Anorexia due to Depression in the Elderly From the Viewpoint of Primary Care
Bibliographic record
Abstract
Japan is currently an aging society with a huge proportion of elderly citizens. Consequently, the incidence and severity of anorexia and depression are predicted to increase in the future. In fact, at present, anorexia is common in the elderly. Anorexia is one of the major symptoms of depression in the elderly. More than 90% of patients with depression are thought to visit primary care physicians and the departments such as general medicine first instead of psychiatrists. Therefore, primary care physicians need to be vigilant for signs of depressive disorder to prevent suicide. Elderly patients have few negative emotions, such as feeling depressed, sad, or any other subjective drops in mood; this implies that elderly individuals might find it difficult to explain their symptoms to others and that the people around them might hardly notice any symptoms of depression. An 84-year-old woman started to gradually lose appetite. She has undergone various examinations, but an obvious physical organic abnormality was not found. Upon admission to our hospital, her weight was 38 kg and body mass index was 16.9 kg/m 2 . Based on diagnostic criteria and further evaluation, we diagnosed her as anorexia due to depression. After biopsychosocial approach including appropriate social support, as well as medical and mental therapies, her appetite improved gradually and she was able to regain her weight eventually. Elderly individuals have a tendency to get depression due to biologic and psychosocial causes. Many patients with depression are thought to visit primary care physicians and the departments such as general medicine first instead of psychiatrists. Therefore, the efficiency of primary care is underscored and primary care physicians need to be vigilant in detecting depression and preventing suicide. We think that general medicine will have a more important part in medical practice in the future in Japan. J Med Cases. 2017;8(4):119-123 doi: https://doi.org/10.14740/jmc2794w
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".