Evidence map›Paper›PMID 37330464›Full record

ArticleBMC medical research methodology2023

Frequency-based rare diagnoses as a novel and accessible approach for studying rare diseases in large datasets: a cross-sectional study.

Thomas S Tröster, Viktor von Wyl, Patrick E Beeler, Holger Dressel

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in BMC medical research methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. [Rare diseases in a medical genetics service of population with social security].Revista medica del Instituto Mexicano del Seguro Social · 2024
    Article
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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

4 authors at 2 institutions in 1 country.

Thomas S TrösterDivision of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich and University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-2552-8544
Viktor von WylEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0002-8754-9797
Patrick E Beeler *Division of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich and University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-6097-2480
Holger Dressel *Division of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich and University Hospital Zurich, Zurich, Switzerland. holger.dressel@usz.ch.ORCID 0000-0002-1268-0416
University of Zurich · CHUniversity of Lucerne · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUp to 8% of the general population have a rare disease, however, for lack of ICD-10 codes for many rare diseases, this population cannot be generically identified in large medical datasets. We aimed to explore frequency-based rare diagnoses (FB-RDx) as a novel method exploring rare diseases by comparing characteristics and outcomes of inpatient populations with FB-RDx to those with rare diseases based on a previously published reference list.

methodsRetrospective, cross-sectional, nationwide, multicenter study including 830,114 adult inpatients. We used the national inpatient cohort dataset of the year 2018 provided by the Swiss Federal Statistical Office, which routinely collects data from all inpatients treated in any Swiss hospital. Exposure: FB-RDx, according to 10% of inpatients with the least frequent diagnoses (i.e.1.decile) vs. those with more frequent diagnoses (deciles 2-10). Results were compared to patients having 1 of 628 ICD-10 coded rare diseases. PRIMARY OUTCOME: In-hospital death. SECONDARY OUTCOMES: 30-day readmission, admission to intensive care unit (ICU), length of stay, and ICU length of stay. Multivariable regression analyzed associations of FB-RDx and rare diseases with these outcomes.

results464,968 (56%) of patients were female, median age was 59 years (IQR: 40-74). Compared with patients in deciles 2-10, patients in the 1. were at increased risk of in-hospital death (OR 1.44; 95% CI: 1.38, 1.50), 30-day readmission (OR 1.29; 95% CI 1.25, 1.34), ICU admission (OR 1.50; 95% CI 1.46, 1.54), increased length of stay (Exp(B) 1.03; 95% CI 1.03, 1.04) and ICU length of stay (1.15; 95% CI 1.12, 1.18). ICD-10 based rare diseases groups showed similar results: in-hospital death (OR 1.82; 95% CI 1.75, 1.89), 30-day readmission (OR 1.37; 95% CI 1.32, 1.42), ICU admission (OR 1.40; 95% CI 1.36, 1.44) and increased length of stay (OR 1.07; 95% CI 1.07, 1.08) and ICU length of stay (OR 1.19; 95% CI 1.16, 1.22). CONCLUSION(S): This study suggests that FB-RDx may not only act as a surrogate for rare diseases but may also help to identify patients with rare disease more comprehensively. FB-RDx associate with in-hospital death, 30-day readmission, intensive care unit admission, and increased length of stay and intensive care unit length of stay, as has been reported for rare diseases.

Indexed as

HospitalizationRare DiseasesAdultCross-Sectional StudiesFemaleHospital MortalityHumansIntensive Care UnitsLength of StayMaleMiddle AgedRetrospective StudiesRare disease [MAJR]Rare diseases/epidemiology [MeSH Terms]Rare diseases/mortality [MeSH Terms]Rare diseases/statistics and numerical data [MeSH Terms]

Identifiers

PMID37330464
PMCPMC10276905
OpenAlexW4381094473

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.