Rhabdomyolysis, Acute Kidney Injury, and Mortality in Ebola Virus Disease: Retrospective Analysis of Cases From the Eastern Democratic Republic of the Congo, 2019
Bibliographic record
Abstract
BACKGROUND: Skeletal muscle injury in Ebola virus disease (EVD) has been reported, but its association with morbidity and mortality remains poorly defined. METHODS: This retrospective study included patients admitted to 2 EVD treatment units over an 8-month period in 2019 during an EVD epidemic in the Democratic Republic of the Congo. RESULTS: An overall 333 patients (median age, 30 years; 58% female) had at least 1 creatine kinase (CK) measurement (n = 2229; median, 5/patient [IQR, 1-11]). Among patients, 271 (81%) had an elevated CK level (>380 U/L); 202 (61%) had rhabdomyolysis (CK >1000 IU/L); and 45 (14%) had severe rhabdomyolysis (≥5000 U/L). Among survivors, the maximum CK level was a median 1600 (IQR, 550-3400), peaking 3.4 days after admission (IQR, 2.3-5.5) and decreasing thereafter. Among fatal cases, the CK rose monotonically until death, with a median maximum CK level of 2900 U/L (IQR, 1500-4900). Rhabdomyolysis at admission was an independent predictor of acute kidney injury (adjusted odds ratio, 2.2 [95% CI, 1.2-3.8]; P = .0065) and mortality (adjusted hazard ratio, 1.7 [95% CI, 1.03-2.9]; P = .037). CONCLUSIONS: Rhabdomyolysis is associated with acute kidney injury and mortality in patients with EVD. These findings may inform clinical practice by identifying laboratory monitoring priorities and highlighting the importance of fluid management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".