Evidence map›Paper›PMID 38500799›Full record

ArticleERJ open research2024

Measuring accuracy of International Classification of Diseases codes in identification of patients with non-cystic fibrosis bronchiectasis.

O'Neil Green, Sybille Liautaud, Alexander Knee, Lucy Modahl

Open access · goldAbstract read
In one paragraph

Article in ERJ open research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.2field-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

9 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. ERJ open research · 2025
    Article
  6. Article
  7. Epidemiology of bronchiectasis.European respiratory review : an official journal of the European Respiratory Society · 2024
    Review
  8. Article
  9. 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

4 authors at 2 institutions in 1 country.

O'Neil GreenDivision of Pulmonary and Critical Care Medicine, UMASS Chan School of Medicine/Baystate Campus, Springfield, MA, USA.
Sybille LiautaudDivision of Pulmonary and Critical Care Medicine, UMASS Chan School of Medicine/Baystate Campus, Springfield, MA, USA.
Alexander KneeDepartment of Healthcare Delivery and Population Science, UMASS Chan School of Medicine/Baystate Campus, Springfield, MA, USA.
Lucy ModahlDepartment of Radiology, NYU Grossman School of Medicine, New York, NY, USA.
Baystate Health · USNew York University · US

Funding

Tufts Clinical and Translational Science Institute (Pilot Supplement)UL1TR002544 · NCATS · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2018 to 2022
$50.2M
NCATS NIH HHS UL1 TR002544
6 · The paper itself

Abstract

Introduction: Non-cystic fibrosis bronchiectasis is a disease which is increasing in incidence and prevalence worldwide. The incidence of the disease is frequently estimated using databases that rely on International Classification of Diseases, ninth and tenth revisions, clinical modification (ICD-9-CM/ICD-10-CM) discharge diagnoses. Code accuracy has proved to be a major issue for other diagnoses using ICD codes. This study aims to investigate the accuracy of the ICD codes for the diagnosis of non-cystic fibrosis bronchiectasis. Methods: This is a retrospective diagnostic accuracy study which compares the radiologist's diagnosis of bronchiectasis with the ICD code reflection of that diagnosis at discharge. Results: Sensitivities were 34% (same for both ICD-9-CM and ICD-10-CM windows) and specificities ranged from 69% for the ICD-9-CM window to 81% for ICD-10-CM window. Conclusion: We observed that ICD codes are an insufficient method to identify patients with a radiologist diagnosis of bronchiectasis.

Identifiers

PMID38500799
PMCPMC10945379
OpenAlexW4391655905

What OpenQuestion holds

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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.