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A Description of Post Intensive Care Syndrome in COVID19 Survivors

2021· article· en· W3174012796 on OpenAlexaboutno aff
Kavya Kommaraju, Michelle Biehl, Emma Bishop, Joshua Veith, K. C. Sarin, Jaclyn O’Brien, K. Bash, M. Holztrager

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntensive care unitIntensive carePopulationAnxietyDepression (economics)Coronavirus disease 2019 (COVID-19)ARDSRetrospective cohort studyEmergency medicineInternal medicinePsychiatryIntensive care medicineDiseaseLung

Abstract

fetched live from OpenAlex

RATIONALE: Over 40 million people have recovered from COVID-19. Many of them are intensive care unit (ICU) survivors who are known to frequently face Post Intensive Care Syndrome (PICS), a constellation of new or worsening physical, mental and cognitive impairments that occur after ICU stay. There is scarce data describing PICS in COVID-19 survivors. The Cleveland Clinic established a new Post ICU Recovery Clinic (PIRC) that began seeing COVID-19 survivors in May 2020. The objective of this abstract is to report the incidence of PICS in COVID-19 ICU survivors.METHODS: A retrospective chart review of all COVID-19 patients seen in PIRC from December 2019 to September 2020 was performed. In-hospital variables collected included demographics and clinical course. PIRC visit variables collected included oxygen requirement, scores on several validated questionnaires screening for depression, anxiety, post-traumatic stress disorder (PTSD), cognitive function, instrumental and activities of daily living (iADL and ADL), 6-minute walk test, pulmonary function tests, and change in occupational and driving status. Statistics reported reflect exclusion of the missing data points. RESULTS: A total of 63 patients were seen in PIRC. COVID-19 ICU survivors comprised of 83% (n= 52) and of these, 46.2% (n = 24) had ARDS. Our population was 58% male with near equal Caucasian and African American distribution. The median hospital and ICU length of stay was as 12.5 (IQR 9.0-18.5) and 6 (3.0-12.0) days respectively. PIRC visits took place roughly two months after hospital discharge and 61% (n=31) were virtual visits. Twenty one (45%) patients had a new oxygen requirement, six (38%) had new mild or moderate cognitive impairment as identified by the Montreal Cognitive Assessment (MOCA), 11(52%) screened positive for new anxiety or depression as identified by the Patient Health Questionnaire-4 (PHQ-4), three patients screened positive for new PTSD as identified by the Primary Care PTSD Screen for DSM-5 (PC-PTSD-5) or Impact of Event Scale-Revised (IES-R) survey. Majority were independent in all ADL and iADL (91% and 71% respectively). Median distance on 6-minute walk test, % predicted of FEV1, FVC, TLC, and DLCO was 1205 feet, 86.2, 79.7, 74.9, and 62.4 respectively. From the 64% of patients who were working and 94% who were driving prior to hospitalization, only 26% and 78% had returned to those activities respectively. CONCLUSIONS: COVID-19 ICU survivors experience every aspect of PICS two months after hospital discharge. These survivors require comprehensive evaluation to facilitate diagnosis and identify treatments to promote holistic recovery.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.267
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes1
Has abstractyes

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