The association between arrival potassium and 30-day survival following resuscitation from out-of-hospital cardiac arrest: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: It is unknown whether there is an association between initial serum potassium level and short-term survival in out-of-hospital cardiac arrest (OHCA) survivors. The aim of this study was to describe potential associations between first recorded potassium level and 30-day survival in patients surviving OHCA. METHODS: We identified 4,894 patients who had return of spontaneous circulation (ROSC) at hospital arrival, and a registered post-OHCA serum-potassium value, using Danish nationwide registry data from 2001-2019. Potassium values were divided into seven predefined levels: < 2.5, 2.5-2.9, 3.0-3.4, 3.5-4.6, 4.7-5.5, 5.5-6.0, > 6.0 mmol/L. Thirty-day survival was estimated using a multivariable Cox regression (reference normokalemia 3.5-4.6 mmol/L). The multivariable model included age, sex, Charlson comorbidity index (including chronic kidney disease), witnessed status, performance of bystander cardiopulmonary resuscitation (CPR) and first registered heart rhythm. RESULTS: Over the 30-day follow-up period, survival rates in the seven strata were as follows: 25 (51.0%), 119 (53.6%), 512 (65.4%), 1,631 (57.9%), 220 (32.7%), 34 (22.8%), and 46 (22.7%), respectively. Thirty-day survival was significantly lower for all groups with hyperkalemia compared with normokalemia: 4.7-5.5 mmol/L: (average risk ratio (RR): 0.72, 95% confidence interval (95% CI): 0.66-0.78); 5.5-6.0 mmol/L: (average RR: 0.60, 95% CI: 0.47-0.73); > 6.0 mmol/L: (average RR: 0.56, 95% CI: 0.46-0.66). Survival did not differ significantly in patients with hypokalemia compared with normokalemia. CONCLUSIONS: In OHCA survivors, hyperkalemia was associated with reduced 30-day survival compared with normokalemia, independent of age, sex, comorbidity burden and pre-hospital OHCA-characteristics. Conversely, hypokalemia was not associated with reduced 30-day survival.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".