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Record W3100729665 · doi:10.2147/jpr.s269648

<p>Association Between Multimorbid Disease Patterns and Pain Outcomes Among a Complex Chronic Care Population in Canada</p>

2020· article· en· W3100729665 on OpenAlexafffundabout
Meaghan Ferguson, Anton Svendrovski, Joel Katz

Bibliographic record

VenueJournal of Pain Research · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsYork University
FundersCanadian Institutes of Health ResearchYork University
KeywordsMedicineComorbidityPopulationDiseaseChronic painLogistic regressionHealth careMedical Expenditure Panel SurveyPhysical therapyInternal medicineEnvironmental healthHealth insurance

Abstract

fetched live from OpenAlex

Purpose: Disease multimorbidity and pain is a complex, yet common, problem for the aging population, and a significant burden on the health-care systems around the world. Despite this, disease comorbidity and the association with pain in a complex chronic care population is not well understood. This study examined the most prevalent disease combinations and their association with pain. Patients and Methods: The study initially included 139,920 residents, aged 18– 101 years, admitted to publicly funded hospital facilities for complex chronic care in Canada between the years 2006 and 2016. Data were acquired through the Canadian Institute for Health Information (CIHI) Facility-Based Continuing Care Reporting System (CCRS). Descriptive and chi-square statistics were used to summarize and compare the sample characteristics. Binary logistic regression analyses were used to examine the association between multimorbid disease categories and pain outcomes. Results: The sample consisted of 139,573 residents (57% female), mostly older (mean age = 77.32 years), married (40%), or widowed (36%). Residents took an average of 11.9 medications and 77% were using analgesic medications. On average, residents had diagnoses from 3.06 disease categories (SD = 1.43). Heart/circulation diseases were the most prevalent among the sample (73%), with neurological second (46%) and musculoskeletal third (44%). Overall, 73% of residents reported pain, with 43% reporting moderate pain severity. Residents with multiple disease categories were more likely to report the presence of pain (OR = 1.08, 95% CI: 1.07– 1.08, p < 0.001), with each additional disease category associated with an 8% increase in the odds of reporting pain. Conclusion: The findings from this study help identify common comorbid disease patterns related to pain in an institutionalized, complex chronic care population. This information contributes to both the pain and multimorbidity literature, and is invaluable for creating care plans to meet the demands of a challenging population. Keywords: complex chronic disease, comorbidity, disease categories, health, health psychology

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.091
GPT teacher head0.374
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2020
Admission routes3
Has abstractyes

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