Sepsis as a cause and consequence of acute kidney injury: Program to Improve Care in Acute Renal Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Sepsis commonly contributes to acute kidney injury (AKI); however, the frequency with which sepsis develops as a complication of AKI and the clinical consequences of this sepsis are unknown. This study examined the incidence of, and outcomes associated with, sepsis developing after AKI. METHODS: We analyzed data from 618 critically ill patients enrolled in a multicenter observational study of AKI (PICARD). Patients were stratified according to their sepsis status and timing of incident sepsis relative to AKI diagnosis. RESULTS: We determined the associations among sepsis, clinical characteristics, provision of dialysis, in-hospital mortality, and length of stay (LOS), comparing outcomes among patients according to their sepsis status. Among the 611 patients with data on sepsis status, 174 (28%) had sepsis before AKI, 194 (32%) remained sepsis-free, and 243 (40%) developed sepsis a median of 5 days after AKI. Mortality rates for patients with sepsis developing after AKI were higher than in sepsis-free patients (44 vs. 21%; p < 0.0001) and similar to patients with sepsis preceding AKI (48 vs. 44%; p = 0.41). Compared with sepsis-free patients, those with sepsis developing after AKI were also more likely to be dialyzed (70 vs. 50%; p < 0.001) and had longer LOS (37 vs. 27 days; p < 0.001). Oliguria, higher fluid accumulation and severity of illness scores, non-surgical procedures after AKI, and provision of dialysis were predictors of sepsis after AKI. CONCLUSIONS: Sepsis frequently develops after AKI and portends a poor prognosis, with high mortality rates and relatively long LOS. Future studies should evaluate techniques to monitor for and manage this complication to improve overall prognosis.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it