Diagnostic Delays in Sepsis: Lessons Learned From a Retrospective Study of Canadian Medico-Legal Claims
Why this work is in the frame
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Bibliographic record
Abstract
Although rapid treatment improves outcomes for patients presenting with sepsis, early detection can be difficult, especially in otherwise healthy adults. OBJECTIVES: Using medico-legal data, we aimed to identify areas of focus to assist with early recognition of sepsis. DESIGN SETTING AND PARTICIPANTS: Retrospective descriptive design. We analyzed closed medico-legal cases involving physicians from a national database repository at the Canadian Medical Protective Association. The study included cases closed between 2011 and 2020 that had documented peer expert criticism of a diagnostic issue related to sepsis or relevant infections. MAIN OUTCOMES AND MEASURES: We used univariate statistics to describe patients and physicians and applied published frameworks to classify contributing factors (provider, team, system) and diagnostic pitfalls based on peer expert criticisms. RESULTS: Of 162 involved patients, the median age was 53 years (interquartile range [IQR], 34-66 yr) and mortality was 49%. Of 218 implicated physicians, 169 (78%) were from family medicine, emergency medicine, or surgical specialties. Eighty patients (49%) made multiple visits to outpatient care leading up to sepsis recognition/hospitalization (median = two visits; IQR, 2-4). Almost 40% of patients were admitted to the ICU. Deficient assessments, such as failing to consider sepsis or not reassessing the patient prior to discharge, contributed to the majority of cases (81%). CONCLUSIONS AND RELEVANCE: Sepsis continues to be a challenging diagnosis for clinicians. Multiple visits to outpatient care may be an early warning sign requiring vigilance in the patient assessment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 it