Hyperlactatemia and concurrent use of antiretroviral therapy among HIV infected patients in Uganda
Bibliographic record
Abstract
BACKGROUND: We determined the prevalence and factors associated with hyperlactatemia among HIV patients admitted on the emergency ward of a national hospital in Uganda. OBJECTIVE: We were specifically interested in knowing whether there was an association between clinically significant hyperlactatemia and concurrent antiretroviral therapy (ART) use. METHODS: A cross sectional descriptive study enrolled 303 HIV infected patients at a national referral hospital between March and April 2008. We consecutively recruited all eligible HIV infected patients above 18 years admitted on the emergency ward. Data were collected on socio-demographic, clinical and laboratory characteristics. Lactate levels were measured using the Accutrend® portable lactate analyser. Data analysis was performed using Stata 10.0; P-value of < 0.05 was considered to be significant. RESULTS: Three hundred and three HIV infected patients were recruited. Prevalence of hyperlactatemia (lactate ≥2.5mmol/L) was 252 (83.2%). Clinically significant hyperlactatemia (lactate ≥4mmol/L) was present in 105/303(34.6%) patients. There was no association between use of ART and clinically significant hyperlactatemia. In the multivariate analysis, body weakness 1.91 (1.09-3.35), skin rash 3.18 (1.11-9.10) and tachypnoea 1.04 (1.01-1.07) were independently associated with clinically significant hyperlactatemia. CONCLUSION: There was a high prevalence of clinically significant hyperlactatemia among HIV infected patients but it was not associated with concurrent antiretroviral use.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".