Mortality differences among organisms causing septicemia in hemodialysis patients
Bibliographic record
Abstract
Septicemia is a serious problem in hemodialysis patients because it can lead to life-threatening complications and a persistently elevated risk of death. Most analyses have not examined whether there are differences in mortality risk among the organisms that cause these episodes of septicemia. This study was a retrospective cohort analysis of first septicemia hospitalizations during the first year of hemodialysis. Time to death (both in-hospital and within 12 weeks post-discharge) was compared among the different septicemia-causing organisms based on discharge diagnoses in Medicare billing data from 1996 to 2001. The effect of various complications on mortality risk was also evaluated. There were 22,130 septicemia hospitalizations identified. The most common organism identified was Staphylococcus aureus (27%), with no other organism having an incidence >10%. The overall unadjusted death rate from admission through 12 weeks of follow-up was 34%. During the first hospitalization, the death rate was 14%, and during the 12-week period after the hospitalization it was 20%. In adjusted analyses, S. aureus was associated with a 20% higher risk of death both during the in-hospital period and the 12-week post-discharge period, when compared with all other specified organisms. Hospitalizations complicated by meningitis, stroke, or endocarditis were also associated with increased risk of mortality, independent of the organism causing septicemia. Septicemia hospitalizations are associated with a high mortality rate--both during the initial hospitalization and after discharge. Meningitis, stroke, and endocarditis represent particularly serious complications. Overall, septicemia hospitalizations (especially for S. aureus) are serious events, and patients would benefit from better treatment and prevention.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".