future, all of us need to create a common language, a lingua franca in the definition of post-COVID fibrosis. To achieve this, we need brainstorming and close cooperation.
It will also be helpful to elaborate the characteristics of the non-fibrotic pattern in the table. The clinical importance of the ground glass areas, which persist four months after active infection but not defined as fibrotic, is unknown. We consider that these patterns cannot be separated from fibrotic-like patterns precisely. Additionally, we can also classify parenchymal bands as fibrosis-like appearance. In our experience...
Show MoreTo the editor,
We thank N. Hürsoy and colleagues for their interest in our study of patients four months after severe COVID-19 [1]. We agree that there needs to be continued development of terms describing the radiographic appearance of post-COVID fibrotic-like patterns. We acknowledge that without the benefit of histopathology or serial imaging, our ability to define pulmonary fibrosis is limited.
The authors posit that parenchymal bands, irregular densities, and ground glass opacities, may be considered fibrotic-like patterns. We have included irregular densities, characterized as reticulations or traction bronchiectasis, as fibrotic-like changes. We did not include parenchymal bands [2], as these can be associated with atelectasis, which is common in COVID and can disappear over time [3]. Similarly, we did not include isolated ground glass opacities as fibrotic-like changes, as these have been found to decrease over time in CT lung cancer screening cohorts [4] and in other post COVID-19 cohorts [5, 6].
A priori, we evaluated for both previously established interstitial lung abnormality categories [7], as well as categories of radiographic abnormalities reported in Acute Respiratory Distress Syndrome (ARDS) survivors using an established scoring system [8]. This inclusive approach should facilitate meta-analyses and comparisons with future studies of COVID-19 survivors, interstitial lung disease studies, and studies of non-COVID ARDS survivors. Fu...
Show MoreWe have read the paper by Barker et al. (1) with interest. We congratulate the authors for conducting and publishing their prospective cohort study evaluating the effect of COPD discharge bundle on pulmonary rehabilitation (PR) referral and uptake following hospitalisation for acute exacerbation of COPD (AECOPD).
The authors have shown that the COPD discharge bundle had a positive effect on PR referral compared with a no bundle (17.5% (40 of 228) referral rate vs 0%(0 of 63)). This figure is lower than the expected 30% referral rate to PR following AECOPD (2). However, the paper offers no potential reasons for the lower referral rate.
The study had two bundle groups:
• COPD discharge bundle delivered by a current PR practitioner
• COPD discharge bundle delivered by a practitioner with no involvement in PR
Compared to delivery by a practitioner with no PR involvement, completion of the bundle delivery by a current PR practitioner resulted in higher referral and pick-up rates (60% vs 12% and 40% vs 32%, respectively). These results support the concept of integrating PR and hospital services.
Unfortunately, the completion rate (number of subjects who completed PR divided by the number of referrals) was disappointingly low. Also, there was no difference between the two bundle groups (13% (2 of 15) vs 12% (3 of 25)), as stated in the supplementary data.
It seems that patients' willingness or ability to complete PR is not af...
Show MoreWe thank Dr Abdulqawi for interest in our work (1). He comments that the referral, uptake and completion rates for pulmonary rehabilitation in the current study were lower than in a previous study by Jones and colleagues (2). We would caution against retrospective comparison with unmatched historical controls due to confounding factors such as differences in patient characteristics and practice pathways that may contribute to inaccurate point estimates.
We hypothesised that the COPD discharge bundle would impact on referral rates. Strengths of the current work include the prospective real-world nature of the study, with the research team having no involvement in treatment allocation. The clinical team delivering the bundle were blinded to the study objectives, thus minimising any Hawthorne effect.
Dr Abdulqawi raises the point that pulmonary rehabilitation completion rates were low in the current study (albeit based on a low denominator). The reasons for non-completion of PR are often complex and multi-factorial (3) and may not be directly related to referral source. However, what is clear is that without a referral for pulmonary rehabilitation, uptake and completion rates are zero.
