Mortality among the Canadian population with multimorbidity: a retrospective cohort study
Bibliographic record
Abstract
The association between multimorbidity and mortality was well established based on the previous studies. However, there is limited evidence of excess mortality in people with multimorbidity among the Canadian population, and a study with a larger sample size is recommended. Furthermore, it has been recommended to examine multimorbidity mortality among individuals under the age of 65, as some research demonstrated that it has become a serious issue for the middle-aged population as well. Therefore, this thesis examined the association between multi-morbidity and mortality based on the linked database of CCHS (Canadian Community Health Survey)-CVSD (Canadian Vital Statistics Death Database) which included a study sample representative of the general population of Canada. The results of the study suggest that people with multimorbidity had a significant lower cumulative survival probability in comparison to those without multimorbidity during the 14-year follow up period, after adjusting for all confounding effects. The effects of multimorbidity on mortality increased from the oldest (65 years old and above) to the youngest age group (35 to 49 years old). Additionally, when the interactions between different chronic diseases were considered, it was found that subjects with COPD and without diabetes had a significantly higher risk of death in comparison to those without COPD and diabetes. This risk was further increased in subjects with both COPD and diabetes. In summary, our study results contributed to the body of knowledge showing multimorbidity was associated with excess mortality and it also provided evidence describing the joint effects of comorbidity on mortality in the middle-aged and senior Canadian population. Further studies focusing on investigating multimorbidity and mortality in the middle-aged Canadian population, as well as exploring other potential comorbidities associated with excess mortality, are necessary to the management of multimorbidity. More public health programs should be initiated to prevent chronic diseases and multimorbidity, which in turn, would save lives, improve quality of life, and save healthcare dollars.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".