Physical and Mental Health Problems Associated with the Use of Alcohol and Drugs
Bibliographic record
Abstract
The nature and extent of treated health problems in patients with problems related to the use of alcohol and drugs (including both licit and illicit drugs) were compared with the morbidity levels of all patients treated for all conditions in Canada. The morbidity experience of all patients with alcohol or drug (A/D) diagnoses treated as inpatients (n = 52,200 cases) in all Ontario hospitals in 1985-1986 (based on Hospital Medical Records Institute [HMRI] data) was compared with that of the total population of all inpatients treated in all Canadian hospitals using age-sex standardized morbidity ratios (SMR) and adjusting for multiple diagnoses. Of A/D cases, 32% were admitted with a primary A/D diagnosis and 68% with a secondary A/D diagnosis; 17% of A/D cases had multiple A/D diagnosis. On average, cases with a primary A/D diagnosis had 29% more diagnoses per case than all cases treated in Ontario. SMRs were highest for cases with diagnoses relating to the use or misuse of licit drugs (SMR = 13.32 and 3.51 for those with primary and secondary drug diagnoses, respectively), intermediate for illicit drug cases (SMR = 8.87 vs. 4.74 for primary and secondary diagnoses, respectively), and lowest for patients with alcohol diagnoses (SMR = 6.68 and 4.12 for primary and secondary diagnoses, respectively). Excess morbidity for alcohol cases affected more diagnostic categories and body systems, being at a higher level than for drug cases. Alcohol or drug cases had particularly high SMRs for mental disorders, infectious and parasitic conditions, and injury and poisoning diagnoses. Alcohol or drug cases had reduced reproductive morbidity: for complications of pregnancy, childbirth, and the puerperium, SMR = 0.04 to 0.24 for cases with primary A/D diagnoses and SMR = 0.12 to 0.89 for those with secondary A/D diagnoses. Cases with drug diagnoses had a considerable reduction in SMR for certain conditions originating in the perinatal period: SMR = 0.0 for cases with primary drug diagnoses and SMR = 0.0 for secondary illicit drug diagnoses cases and SMR = 0.18 for secondary licit drug diagnoses cases.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".