Returning to work and health status at 12 months among patients with COVID-19 cared for in intensive care—A prospective, longitudinal study
Bibliographic record
Abstract
OBJECTIVE: Intensive care unit (ICU) stay for a serious illness has a long-term impact on patients' physical and psychological well-being, affecting their ability to return to their everyday life. We aimed to investigate whether there are differences in health status between those who return to work and those who do not, and how demographic characteristics and illness severity impact patients' ability to return to work 12 months after intensive care for COVID-19. RESEARCH METHODOLOGY: This was a prospective longitudinal cohort study. The participants were patients who had been in intensive care for COVID-19 and had worked before contracting COVID-19. Data on return to previous occupational status, demographic data, comorbidities, intensive care characteristics, and health status were collected at a 12-month follow-up visit. SETTING: General ICU at the Uppsala University Hospital in Sweden. RESULTS: Seventy-three participants were included in the study. Twelve months after discharge from the ICU, 77 % (n = 56) had returned to work. The participants who were unable to return to work reported more severe health symptoms. The (odds ratio [OR] for not returning to work was high for critical illness OR, 12.05; 95 % confidence interval [CI], 2.07-70.29, p = 0.006) and length of ICU stay (OR, 1.06; 95 % CI, 1.01-1.11, p = 0.01) CONCLUSION: Two-thirds of the participants were able to return to work within 1 year after discharge from the ICU. The primary factors contributing to the failure to work were duration of the acute disease and presence of severe and persistent long-term symptoms. IMPLICATIONS FOR CLINICAL PRACTICE: Patients' health status must be comprehensively assessed and their ability to return to work should be addressed in the rehabilitation process. Therefore, any complications faced by the patients must be identified and treated early to increase the possibility of their successful return to work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".