ReviewThe journals of gerontology. Series A, Biological sciences and medical sciences2007
Methodology, design, and analytic techniques to address measurement of comorbid disease.
Review in The journals of gerontology. Series A, Biological sciences and medical sciences, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
56 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Endophenotype-based in silico network medicine discovery combined with insurance record data mining identifies sildenafil as a candidate drug for Alzheimer's disease.Nature aging · 2021Trial
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- Article
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- Impact of observability period on the classification of COPD diagnosis timing among Medicare beneficiaries with lung cancer.PLOS digital health · 2024Article
- Predicting Multimorbidity Using Saudi Health Indicators (Sharik) Nationwide Data: Statistical and Machine Learning Approach.Healthcare (Basel, Switzerland) · 2023Article
- The Ability of Comorbidity Indices to Predict Mortality After Heart Transplantation: A Validation of the Danish Comorbidity Index for Acute Myocardial Infarction, Charlson Comorbidity Index, and Elixhauser Comorbidity Index.Transplantation direct · 2023Article
- Improving multimorbidity measurement using individualized disease-specific quality of life impact assessments: predictive validity of a new comorbidity index.Health and quality of life outcomes · 2022Article
- Measuring Multimorbidity: Selecting the Right Instrument for the Purpose and the Data Source.Medical care · 2021Article
- Association between Time to First Cigarette and Health-Related Quality of Life of Middle-Aged Male Current Smokers: A Nationwide Representative Study in Korea.Korean journal of family medicine · 2021Article
- Sex Differences in Time-Series Changes in Pseudo-Journal of personalized medicine · 2020Article
- Individual and joint effects of metformin and statins on mortality among patients with high-risk prostate cancer.Cancer medicine · 2020Article
- A Novel Approach to Developing a Discordance Index for Older Adults With Chronic Kidney Disease.The journals of gerontology. Series A, Biological sciences and medical sciences · 2020Article
- The DANish Comorbidity Index for Acute Myocardial Infarction (DANCAMI): Development, Validation and Comparison with Existing Comorbidity Indices.Clinical epidemiology · 2020Article
- Different Correlates of COVID-19-Related Adherent and Dysfunctional Safety Behavior.Frontiers in public health · 2020Article
- Validation and Comparison of a Modified Elixhauser Index for Predicting In-Hospital Mortality in Italian Internal Medicine Wards.Risk management and healthcare policy · 2020Article
- Comparing comorbidity measures and fatigue post myocardial infarction.Applied nursing research : ANR · 2019Article
- Time to First Cigarette and Self-Reported Health Among US Adult Smokers.Tobacco use insights · 2019Article
- Assessing and Measuring Chronic Multimorbidity in the Older Population: A Proposal for Its Operationalization.The journals of gerontology. Series A, Biological sciences and medical sciences · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundMeasurement of comorbidity affects all variable axes that are considered in health care research: confounding, modifying, independent, and dependent variable. Comorbidity measurement particularly affects research involving older adults because they bear the disproportionate share of the comorbidity burden.
methodsWe examine how well researchers can expect to segregate study participants into those who are healthier and those who are less healthy, given the variable axis for which they are measuring comorbidity, the comorbidity measure they select, and the analytic method they choose. We also examine the impact of poor measurement of comorbidity.
resultsAvailable comorbidity measures make use of medical records, self-report, physician assessments, and administrative databases. Analyses using these scales introduce uncertainties that can be framed as measurement error or misclassification problems, and can be addressed by extant analytic methods. Newer analytic methods make efficient use of multiple sources of comorbidity information.
conclusionsConsideration of the comorbidity measure, its role in the analysis, and analogous measurement error problems will yield an analytic solution and an appreciation for the likely direction and magnitude of the biases introduced.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.