Evidence map›Paper›PMID 38783995›Full record

ArticleClinical epidemiology2024

Evaluation of Left Truncation and Censoring When Changing the Use of the

Søren Korsgaard, Frederikke Schønfeldt Troelsen, Katalin Veres, Cecilia Hvitfeldt Fuglsang, Henrik Toft Sørensen

Abstract read
In one paragraph

Article in Clinical epidemiology, 2024. 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. Review
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.

Søren KorsgaardDepartment of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark.ORCID 0000-0001-9251-2561
Frederikke Schønfeldt TroelsenDepartment of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark.ORCID 0000-0002-5276-5959
Katalin VeresDepartment of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark.ORCID 0000-0001-8549-8781
Cecilia Hvitfeldt FuglsangDepartment of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark.ORCID 0000-0003-2789-5003
Henrik Toft SørensenDepartment of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark.ORCID 0000-0003-4299-7040

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: In the Danish National Patient Registry (DNPR), covering all Danish hospitals and widely used in research, diseases have been recorded using Patients and Methods: We sampled 500,000 Danes ≥40 years of age in 1995, 2010, and 2018. From the DNPR, we identified cardiovascular, endocrine, gastrointestinal, neurological, pulmonary, rheumatic, and urogenital diseases as well as fractures. We obtained the number of people with a disease recorded with ICD-8 codes only ( Results: Overall, the left-truncation issue decreased over the years. Relative to all people with a disease, the left-truncated proportion was for example 59% in 1995 and <2% in 2018 for diabetes mellitus; 93% in 1995, and 54% in 2018 for appendicitis. The left-truncation issue increased with age group for most diseases. The proportion of disease records left-censored by not using ICD-8 codes was generally low but highest for chronic diseases. Conclusion: The left-truncation issue diminished over sample years, particularly for chronic diseases, yet remained rather high for selected surgical diseases. The left-truncation issue increased with age group for most diseases. Left-censoring was overall a minor issue that primarily concerned chronic diseases.

Indexed as

biasepidemiologyleft-censoringleft-truncationmethodology

Identifiers

PMID38783995
PMCPMC11114138

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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.