Mechanical ventilation and outcomes in COVID-19 patients admitted to intensive care unit in a low-resources setting: A retrospective study
Bibliographic record
Abstract
Objective: To describe the strategies and outcomes of mechanical ventilation in a poorly equipped facility. Methods: This retrospective descriptive study included patients with COVID-19 who were admitted to the intensive care unit (ICU) and mechanically ventilated between September 1, 2020, and May 31, 2021. Data were collected from medical records and databases. Results: 54 Patients aged (62.9±13.3) years were included. Among these cases, 79.6% had at least one comorbidity. On admission, all patients had hypoxia. The median peripheral oxygen saturation in room air was 76% (61%, 83%). Non-invasive ventilation (NIV) was performed in 75.9% of the patients, and invasive mechanical ventilation (IMV) in 68.5%. IMV was performed on patients due to severe coma (8.1%), failure of standard oxygen therapy (27.0%), and failure of NIV (64.9%). An arterial blood gas test was performed in 14.8% of the patients. NIV failed in 90.2% of cases and succeeded in 9.8%. IMV was successful in 5.4% of cases, vs . 94.6% of mortality. The overall mortality rate of patients on ventilation in the ICU was 88.9%. The causes of death included severe respiratory distress syndrome (85.2%), multiple organ failure (14.8%), and pulmonary embolism (13.0%). Conclusions: The ventilation management of COVID-19 patients in the ICU with NIV and IMV in a scarce resource setting is associated with a high mortality rate. Shortcomings are identified in ventilation strategies, protocols, and monitoring. Required improvements were also proposed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".