Diagnostic Accuracy of the HINTS Exam in an Emergency Department: A Retrospective Chart Review
Bibliographic record
Abstract
INTRODUCTION: The HINTS exam is a series of bedside ocular motor tests designed to distinguish between central and peripheral causes of dizziness in patients with continuous dizziness, nystagmus, and gait unsteadiness. Previous studies, where the HINTS exam was performed by trained specialists, have shown excellent diagnostic accuracy. Our objective was to assess the diagnostic accuracy of the HINTS exam as performed by emergency physicians on patients presenting to the emergency department (ED) with a primary complaint of vertigo or dizziness. METHODS: A retrospective cohort study was performed using data from patients who presented to a tertiary care ED between September 2014 and March 2018 with a primary complaint of vertigo or dizziness. Patient characteristics of those who received the HINTS exam were assessed along with sensitivity and specificity of the test to rule out a central cause of stroke. RESULTS: A total of 2,309 patients met criteria for inclusion in the study. Physician uptake of the HINTS exam was high, with 450 (19.5%) dizzy patients receiving all or part of the HINTS. A large majority of patients (96.9%) did not meet criteria for receiving the test as described in validation studies; most often this was because patients lacked documentation of nystagmus or described their symptoms as intermittent. In addition, many patients received both HINTS and Dix-Hallpike exams, which are intended for use in mutually exclusive patient populations. In no case was dizziness due to a central cause identified using the HINTS exam. CONCLUSIONS: Our results suggest that despite widespread use of the HINTS exam in our ED, its diagnostic value in that setting was limited. The test was frequently used in patients who did not meet criteria to receive the HINTS exam (i.e., continuous vertigo, nystagmus, and unsteady gait). Additional training of emergency physicians may be required to improve test sensitivity and specificity.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".