Value of medical history in ophthalmology: A study of diagnostic accuracy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: This study aimed to demonstrate the value of the chief compliant and patient history to accurately diagnose patient pathology without requiring ocular examination or imaging in an outpatient neuro-ophthalmology clinic. METHODS: We prospectively evaluated 115 consecutive patients at our institution from January to April 2009. The attending neuro-ophthalmologist committed to a single most likely diagnosis while solely being exposed to patient demographic information (age, gender, race) and chief complaint, but was otherwise blinded to ocular examination or imaging. The validity of the initial diagnosis was assessed by further acquiring subjective and objective findings and the percentage of correct diagnoses was determined. RESULTS: Patient cases were categorized based on the neuro-ophthalmologic localization of the final diagnoses: afferent nervous system, central nervous system (CNS), efferent nervous system, orbital system, and pupillary system. Correct diagnoses by chief complaint and patient history were 84%, 100%, 86%, 80%, 50% and 100% for afferent, central, efferent, orbit, pupil, and other neuro-ophthalmic diseases, respectively. Over half the cases were correctly diagnosed by chief complaint alone, which improved to 88% when combined with the patient history. CONCLUSIONS: A simple combination of patient history and chief complaint predicts an overall diagnostic accuracy in approximately 90% of cases. Our study demonstrates the remarkable diagnostic value of patient history in neuro-ophthalmologic clinic practice.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it