Evidence map›Paper›PMID 36618107›Full record

ArticleJournal of multimorbidity and comorbidity

Convergence of four measures of multi-morbidity.

Brandon R Grossardt, Alanna M Chamberlain, Cynthia M Boyd, William V Bobo, Jennifer L St Sauver, Walter A Rocca

Abstract read
In one paragraph

Article in Journal of multimorbidity and comorbidity. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Brandon R GrossardtDivision of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Alanna M ChamberlainDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.ORCID https://orcid.org/0000-0003-1888-9584
Cynthia M BoydDivision of Geriatric Medicine and Gerontology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.
William V BoboDepartment of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL, USA.ORCID https://orcid.org/0000-0002-5674-3079
Jennifer L St SauverDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.ORCID https://orcid.org/0000-0002-9789-8544
Walter A RoccaDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.ORCID https://orcid.org/0000-0002-1832-7664

Funding

Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology ProjectR33AG058738 · NIA · MAYO CLINIC ROCHESTER · PI LEBRASSEUR, NATHAN K, OLSON, JANET E · 2020 to 2022
$2.4M
NIA NIH HHS R33 AG058738
6 · The paper itself

Abstract

Objectives: To compare the agreement between percentile ranks from 4 multi-morbidity scores. Design: Population-based descriptive study. Setting: Olmsted County, Minnesota (USA). Participants: We used the medical records-linkage system of the Rochester Epidemiology Project (REP; http://www.rochesterproject.org) to identify all residents of Olmsted County, Minnesota who reached one or more birthdays between 1 January 2005 and 31 December 2014 (10 years). Methods: For each person, we calculated 4 multi-morbidity scores using readily available diagnostic code lists from the US Department of Health and Human Services, the Clinical Classifications Software, and the Elixhauser Comorbidity Index. We calculated scores using diagnostic codes received in the 5 years before the index birthday and fit quantile regression models across age and separately by sex to transform unweighted, simple counts of conditions into percentile ranks as compared to peers of same age and of same sex. We compared the percentile ranks of the 4 multi-morbidity scores using intra-class correlation coefficients (ICCs). Results: We assessed agreement in 181,553 persons who reached a total of 1,075,433 birthdays at ages 18 years through 85 years during the study period. In general, the percentile ranks of the 4 multi-morbidity scores exhibited high levels of agreement in 6 score-to-score pairwise comparisons. The agreement increased with older age for all pairwise comparisons, and ICCs were consistently greater than 0.65 at ages 50 years and older. Conclusions: The assignment of percentile ranks may be a simple and intuitive way to assess the underlying trait of multi-morbidity across studies that use different measures.

Indexed as

agingagreement analysesmeasurement scoresMulti-morbiditypercentiles

Identifiers

PMID36618107
PMCPMC9813979

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Registered trials

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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.