Survival of HIV-Infected Patients in ICU in the Era of Highly Active Antiretroviral Therapy
Bibliographic record
Abstract
Background. In the era of combination antiretroviral therapy (cART), mortality and morbidity of HIV patients has declined. However, data suggest that intensive care unit (ICU) admission rates have not declined. In this study, we describe the epidemiology of critically ill HIV-infected patients and identify prognostic markers for 30-day mortality. Methods. Data were retrospectively collected on all HIV-infected patients admitted to five intensive care units (ICUs) in Edmonton, Alberta from July 2002 to July 2014. Univariate and multivariable (Cox proportional hazards regression) analyses were performed to identify factors associated with mortality. Results. During the study period, 282 patients had 343 discrete ICU admissions. Mean age was 44 (±10 SD), 202 (59%) were male, 203 (59%) had hepatitis C virus (HCV) coinfection, and 229 (67%) had documented polysubstance abuse. Median CD4 count was 130 (IQR 30-300) cells/mm3and median viral load 20,500 (IQR 37-220,000) copies/mL. Only 133 (39%) patients were receiving cART while 33 (10%) were newly diagnosed in the ICU. Most common admission diagnosis was sepsis (50%) and 48% had respiratory failure. Most patients [259 (76%)] received mechanical ventilation and 169 (49%) received vasopressor support. Care was limited in 89 (26%) patients and withdrawn in 53 (16%). Seventy-four (22%) patients died within 30 days of ICU admission. Correlates of 30-day mortality on univariate analysis included newly diagnosed HIV infection, APACHE II score, shock, and limitations on or withdrawal of care. On multivariable analysis, APACHE II (adjusted hazard ratio [aHR] 1.06; 95% CI 1.02–1.09, p = 0.001), care limitation (aHR 4.6; 95% CI 2.3-9.2, p < 0.001) and care withdrawal (aHR 5.2; 95% CI 2.7-9.8, p < 0.001) were independently associated with 30-day mortality. Surprisingly, CD4 count and viral load were not independently associated with mortality. Conclusion. Mortality of critically ill HIV-infected patients remains high in the cART era. Substance abuse and HCV co-infection were common in our population. In this young cohort, one in four patients had care limited. APACHE II score, care limitation and care withdrawal were independently associated with mortality. This suggests that HIV-positivity and degree of immune suppression may not be the chief determinants of mortality in this vulnerable population. Disclosures. All authors: No reported disclosures.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".