Quality of life after ICU: 1-year follow-up in patients with and without COVID
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to perform a 1-year follow-up after ICU discharge and evaluate post-intensive care syndrome (PICS) in both COVID (GroupCov) and NON COVID (GroupNCov) patients. METHODS: All consecutive patients discharged from our Intensive Care Unit (ICU) from June to December 2022 were prospectively screened. Scheduled in-person visits were carried on 3, 6, and 12 months after ICU discharge to evaluate physical, cognitive, and mental health status using different scale evaluations (SF-36, Barthel Index, ISI score, PCL-5 score, MNA-sf score, Fatigue Severity Score, MoCA Test, HADS and GDS) by means of standardized questionnaires. RESULTS: Eighty patients (50 GroupCov vs 30 GroupNCov) were initially included, but some patients did not attend all follow-up visits. At 1-year follow-up, 60 patients (30 COVID-19 and 30 non-COVID) completed all evaluations. Both groups showed PICS, but GroupCov had a better nutritional status, better outcomes in physical evaluations, and a better perception of Quality of Life (QoL) and mental health status, but a worse cognitive assessment in the MoCA Test. Moreover, heterogeneity analysis showed that GroupNCov patients had the same trend during follow-up, while in GroupCov different trends were observed over time, especially a worse nutritional state, often found in older patients, that was related to a longer hospital stay and worse psychophysical outcomes. CONCLUSIONS: This study shows that PICS in SARS-COV2 patients is not always homogeneous, and that different clusters of psychophysical patterns may develop over time. Although our study was only observational, it seems from our preliminary results that performing a follow-up could be the basis for a secondary prevention and to develop new therapeutic strategies after patients discharge from ICU.
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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 | 0.003 |
| 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".