Physical function and fatigue recovery at <scp>6 months</scp> after hospitalization for <scp>COVID</scp>‐19
Bibliographic record
Abstract
INTRODUCTION: There are an increasing number of individuals with long-term symptoms of coronavirus-19 disease (COVID-19); however, the prognosis for recovery of physical function and fatigue after COVID-19 is uncertain. OBJECTIVE: To report the changes in functional recovery between 1 and 6 months after hospitalization of adults hospitalized for COVID-19 and explore the baseline factors associated with physical function recovery. DESIGN: A prospective cohort study. SETTING: Tertiary care hospital. PARTICIPANTS: U.S. adult COVID-19 survivors. INTERVENTION: N/A. MAIN OUTCOME MEASURES: Telephone interviews assessed three outcome domains: basic and instrumental activities of daily living (ADLs) performance, fatigue, and general physical function (Health Assessment Questionnaire [HAQ]). RESULTS: The age of participants (n = 92) ranged from 22 to 95 years (54.3 ± 17.2). Across outcome domains, a majority (63%-67%) of participants developed new ADL impairment, fatigue, or worsening HAQ severity by 1 month. Of those, 50%-79% partially or fully recovered by 6 months, but 21%-50% did not recover at least partially. Fifteen to 30% developed new impairment between 1 and 6 months. For those without any improvement in ADL impairments at 6 months, lower socioeconomic status was significantly more common (p = .01) and age ≥ 65 (p = .06), trending toward being more common. CONCLUSION: In this cohort, a substantial proportion of the participants who developed new ADL impairment, worsening fatigue, or HAQ severity after hospitalization for COVID-19 did not recover at least partially by 6 months after discharge. Evaluating functional status 1 month after discharge may be important in understanding functional prognosis and recovery after hospitalization for COVID-19.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".