Evidence map›Paper›PMID 33298583›Full record

ArticleThorax2021

Frailty subtypes and recovery in older survivors of acute respiratory failure: a pilot study.

Matthew R Baldwin, Lauren R Pollack, Richard A Friedman, Simone P Norris, Azka Javaid, Max R O'Donnell, Matthew J Cummings, Dale M Needham, Elizabeth Colantuoni, Mathew S Maurer and 1 more

Open access · greenAbstract read
In one paragraph

Article in Thorax, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Article
  8. Identifying Comorbid Subtypes of Patients With Acute Respiratory Failure.American journal of critical care : an official publication, American Association of Critical-Care Nurses · 2023
    Article
  9. Long-term recovery after critical illness in older adults.Current opinion in critical care · 2022
    Review
  10. Article
  11. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 1 country.

Matthew R BaldwinPulmonary, Allergy, and Critical Care, Columbia University Irving Medical Center, New York, New York, USA mrb45@cumc.columbia.edu.ORCID 0000-0003-4670-3433
Lauren R PollackMedicine, University of Washington School of Medicine, Seattle, Washington, USA.
Richard A FriedmanBioinformatics, Columbia University Irving Medical Center, New York, New York, USA.
Simone P NorrisPulmonary, Allergy, and Critical Care, Columbia University Irving Medical Center, New York, New York, USA.
Azka JavaidPulmonary, Allergy, and Critical Care, Columbia University Irving Medical Center, New York, New York, USA.
Max R O'DonnellPulmonary, Allergy, and Critical Care, Columbia University Irving Medical Center, New York, New York, USA.
Matthew J CummingsPulmonary, Allergy, and Critical Care, Columbia University Irving Medical Center, New York, New York, USA.
Dale M NeedhamOutcomes After Critical Illness and Surgery Group, Johns Hopkins University, Baltimore, Maryland, USA.ORCID 0000-0002-9538-0557
Elizabeth ColantuoniOutcomes After Critical Illness and Surgery Group, Johns Hopkins University, Baltimore, Maryland, USA.
Mathew S MaurerCardiology, Columbia University Irving Medical Center, New York, New York, USA.
David J LedererPulmonary, Allergy, and Critical Care, Columbia University Irving Medical Center, New York, New York, USA.ORCID 0000-0001-5258-0228
Columbia University Irving Medical Center · USJohns Hopkins University · USRegeneron (United States) · USUniversity of Washington · US

Funding

Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
Subclinical Interstitial Lung Disease in MESA and FAR-ILDR01HL103676 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GARCIA, CHRISTINE KIM · 2011 to 2020
$6.4M
Obstructive Sleep Apnea and Subclinical Lung Injury in Health and DiseaseR01HL137234 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GOTTLIEB, DANIEL J, JELIC, SANJA · 2018 to 2021
$3.2M
Midcareer Mentoring Award for Patient Oriented Research in Geriatric CardiologyK24AG036778 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MAURER, MATHEW S · 2010 to 2020
$1.6M
Frailty, Palliative Care Needs, and Outcomes in Older Survivors of Critical IllneK23AG045560 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BALDWIN, MATTHEW R · 2014 to 2018
$750k
Mentored Patient Oriented Research in Pulmonary Fibrosis and Lung TransplantationK24HL131937 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI LEDERER, DAVID J. · 2016 to 2018
$352k
Added Value of Primary Care-Senior Center Linkages for Health and FunctioningR21AG045660 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI NOEL, POLLY H. · 2013 to 2014
$352k
NCATS NIH HHS UL1 TR001873NHLBI NIH HHS K24 HL131937NHLBI NIH HHS R01 HL103676NHLBI NIH HHS R01 HL137234NIA NIH HHS K23 AG045560NIA NIH HHS K24 AG036778NIA NIH HHS L30 AG040838NIA NIH HHS R21 AG045660
6 · The paper itself

Abstract

backgroundIdentifying subtypes of acute respiratory failure survivors may facilitate patient selection for post-intensive care unit (ICU) follow-up clinics and trials.

methodsWe 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.

resultsWe 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.

conclusionsFrailty 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.

Indexed as

Activities of Daily LivingAgedAged, 80 and overCognition DisordersCytokinesFemaleFrailtyHormonesHospitalizationHumansIntensive Care UnitsLatent Class AnalysisMalePatient DischargePhenotypePilot ProjectsCytokinesHormonesARDSclinical epidemiologycritical care

Identifiers

PMID33298583
PMCPMC8187474
OpenAlexW3110961083

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.