Background Identifying subtypes of acute respiratory failure survivors may facilitate patient selection for post-intensive care unit (ICU) follow-up clinics and trials.
Methods We conducted a single-centre prospective cohort study of 185 acute respiratory failure survivors, aged ≥ 65 years. We applied latent class modelling to identify frailty subtypes using frailty phenotype and cognitive impairment measurements made during the week before hospital discharge. We used Fine-Gray competing risks survival regression to test associations between frailty subtypes and recovery, defined as returning to a basic Activities of Daily Living disability count less than or equal to the pre-hospitalisation count within 6 months. We characterised subtypes by pre-ICU frailty (Clinical Frailty Scale score ≥ 5), the post-ICU frailty phenotype, and serum inflammatory cytokines, hormones and exosome proteomics during the week before hospital discharge.
Results We identified five frailty subtypes. The recovery rate decreased 49% across each subtype independent of age, sex, pre-existing disability, comorbidity and Acute Physiology and Chronic Health Evaluation II score (recovery rate ratio: 0.51, 95% CI 0.41 to 0.63). Post-ICU frailty phenotype prevalence increased across subtypes, but pre-ICU frailty prevalence did not. In the subtype with the slowest recovery, all had cognitive impairment. The three subtypes with the slowest recovery had higher interleukin-6 levels (p=0.03) and a higher prevalence of ≥ 2 deficiencies in insulin growth factor-1, dehydroepiandrostersone-sulfate, or free-testosterone (p=0.02). Exosome proteomics revealed impaired innate immunity in subtypes with slower recovery.
Conclusions Frailty subtypes varied by prehospitalisation frailty and cognitive impairment at hospital discharge. Subtypes with the slowest recovery were similarly characterised by greater systemic inflammation and more anabolic hormone deficiencies at hospital discharge.
- critical care
- clinical epidemiology
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Contributors MRB, MSM and DJL conceived of the study and its design. MRB had full access to the data. MRB, RAF and EC take responsibility for the integrity of the data and accuracy of the analysis. MRB, LRP, SPN and AJ organised and entered data. MRB, LRP, SPN, AJ, MRO, MJC, DMN, EC and DJL contributed to data analyses. MRB, LRP, RAF, MRO, MJC, DMN, EC, MSM and DJL contributed to data interpretation. MRB drafted the manuscript. All authors critically revised the drafted manuscript and approve of the submitted manuscript.
Funding MRB is supported by NIH grant K23 AG045660, a faculty research fellowship from the Columbia University Ageing Centre, and the Columbia University Irving Institute (NIH grant UL1 TR001873). DJL was supported by NIH grants R01 HL103676, R01 HL137234 and K24 HL131937. MSM was supported by NIH grant K24 AG036778.
Competing interests None declared.
Patient consent for publication Not required.
Ethics approval The Columbia University institutional review board approved this study (protocols AAAI1864 and AAAN7107).
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available upon reasonable request. Deidentified participant data are available from MRB, MD, MS ORCID: https://orcid.org/0000-0003-4670-3433.
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