The performance of HEAR score for identification of low-risk chest pain: a systematic review and meta-analysis
Bibliographic record
Abstract
Chest pain is one of the most common presentations to the emergency department (ED) and HEART score (history, ECG, age, risk factors, and cardiac troponin) is recommended for risk stratification. It has been proposed that the sum of four items with no troponin (HEAR score) below 2 can be used safely to lower testing and reduce length of stay. To assess the performance of the HEAR score in hospital and prehospital settings, we performed a systematic review and meta-analysis. English studies on the performance of the HEAR score in patients with acute chest pain were included. They were excluded if data are inaccessible. MEDLINE, Embase, Evidence-Based Medicine Reviews, Scopus, and web of science were searched from 1946 to July 2021. The quality of studies was assessed using Quality Assessment of Diagnostic Accuracy Studies version 2. Acute coronary syndrome or major adverse cardiac events prediction were outcomes of interest. The performance indices with 95% confidence intervals (CIs) were extracted. Inverse variance and the random-effects model were used to report the results. Of the 692 articles on the HEAR score, 10 studies were included in the analysis with 33 843 patients. Studies were at low to moderate risk of bias. Three studies were in prehospital and three were retrospective. The pooling of data on the HEAR score showed that the sensitivity at the HEAR<2, <3, and <4 cutoffs in the ED were 99.03% (95% CI, 98.29-99.77), 97.54% (95% CI, 94.50-100), and 91.80% (95% CI, 84.62-98.98), respectively. The negative predictive values (NPVs) for the above cutoffs were 99.84% (95% CI, 99.72-99.95), 99.75% (95% CI, 99.65-99.85), and 99.57% (95% CI, 99.11-100), respectively. Of note, for the HEAR<2, negative likelihood ratio was 0.07 (95% CI, 0.02-0.12). In the prehospital, at the HEAR<4 cutoff, the pooled sensitivity and NPV were 85.01% (95% CI, 80.56-89.47) and 91.48% (95% CI, 87.10-95.87), respectively. This study showed that in the ED, the HEAR score<2 can be used for an early discharge strategy. Currently, this score cannot be recommended in prehospital setting. Prospero (CRD42021273710).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.034 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".