Screening highly prevalent disorders among the elderly
Bibliographic record
Abstract
Eekhof and colleagues1 recently reported the results of screening highly prevalent disorders among the elderly in general practice. We fully agree with one of their concluding statements, “preventive care … should be started before the age of 75 years …”; however, their statement that a screening programme is not recommended does not seem a logical conclusion from their results. The primary outcome of the study was to demonstrate differences in disorder prevalence of the diseases/conditions in the intervention and control groups. Yet, all four conditions studied are chronic and cannot be eradicated in this population. These conditions can be controlled or managed to improve the health (by decreasing morbidity or mortality) or quality of life of patients. Perhaps the authors intended to look at the prevalence of ‘controlled’ or ‘managed’ conditions; however, this was not clear from the article. For example, in patients with urinary incontinence it may have been more applicable to evaluate the number of incontinence episodes/day or the number of absorbable undergarment products used, rather than prevalence. Patient refusal of intervention should not be interpreted as programme failure. Often patients can adapt to chronic diseases. Until their lifestyle is significantly disrupted, they may prefer to avoid intervention. For example, patients with urinary incontinence may have started using absorbable undergarments and did not feel that any other intervention was necessary. Regarding the refusal of interventions, it would have been beneficial to know which patients were diagnosed with depression, as this may have caused them to be more apathetic or not respond as well to the prescribed interventions. Previous studies have shown that urinary incontinence2,3 or other chronic diseases4 have been associated with depression or depressive symptomatology. The authors appropriately noted that “depression … is part of the daily reality of the elderly …”, yet it may have been helpful to reflect this diagnosis in their analyses. An important contribution of the screening programmes seems to be that this information was new to the physicians in 25–50% of patients, depending upon the condition. While patients may not want direct intervention to improve the conditions that were screened, knowledge of these conditions may impact care in other ways. For example, visual disorders may lead to decreased ability to manage medications, and additional, unreported interventions may have resulted that improved the patient's ability to manage their medications. One other point is that when the information was not new to physicians, it is not clear what happened. Were discussions carried out with patients regarding the condition and/or its management? We strongly support the efforts of GPs to screen elderly patients for chronic conditions such as hearing disorders, visual disorders, urinary incontinence and mobility disorders. Based upon this evaluation, concluding that such screening is not recommended for other general practice physicians is too strong, given the outcomes selected for evaluation.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.023 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".