1. Barker RE BL, Maddocks M, Nolan CM, Patel S, Walsh JA, Polgar O, Wenneberg J, Kon SSC, Wedzicha JA, Man WDC, Farquhar M. Integrating Home-Based Exercise Training with a Hospital at Home Service for Patients Hospitalised with Acute Exacerbations of COPD: Developing the M...
Show MoreThe paper by Hopkinson et al (1) provides unique and important data on smoking prevalence and COVID-19 symptoms, but their conclusion does not reflect the data well. The authors conclude “these data are consistent with people who smoke being at an increased risk of developing symptomatic COVID-19”. The study includes over 150,000 people with self-reported COVID-19 symptoms and over two million without such symptoms. It also includes data on over 25,000 people who were tested for SARS-CoV-2 and their test results. Based on our analysis of these more relevant data, we interpret the study differently. Our conclusion would be “these data are consistent with smokers having an increased risk of symptoms such as cough and breathlessness, but a decreased risk of having SARS-CoV-2 infection”.
The difficulty in interpreting these results is that both symptoms and testing are likely colliders in a causal model of smoking and COVID-19. The data reported on SARS-CoV-2 test results make it possible to compare smoking prevalence by age-group and sex in three groups: those who tested positive for SARS-CoV-2 (n=7,123); those who tested negative (n=16,765); and untested asymptomatic users (n=2,221,088, called “standard users” by the authors). Overall smoking prevalence was less in those tested (8.9%) than in all users of the app (11.0%). This might be thought of as a surprising finding – smoking-related symptoms should lead to testing – but can probably be explained by most asymptom...
Show MoreWe thank the authors for their letter in response to our paper(1). We disagree however that the data among the tested subgroup are more informative than our other findings. This is because the small subgroup (1.1% of app users - 0.7% negative, 0.3% positive, 0.1% result unknown) who reported that they had undergone testing for COVID-19 at this relatively early stage in the pandemic (the month from 24th March 2020) were heavily selected. Testing policies focused on healthcare workers and others interacting with healthcare - in particular, patients tested who may have been attending healthcare settings for other, non-COVID-19 related, conditions. As numerous health conditions are smoking-related this would tend to increase the exposure of smokers without COVID-19 to testing. For these reasons, as discussed in the paper, the finding that smoking rates were lower in those testing positive is likely to be due to sampling bias. Rather than being “more relevant”, extrapolation from this subgroup to population risk is entirely inappropriate.
Show MoreThe letter does appear to misunderstand the groups presented – the “standard user” group were not asymptomatic during the study. Rather, as set out in the first paragraph of the results, they were individuals who at the point of registration with the Zoe COVID Symptom Study App did not think that they already had COVID-19. Among this group of “standard users” current smokers were more likely to report the onset of new symptoms suggesting...
There is no question that the harms of smoking hugely outweigh any potential health benefits. Many people, ourselves included, assumed at the beginning of the pandemic that greater susceptibility to COVID-19 would be another harm of tobacco smoking to be added to the long list. Surprisingly, most of the epidemiological data published over the last year do not support this claim. Indeed whereas ex-smokers are consistently found to be at increased risk of both SARS-CoV-2 infection and severe COVID-19, current smokers are consistently at lower risk than ex-smokers and in many studies they appear to be at a lower risk than never smokers. The lower infection rate in smokers compared to non-smokers and ex-smokers has been found across 62 studies (1, 2), including now a full cohort with a dose-response pattern (3).
The authors’ response does not counter the observation that among nearly 27,000 individuals who had a SARS-CoV-2 test in their study, smoking prevalence was lower in those who tested positive than in those who tested negative.
In the OpenSAFELY study (4) too, the direction of the association between smoking and death from COVID-19 depends critically on what adjustments are made. The primary analysis appears to be based on a fully adjusted Cox regression model in which the hazard ratio for current smokers relative to never smokers was 0.89 (95% CI 0.82-0.97). The value (1.14; 1.05-1.23) cited by Hopkinson and colleagues is after adjusting for age and sex...
