Initial Rhythm and Resuscitation Outcomes for Patients Developing Cardiac Arrest in Hospital
Bibliographic record
Abstract
BACKGROUND: Health care resource allocation remains challenging in lower middle income countries such as Kenya with meager resources being allocated to resuscitation and critical care. The causes and outcomes for in-hospital cardiac arrest and resuscitation have not been studied. OBJECTIVES: This study sought to determine the initial rhythm and the survival for patients developing in-hospital cardiac arrest. METHODS: This was a prospective study for in-hospital cardiac arrest in 6 Kenyan hospitals from July 2014 to April 2016. Resuscitation teams were utilized to collect data during resuscitation using a standardized protocol. Patients with do-not-resuscitate orders, trauma, postsurgical, and pregnancy-related complications were excluded. The Modified Early Warning Score (MEWS)- systolic blood pressure, heart rate, respiration rate, temperature, and responsiveness-was determined based on worst parameters at least 4 hours prior to the arrest. RESULTS: A total of 353 patients with cardiac arrest were included over 19 months. The mean age was 61 years, 53.5% were male, and admission diagnoses included cardiovascular disease (15%), pneumonia 18.13%, and cancer 9%. The mean MEWS was 4.48 and low, intermediate, and high MEWS were found in 25.8%, 29.5%, and 44.8%, respectively. The mean time to cardiopulmonary resuscitation was 0.84 min. The initial rhythm was asystole in 47.6%, pulseless electrical activity in 38.2%, ventricular tachycardia/ventricular fibrillation in 5.4%, and unknown in 8.8%. Return of spontaneous circulation (ROSC) occurred in 29.2% of patients with the mean time to ROSC being 5.3 min. ROSC occurred in 17.3% of patients with asystole, 40.7% in pulseless electrical activity, 57.9% in ventricular tachycardia/ventricular fibrillation, and 25.8% in patients with an unknown rhythm. Of all patients, 16 (4.2%) were discharged alive. CONCLUSIONS: Nonshockable rhythms account for the majority of the cardiac arrests in hospitals in a lower middle income country and are associated with unfavorable outcomes. Future work should be directed to training health care personnel in recognizing early warning signs and implementing appropriate measures in a resource-scarce environment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".