Hypertensive Hypoalgesia in a Complex Chronic Disease Population
Bibliographic record
Abstract
Hypertension-related hypoalgesia, defined as lower pain sensitivity in individuals with high blood pressure, has yet to be examined in a large-scale study of complex care residents. Here, the Continuing Care Reporting System database, which contains health information on residents of Canadian complex chronic care facilities, was used for assessment. Hypertension was reported among 77,323 residents (55.5%, total N = 139,920). Propensity score matching, with a 1:1 ratio, was used to identify a control record without hypertension for each case. Multinomial logistic regression was used to quantify the effects of hypertension and sex on four-level ordinal pain variables, controlling for potential confounders. The matched dataset included n = 40,799 cases with hypertension and n = 40,799 without hypertension, with 57% female. Residents with hypertension had significantly lower odds of reporting pain (yes/no) (OR = 0.85, 95% CI 0.81–0.90, p < 0.001), including on measures of severe pain (OR = 0.69, 95% CI 0.63–0.76, p < 0.001). A significant interaction between hypertension and sex (OR = 1.17, 95% CI 1.03–1.32, p = 0.014) indicated that a significantly greater proportion of females without hypertension reported severe pain (8.71%). The results confirm the relationship between hypertension and reduced pain sensitivity on a population level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".