Hyperchloremia and moderate increase in serum chloride are associated with acute kidney injury in severe sepsis and septic shock patients
Bibliographic record
Abstract
Acute kidney injury and hyperchloremia are commonly present in critically ill septic patients. Our study goal was to evaluate the association of hyperchloremia and acute kidney injury in severe sepsis and septic shock patients. In this retrospective cohort study in a provincial tertiary care hospital, adult patients with severe sepsis or septic shock and serum chloride measurements were included. Serum chloride was measured on a daily basis for 48 hours. Primary outcome was development of acute kidney injury (AKI) and association of AKI and serum chloride parameters was analyzed. A total of 240 patients were included in the study, 98 patients (40.8 %) had hyperchloremia. The incidence of acute kidney injury (AKI) was significantly higher in the hyperchloremia group (85.7 % vs 47.9 %; p < 0.001). Maximal chloride concentration in the first 48 hours ([Cl - ] max ) was significantly associated with AKI. In multivariate analysis, [Cl - ] max was independently associated with AKI [adjusted odds ratio (OR) for AKI = 1.28 (1.02–1.62); p = 0.037]. The increase in serum chloride (Δ[Cl - ] = [Cl - ] max – initial chloride concentration) demonstrated a dose-dependent relationship with severity of AKI. The mean Δ[Cl - ] in patients without AKI was 2.1 mmol/L while in the patients with AKI stage 1, 2 and 3 the mean Δ[Cl - ] was 5.1, 5.9 and 6.7 mmol/L, respectively. A moderate increase in serum chloride (Δ[Cl - ] ≥ 5 mmol/L) was associated with AKI [OR = 5.70 (3.00–10.82); p < 0.001], even in patients without hyperchloremia [OR = 8.25 (3.44–19.78); p < 0.001]. Hyperchloremia is common in severe sepsis and septic shock and independently associated with AKI. A moderate increase in serum chloride (Δ[Cl - ] ≥5 mmol/L) is associated with AKI even in patients without hyperchloremia.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".