Protocolized Laboratory Screening for the Medical Clearance of Psychiatric Patients in the Emergency Department: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Emergency department (ED) patients with psychiatric chief complaints undergo medical screening to rule out underlying or comorbid medical illnesses prior to transfer to a psychiatric facility. This systematic review attempts to determine the clinical utility of protocolized laboratory screening for the streamlined medical clearance of ED psychiatric patients by determining the clinical significance of individual laboratory results. METHODS: We searched PubMed, Embase, and Scopus using the search terms "emergency department, psychiatry, diagnostic tests, laboratories, studies, testing, screening, and clearance" up to June 2017 for studies on adult psychiatric patients. This systematic review follows the recommendations of Meta-analysis of Observational Studies in Epidemiology (MOOSE) statement. The quality of each study was rated according to the Newcastle-Ottawa quality assessment scale. RESULTS: Four independent reviewers identified 2,847 publications. We extracted data from three studies (n = 629 patients). Included studies defined an abnormal test result as any laboratory result that falls out of the normal range. A laboratory test result was deemed as "clinically significant" only when patient disposition or treatment plan was changed because of that test result. Across the three studies the prevalence of clinically significant results were low (0.0%-0.4%). CONCLUSIONS: The prevalence of clinically significant laboratory test results were low, suggesting that according to the available literature, routine laboratory testing does not significantly change patient disposition. Due to the paucity of available research on this subject, we could not determine the clinical utility of protocolized laboratory screening tests for medical clearance of psychiatric patients in the ED. Future research on the utility of routine laboratory testing is important in a move toward shared decision making and patient-centered health care.
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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 | 0.031 | 0.126 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".