Diagnostic Accuracy of Posterior Circulation Stroke by Paramedics: A Systematic Review
Bibliographic record
Abstract
Objective This systematic review aims to identify the diagnostic accuracy of posterior circulation stroke (PCS) by paramedics and the causes and duration of delay in its recognition.Methods A systematic search using CINAHL Plus, MEDLINE, Scopus, and PubMed was performed. All databases were searched up to May 25, 2022. Studies were included where patients were adults, assessed by paramedics, and PCS was the primary diagnosis. Bias was assessed using the Newcastle-Ottawa Scale and the Effective Practice and Organization of Care tool. Results have been described by proportions, and both sensitivity calculations and subgroup analysis were performed utilizing MedCalc.Results A total of 797 titles/abstracts and a subsequent 87 full texts were screened, of which 15 were included. There were 5395 patients who were assessed by paramedics and had a confirmed diagnosis of PCS. Among five studies containing both true positive and false negative data, there were 98 (45.8%) true positives. PCS patients lost an average of 27 min (p < 0.001) compared to anterior stroke patients in the prehospital setting. One study revealed that educational intervention, including implementing the finger-to-nose test, increased the sensitivity for diagnosis from 45.8 to 74.1% (p = 0.039) and decreased the time from door to computed tomography from 62 to 41 min (p = 0.037).Conclusion There is a substantial lack of evidence regarding the diagnosis of PCS by paramedics. Despite the low quality of evidence available, overall, the sensitivity for paramedic PCS diagnosis appears to be poor. Further investigation is required into paramedics’ diagnosis of PCS and the use of educational interventions.Prospective Register of Systematic Reviews Registration Number: CRD42022324675.
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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 | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".