Rehabilitation of COVID-19 patients with respiratory failure and critical illness disease in Slovenia: an observational study
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection often causes pneumonia and respiratory failure that may lead to postintensive care syndrome, including critical illness neuropathy (CIN) and critical illness myopathy (CIM). The data on the rehabilitation outcomes of post-novel coronavirus disease (COVID) patients with CIN and CIM following respiratory failure and mechanical ventilation are still limited. To address this, we enrolled in our prospective observational study a sample of 50 consecutive COVID-19 patients admitted to our facility between 2 November 2020 and 3 May 2021 with electrophysiologically confirmed or clinically suspected diagnosis of CIN/CIM. The functional abilities were assessed at admission and discharge with the Functional Independence Measure (FIM), The Canadian Occupational Performance Measure, 10-metre walk test, 6-min walk test and the de Morton Mobility Index. The gain in motor FIM and the length of stay were used as an index of rehabilitation efficiency. Nutritional status was also assessed using anthropometric measurements and bioelectrical Impedance analysis. Psychologic evaluation was performed at admission only. At admission, functional limitations and severe malnutrition were present in all patients with psychologic problems in about one third. At discharge (42 ± 16 days later), clinically important and statistically significant improvements were found in all outcome measures, which was also noted by the patients. The gain in motor FIM was larger with the longer length of stay up to 2 months and plateaued thereafter. We conclude that post-COVID-19 patients who develop CIN/CIM following respiratory failure can improve functional and nutritional status during inpatient rehabilitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".