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Record W2137169112 · doi:10.1186/1477-7525-5-52

Multimorbidity and quality of life: a closer look

2007· article· en· W2137169112 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHealth and Quality of Life Outcomes · 2007
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsCentre de Santé et de Services Sociaux de ChicoutimiHealth and Social Services Centre University Institute of Geriatrics of SherbrookeUniversité de Sherbrooke
FundersPfizer CanadaPfizer
KeywordsQuality of life (healthcare)Bivariate analysisConfoundingMedicineMultivariate statisticsMultivariate analysisRating scaleAffect (linguistics)Explained variationDiseaseAnalysis of varianceInternal medicineClinical psychologyPsychologyStatisticsDevelopmental psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The presence of multiple chronic conditions is associated with lower health related quality of life (HRQOL). Disease severity also influences HRQOL. To analyse the effects of all possible combinations of single diseases along with their severity on HRQOL seems cumbersome. Grouping diseases and their severity in specific organ domains may facilitate the study of the complex relationship between multiple chronic conditions and HRQOL. The goal of this study was to analyse impaired organ domains that affect the most HRQOL of patients with multiple chronic conditions in primary care and their possible interactions. METHODS: We analysed data from 238 patients recruited from the clientele of 21 family physicians. We classified all chronic conditions along with the measure of their severity into the 14 organ domains of the Cumulative Illness Rating Scale (CIRS). Patients also completed the 36-item Medical Outcomes Study questionnaire (SF-36). One-way analyses of variance were performed to study the relationship between the severity score for each CIRS domain and both physical component summary (PCS) and mental component summary (MCS) of HRQOL. Two-way analyses of variance were conducted to investigate the significance of possible organ domains interactions. Variables involved in significant bivariate relationships or interactions were candidates for inclusion in a multivariate model. Five additional variables were included in the multivariate model because of their possible confounding effect: perceived social support, age, education, perceived economic status and residual CIRS. RESULTS: Significant differences in the PCS (p < 0.01) were found in 12 of the 14 CIRS organ domains. A significant difference in MCS was found only in the Psychiatric domain. In the multivariate analysis for the PCS, the CIRS domains Musculoskeletal, Neurological, and Psychiatric, had an independent direct impact on PCS while the Upper gastrointestinal, Vascular, Cardiac and Respiratory domains were involved in interactions. A multivariate model was not necessary for the mental component. CONCLUSION: Vascular, Upper gastrointestinal and Musculoskeletal systems have strong negative effects on HRQOL. Among combinations of systems, the respiratory and cardiac combination is of particular concern because of a synergistic negative effect. This study paves the way for a future study with a bigger sample that could yield a model of wider generalizability.

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.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.017
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.228
GPT teacher head0.471
Teacher spread0.244 · 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