Causes of death among people who used illicit opioids in England, 2001–18: a matched cohort study
Bibliographic record
Abstract
BACKGROUND: In many countries, the average age of people who use illicit opioids, such as heroin, is increasing. This has been suggested to be a reason for increasing numbers of opioid-related deaths seen in surveillance data. We aimed to describe causes of death among people who use illicit opioids in England, how causes of death have changed over time, and how they change with age. METHODS: In this matched cohort study, we studied patients in the Clinical Practice Research Datalink with recorded illicit opioid use (defined as aged 18-64 years, with prescriptions or clinical observations that indicate use of illicit opioids) in England between Jan 1, 2001, and Oct 30, 2018. We also included a comparison group, matched (1:3) for age, sex, and general practice with no records of illicit opioid use before cohort entry. Dates and causes of death were obtained from the UK Office for National Statistics. The cohort exit date was the earliest of date of death or Oct 30, 2018. We described rates of death and calculated cause-specific standardised mortality ratios. We used Poisson regression to estimate associations between age, calendar year, and cause-specific death. FINDINGS: We collected data for 106 789 participants with a history of illicit opioid use, with a median follow-up of 8·7 years (IQR 4·3-13·5), and 320 367 matched controls with a median follow-up of 9·5 years (5·0-14·4). 13 209 (12·4%) of 106 789 participants in the exposed cohort had died, with a standardised mortality ratio of 7·72 (95% CI 7·47-7·97). The most common causes of death were drug poisoning (4375 [33·1%] of 13 209), liver disease (1272 [9·6%]), chronic obstructive pulmonary disease (COPD; 681 [5·2%]), and suicide (645 [4·9%]). Participants with a history of illicit opioid use had higher mortality rates than the comparison group for all causes of death analysed, with highest standardised mortality ratios being seen for viral hepatitis (103·5 [95% CI 61·7-242·6]), HIV (16·7 [9·5-34·9]), and COPD (14·8 [12·6-17·6]). In the exposed cohort, at age 20 years, the rate of fatal drug poisonings was 271 (95% CI 230-313) per 100 000 person-years, accounting for 59·9% of deaths at this age, whereas the mortality rate due to non-communicable diseases was 31 (16-45) per 100 000 person-years, accounting for 6·8% of deaths at this age. Deaths due to non-communicable diseases increased more rapidly with age (1155 [95% CI 880-1431] deaths per 100 000 person-years at age 50 years; accounting for 52·0% of deaths at this age) than did deaths due to drug poisoning (507 (95% CI 452-562) per 100 000 person-years at age 50 years; accounting for 22·8% of deaths at this age). Mirroring national surveillance data, the rate of fatal drug poisonings in the exposed cohort increased from 345 (95% CI 299-391) deaths per 100 000 person-years in 2010-12 to 534 (468-600) per 100 000 person-years in 2016-18; an increase of 55%, a trend that was not explained by ageing of participants. INTERPRETATION: People who use illicit opioids have excess risk of death across all major causes of death we analysed. Our findings suggest that population ageing is unlikely to explain the increasing number of fatal drug poisonings seen in surveillance data, but is associated with many more deaths due to non-communicable diseases. FUNDING: National Institute for Health Research.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".