Intensive care support and clinical outcomes of patients with Ebola virus disease (EVD) in West Africa
Bibliographic record
Abstract
PURPOSE: We investigate the impact on outcome of different levels of supportive treatment in Ebola virus disease (EVD). The NGO EMERGENCY delivered care sequentially at two Ebola Treatment Centres (ETC) in Sierra Leone: first at Lakka (fluids, symptomatic, antibiotic, antimalaria treatment, and hospital level medical care), and thereafter in Goderich, adding organ support in the only African ETC with an equipped and staffed intensive care unit (ETC-ICU). METHODS: The primary outcome in this retrospective cohort study was in-ETC mortality. Secondarily, we used multivariable logistic regression to investigate the independent impact of the IC on mortality by comparing patients in two ETCs, adjusting for potential confounders, including the viral load (base-10 logarithm in copies/ml) (LVL), modelled as a piecewise linear function. Mortality was plotted versus LVL. Confidence bands were constructed by a bootstrap technique. The number of hospital-free days within 28 was computed to assess the burden of EVD. RESULTS: Data from 229 EVD patients were analysed (123 in Lakka, 106 in Goderich). Crude analysis showed a non-statistically significant difference in mortality (57.7% in Lakka vs 50.0% in Goderich; p = 0.19). Age and LVL were associated with mortality. Adjusted mortality was lower at the Goderich ICU-ETC (p = 0.055). This difference was observed with 80% confidence for patients with LVL between 7.5 and 8.5 copies/ml. Hospital-free days (of 28 days) were greater (7.7 vs 5.5; p = 0.03) for patients treated in the ICU-ETC. CONCLUSIONS: Provision of critical care to patients with EVD is feasible in resource-limited settings and was associated with improved survival and less time in hospital.
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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 | 0.006 |
| 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 | 0.002 |
| 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".