Multimorbidity and quality of life in primary care: a systematic review
Bibliographic record
Abstract
BACKGROUND: Many patients with several concurrent medical conditions (multimorbidity) are seen in the primary care setting. A thorough understanding of outcomes associated with multimorbidity would benefit primary care workers of all disciplines. The purpose of this systematic review was to clarify the relationship between the presence of multimorbidity and the quality of life (QOL) or health-related quality of life (HRQOL) of patients seen, or likely to be seen, in the primary care setting. METHODS: Medline and Embase electronic databases were screened using the following search terms for the reference period 1990 to 2003: multimorbidity, comorbidity, chronic disease, and their spelling variations, along with quality of life and health-related quality of life. Only descriptive studies relevant to primary care were selected. RESULTS: Of 753 articles screened, 108 were critically assessed for compliance with study inclusion and exclusion criteria. Thirty of these studies were ultimately selected for this review, including 7 in which the relationship between multimorbidity or comorbidity and QOL or HRQOL was the main outcome measure. Major limitations of these studies include the lack of a uniform definition for multimorbidity or comorbidity and the absence of assessment of disease severity. The use of self-reported diagnoses may also be a weakness. The frequent exclusion of psychiatric diagnoses and presence of potential confounding variables are other limitations. Nonetheless, we did find an inverse relationship between the number of medical conditions and QOL related to physical domains. For social and psychological dimensions of QOL, some studies reveal a similar inverse relationship in patients with 4 or more diagnoses. CONCLUSIONS: Our findings confirm the existence of an inverse relationship between multimorbidity or comorbidy and QOL. However, additional studies are needed to clarify this relationship, including the various dimensions of QOL affected. Those studies must employ a clear definition of multimorbidity or comorbidity and valid ways to measure these concepts in a primary care setting. Pursuit of this research will help to better understand the impact of chronic diseases on patients.
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".