The value of clock drawing in identifying executive cognitive dysfunction in people with a normal Mini-Mental State Examination score.
Bibliographic record
Abstract
BACKGROUND: Executive cognitive dysfunction can precede the memory disturbances of dementia. People with executive cognitive dysfunction can have a normal Mini-Mental State Examination (MMSE) score but still have severe functional limitations. We evaluated the usefulness of clock drawing in identifying people with executive dysfunction who have a normal MMSE score. METHODS: We reviewed the charts of consecutive patients referred between July 1999 and June 2000 to a multidisciplinary geriatric assessment clinic because of concerns about functional inabilities. The patients had all undergone the Executive Interview for the diagnosis of executive cognitive dysfunction as well as an MMSE and clock-drawing test (scored by 2 methods: one described by Watson and colleagues [the Watson method] and one described by Sunderland and colleagues [the Sunderland method]). RESULTS: We reviewed the charts of 68 patients (40 women, 28 men); their mean age was 79 years (range 55-94). Thirty-six patients had an MMSE score of less than 24, and 32 had a "normal" MMSE score (24-30). Among those with a normal MMSE score, 22 had an abnormal Executive Interview score. Using the Executive Interview as the gold standard, the sensitivity and specificity of the Watson method of scoring clock drawings to predict an abnormal Executive Interview score were 59% and 70% respectively; the corresponding values were 18% and 100% for the Sunderland method. INTERPRETATION: The presence of an abnormal MMSE score alerts clinicians to the possibility of cognitive impairment. For patients referred for geriatric assessment who have a normal MMSE score, a clock-drawing test, scored by either the Watson or the Sunderland method, is a moderately sensitive and specific adjunct for detecting executive cognitive dysfunction.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".