Evidence map›Paper›PMID 32766818›Full record

ArticleFamily practice2021

Patterns of multimorbidity and pharmacotherapy: a total population cross-sectional study.

Tomas Forslund, Axel C Carlsson, Gunnar Ljunggren, Johan Ärnlöv, Caroline Wachtler

Open access · hybridAbstract read
In one paragraph

Article in Family practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 2 pooled it
3.8field-weighted citation impact, top 6% of its field
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

35 citing papers in PubMed, 2 syntheses or guidelines pooled it, 59 citations in OpenAlex.

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  14. Multimorbidity Management: A Scoping Review of Interventions and Health Outcomes.International journal of environmental research and public health · 2025
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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

5 authors at 2 institutions in 1 country.

Tomas ForslundDepartment of Healthcare Development, Stockholm Region, Public Healthcare Services Committee, Stockholm, Sweden.
Axel C CarlssonDepartment of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Huddinge, Sweden.
Gunnar LjunggrenDepartment of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Huddinge, Sweden.
Johan ÄrnlövDepartment of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Huddinge, Sweden.
Caroline WachtlerDepartment of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Huddinge, Sweden.
Karolinska Institutet · SEDalarna University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTreatment of multimorbid patients can be improved. Development of patient-centred care of high-quality requires context-bound understanding of the multimorbid population's patterns of demographics, co-morbidities and medication use.

objectiveThe aim of this study was to identify patterns of multimorbidity in the total population of Region Stockholm, Sweden, by exploring demographics, claimed prescription drugs, risk of mortality and non-random association of conditions.

methodsIn this cross-sectional descriptive population-based cohort study, we extracted data from the Swedish VAL database (N = 2 323 667) including all consultations in primary and specialized outpatient care, all inpatient care and all prescriptions claimed during 2017. We report number of chronic conditions and claimed prescription drugs, physical and mental co-morbidity, and 1-year mortality. We stratified the analyses by sex. We examined non-random associations between diseases using cluster analysis.

resultsIn total, 21.6% had multimorbidity (two or more chronic conditions) and 24.1% had polypharmacy (more than five claimed prescription drugs). Number of claimed drugs, co-occurrence of mental and physical conditions, and 1-year mortality increased as multimorbidity increased. We identified seven multimorbidity clusters with clinically distinct characteristics. The smallest cluster (7% of individuals) had prominent cardiovascular disease, the highest 1-year mortality rate, high levels of multimorbidity and polypharmacy, and was much older. The largest cluster (27% of individuals) was younger and heterogenous, with primarily mental health problems.

conclusionsIndividuals with chronic conditions often show clinical complexity with both concordant and discordant conditions and polypharmacy. This study indicates that clinical guidelines addressing clustering of conditions may be one strategy for managing complexity.

Indexed as

MultimorbidityPolypharmacyChronic DiseaseCohort StudiesCross-Sectional StudiesHumansChronic diseasefrailtymultimorbidityphamacology/drug reactionspopulation healthprimary health care

Identifiers

PMID32766818
PMCPMC8006765
OpenAlexW3047936160

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.