Evidence map›Paper›PMID 32005102›Full record

ArticleThe journal of headache and pain2020

Burden of migraine in Finland: multimorbidity and phenotypic disease networks in occupational healthcare.

Minna A Korolainen, Samuli Tuominen, Samu Kurki, Mariann I Lassenius, Iiro Toppila, Timo Purmonen, Jaana Santaholma, Markku Nissilä

Open access · goldAbstract read
In one paragraph

Article in The journal of headache and pain, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

13 citing papers in PubMed, 29 citations in OpenAlex.

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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

8 authors at 2 institutions in 2 countries.

Minna A KorolainenNovartis Finland Oy, Espoo, Finland. Minna.Korolainen@novartis.com.ORCID http://orcid.org/0000-0002-8593-5918
Samuli TuominenMedaffcon Oy, Espoo, Finland.
Samu KurkiTerveystalo Biobank Finland, Turku, Finland.
Mariann I LasseniusMedaffcon Oy, Espoo, Finland.
Iiro ToppilaMedaffcon Oy, Espoo, Finland.
Timo PurmonenNovartis Finland Oy, Espoo, Finland.
Jaana SantaholmaNovartis Finland Oy, Espoo, Finland.
Markku NissiläTerveystalo Biobank Finland, Turku, Finland.
Turku Centre for Biotechnology · FINovartis (China) · CN

Funding

Novartis Finland NA
6 · The paper itself

Abstract

backgroundMigraine is a complex neurological disorder with high co-existing morbidity burden. The aim of our study was to examine the overall morbidity and phenotypic diseasome for migraine among people of working age using real world data collected as a part of routine clinical practice.

methodsElectronic medical records (EMR) of patients with migraine (n = 17,623) and age- and gender matched controls (n = 17,623) were included in this retrospective analysis. EMRs were assessed for the prevalence of ICD-10 codes, those with at least two significant phi correlations, and a prevalence >2.5% in migraine patients were included to phenotypic disease networks (PDN) for further analysis. An automatic subnetwork detection algorithm was applied in order to cluster the diagnoses within the PDNs. The diagnosis-wise connectivity based on the PDNs was compared between migraine patients and controls to assess differences in morbidity patterns.

resultsThe mean number of diagnoses per patient was increased 1.7-fold in migraine compared to controls. Altogether 1337 different ICD-10 codes were detected in EMRs of migraine patients. Monodiagnosis was present in 1% and 13%, and the median number of diagnoses was 12 and 6 in migraine patients and controls. The number of significant phi-correlations was 2.3-fold increased, and cluster analysis showed more clusters in those with migraine vs. controls (9 vs. 6). For migraine, the PDN was larger and denser and exhibited one large cluster containing fatigue, respiratory, sympathetic nervous system, gastrointestinal, infection, mental and mood disorder diagnoses. Migraine patients were more likely affected by multiple conditions compared to controls, even if no notable differences in morbidity patterns were identified through connectivity measures. Frequencies of ICD-10 codes on a three character and block level were increased across the whole diagnostic spectrum in migraine.

conclusionsMigraine was associated with an increased multimorbidity, evidenced by multiple different approaches in the study. A systematic increase in the morbidity across the whole spectrum of ICD-10 coded diagnoses, and when interpreting PDNs, were detected in migraine patients. However, no specific diagnoses explained the morbidity. The results reflect clinical praxis, but also undoubtedly, the pathophysiological phenotypes related to migraine, and emphasize the importance of better understanding migraine-related morbidity.

Indexed as

MultimorbidityAdultElectronic Health RecordsFemaleFinlandHumansInternational Classification of DiseasesMaleMiddle AgedMigraine DisordersPhenotypePrevalenceRetrospective StudiesDiseasomeICD-10MigraineMultimorbidityNetworksOccupational healthcare

Identifiers

PMID32005102
PMCPMC6995206
OpenAlexW3013840818

What OpenQuestion holds

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LicenceCC BY
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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.