The Revised-Panic Screening Score for emergency department patients with noncardiac chest pain.
Bibliographic record
Abstract
OBJECTIVES: We sought to reduce the 90% rate of missed diagnoses of panic-like anxiety (panic attacks with or without panic disorder) among emergency department patients with low risk noncardiac chest pain by validating and improving the Panic Screening Score (PSS). METHOD: A total of 1,102 patients with low risk noncardiac chest pain were prospectively and consecutively recruited in two emergency departments. Each patient completed a telephone interview that included the PSS, a brief 4-item screening instrument, new candidate predictors of panic-like anxiety, and the Anxiety Disorder Interview for the Diagnostic and Statistical Manual of Mental Disorders. Fourth Edition to identify panic-like anxiety. RESULTS: The original 4-item PSS demonstrated a sensitivity of 51.8% (95% CI [48.4, 57.0]) and a specificity of 74.8% (95% CI [71.3, 78.1]) for panic-like anxiety. Analyses prompted the development of the Revised-PSS; this 6-item instrument was 19.1% (95% CI [12.7, 25.5]) more sensitive than the original PSS in identifying panic-like anxiety in this sample (χ2(1, N = 351) = 23.89 p < .001) while maintaining a similar specificity (χ2(1, N = 659) = 0.754, p = .385; 0.4%, 95% CI [-3.6, 4.5]). The discriminant validity of the Revised-PSS proved stable over the course of a 10-fold cross-validation. CONCLUSIONS: The Revised-PSS has significant potential for improving identification of panic-like anxiety in emergency department patients with low risk noncardiac chest pain and promoting early access to treatment. External validation and impact analysis of the Revised-PSS are warranted prior to clinical implementation. (PsycINFO Database Record
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".