Bibliographic record
Abstract
Background: Dog ownership has been associated with decreased cardiovascular risk. Recent reports have suggested an association of dog companionship with lower blood pressure levels, improved lipid profile, and diminished sympathetic responses to stress. However, it is unclear if dog ownership is associated with improved survival as previous studies have yielded inconsistent results. Thus, we performed a systematic review and meta-analysis to evaluate the association of dog ownership with all-cause mortality, with and without prior cardiovascular disease, and cardiovascular mortality. Methods and Results: Studies published between 1950 and May 24, 2019 were identified by searching Embase and PubMed. Observational studies that evaluated baseline dog ownership and subsequent all-cause mortality or cardiovascular mortality. Two independent reviewers extracted the data. We assessed pooled data using random-effects model. A possible limitation was that the analyses were not adjusted for confounders. Ten studies were included yielding data from 3 837 005 participants (530 515 events; mean follow-up 10.1 years). Dog ownership was associated with a 24% risk reduction for all-cause mortality as compared to nonownership (relative risk, 0.76; 95% CI, 0.67–0.86) with 6 studies demonstrating significant reduction in the risk of death. Notably, in individuals with prior coronary events, living in a home with a dog was associated with an even more pronounced risk reduction for all-cause mortality (relative risk, 0.35; 95% CI, 0.17–0.69; I 2 , 0%). Moreover, when we restricted the analyses to studies evaluating cardiovascular mortality, dog ownership conferred a 31% risk reduction for cardiovascular death (relative risk, 0.69; 95% CI, 0.67–0.71; I 2 , 5.1%). Conclusions: Dog ownership is associated with lower risk of death over the long term, which is possibly driven by a reduction in cardiovascular mortality. Systematic Review Registration URL: http://www.crd.york.ac.uk/prospero/ . Unique identifier: CRD42018111048.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".