Medical illness, medication use and suicide in seniors: a population-based case–control study
Bibliographic record
Abstract
BACKGROUND: Suicide among seniors is a significant health problem in north America, particularly for men in whom the rates rise steadily after 50 years of age. The goal of this study was to examine elder suicides identified from a large population-based database using case-control methods to determine disease and medication factors related to suicide. METHODS: A population-based 1 : 5 case-control study was conducted comparing seniors aged 66 years and older who had died by suicide with age and sex-matched controls. Case data were obtained through British Columbia (BC) Vital Statistics, whereas controls were randomly selected from the BC Health Insurance Registry. Cases and controls were linked to the provincial PharmaCare database to determine medication use and the provincial Physician Claims and Inpatient Hospitalization databases to determine co-morbidity. RESULTS: Between 1993 and 2002 a total of 602 seniors died by suicide in BC giving an annual rate of 13.2 per 100,000. Firearms were the most common mechanism (28%), followed by hanging/suffocation (25%), self-poisoning (21%), and jumping from height (7%). In the adjusted logistic model, variables related to suicide included: lower socioeconomic status, depression/psychosis, neurosis, stroke, cancer, liver disease, parasuicide, benzodiazepine use, narcotic pain killer use and diuretic use. There was an elevated risk for those prescribed inappropriate benzodiazepines and for those using strong narcotic pain killers. CONCLUSION: This study is consistent with previous studies that have identified a relationship between medical or psychiatric co-morbidity and suicide in seniors. In addition, new and potentially useful information confirms that certain types and dosages of benzodiazepines are harmful to seniors and their use should be avoided.
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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 | 0.022 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".