Show MoreThe idea that smoking might have a protective effect against COVID-19 is an intriguing, man bites dog type of story, which gives it a certain attraction. Happily, it appears to be false and the assumption of harm has turned out to be correct[1-5].
Our data show clearly that in the 2.4 million Zoe COVID Symptom Study App users, people who smoked were at increased risk of symptomatic COVID-19[2] and were at risk of more severe disease, which is consistent with a systematic review of patients hospitalized with COVID-19[4]. Our findings are also consistent with The UCL COVID-19 Social Study3 which found increased risk of test confirmed COVID-19 (OR=2.14 (1.49–3.08)) and with the COVIDENCE study where smokers had an OR of1.42 (0.99-2.05) for test-confirmed COVID-19[1].
The OpenSafely dataset based on data from the primary care records of 17.3 million adults in the UK found that, adjusted for age and sex, also identifies smoking as a risk factor - current smoking was associated with a hazard ratio for COVID-19-related death of 1.14 (1.05–1.23)5. The apparently protective effect in the “fully adjusted” model is due to over-correction producing collider bias.
Since any protective effect of smoking in COVID-19 appears to be illusory, pursuing a mechanism for it is unlikely to be productive.
References
Show More1 Holt H, Talaei M, Greenig M, et al. Risk factors for developing COVID-19: a population-based longitudinal study (COVIDENCE UK). medRxiv 2021:2021.2003...
With great interest we have read the study by Deshayes et al. The authors present two cases of silvernitrate (AgNO3) aspiration in laryngectomized patients.
Show More1) In both cases the applicator tip broke off.
2) The authors conclude that treatment should comprise oral antibiotics and one should refrain from bronchial washing with sodium chloride solution.
With this response we would like to reply to both points addressed above.
1.
Five years ago we were confronted with the aspiration of an AgNO3 applicator tip in a laryngectomized patient. After the incident we analyzed the case to prevent future AgNO3 applicator tip aspiration. The AgNO3 pencil, used in both our case and the cases in the current article, is specifically designed to treat dermal lesions like verruca which requires repeated use. The pencil therefore contains a relatively large volume of AgNO3. AgNO3 is a brittle substance. When the pencil is used with a little too much pressure there is risk for the tip to break, and when used in a tracheostomy, there is risk for aspiration.
Our case led us to immediately stop using the AgNO3 pencils for treatment of granulation tissue in a tracheostomy. We strongly recommend the use of disposable AgNO3 cutaneous sticks for the treatment of granulation tissue around a tracheostomy. The disposable sticks contains less volume of AgNO3. Moreover, the stick is easier to use in narrow spaces like a tracheostomy.
2.
Aspiration of AgNO3 i...
To the editor,
We read the interesting report by Mason et al, “Respiratory exacerbations are associated with muscle loss in current and former smokers”.[1] In this study, the authors demonstrated that exacerbations are associated with accelerated loss of pectoralis muscles (PMs) in two large observational cohorts and quantified the impact of each annual exacerbation as the equivalent of 6 months of age-expected decline.
Show MoreSkeletal muscle loss is one of the major systemic manifestations associated with mortality in patients with COPD. Not only systemic muscle loss but also loss of specific muscle groups are associated with clinical outcomes such as exacerbations and mortality in patients with COPD.[2, 3] Moreover, muscle loss can occur heterogeneously.[4] This may be partially because each muscle group has its physiological function or biological characteristics such as muscle fiber composition. This supports that loss of specific muscle groups may have different implications in the clinical course of COPD.
We previously analyzed the cross-sectional area of erector spinae muscles (ESMCSA) and that of PMs (PMCSA) in male patients with COPD using chest CT.[3] ESMs are ones of antigravity muscles which are involved in maintaining an upright posture. PMs play an important role in the movement of upper limbs. Both muscles also act as accessory inspiratory muscles. ESMs are composed of 60% type 1 fibers and 40% of type 2 fibers and PMs are composed in the reverse...
Pages