Evidence map›Paper›PMID 21152251›Full record

ArticleClinical epidemiology2010

Validation of spontaneous abortion diagnoses in the Danish National Registry of Patients.

Sarah Rytter Lohse, Dóra Körmendiné Farkas, Nicolai Lohse, Sven Olaf Skouby, Finn Erland Nielsen, Timothy L Lash, Vera Ehrenstein

Open access · goldAbstract read
In one paragraph

Article in Clinical epidemiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
11.4field-weighted citation impact, top 2% 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

38 citing papers in PubMed, 80 citations in OpenAlex.

  1. Article
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  7. Ciprofloxacin exposure and adverse pregnancy outcomes: A Danish nationwide cohort study.BJOG : an international journal of obstetrics and gynaecology · 2022
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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

7 authors at 2 institutions in 1 country.

Sarah Rytter LohseDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark;
Dóra Körmendiné Farkas
Nicolai Lohse
Sven Olaf Skouby
Finn Erland Nielsen
Timothy L Lash
Vera Ehrenstein
Aarhus University Hospital · DKHerlev Hospital · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe purpose of this study is to validate the diagnosis of spontaneous abortion (SA) recorded in the Danish National Registry of Patients (DNRP).

methodsWe randomly selected patients registered in the DNRP with a diagnosis of SA between 1980 and 2008 from hospitals in the county of North Jutland and searched for their discharge records in hospital files. We estimated positive predictive value (PPV) of the DNRP diagnosis and stratified the analysis by period (1980-1994 versus 1995-2008), hospital type (regional versus local), and International Classification of Diseases revisions (ICD-8 versus ICD-10).

resultsWe could identify hospital files of 117/174 (67%) sampled registration records. Of those, the diagnosis was confirmed in 114 patients, yielding a PPV of 97.4% (95% confidence interval = 92.7%-99.5%). The PPV did not markedly vary by period, hospital type, or ICD revision. Among the three patients with available data who did not fulfill the criteria for SA, one had an induced abortion and two had threatened abortion but did not miscarry.

conclusionRegistration of SA in the DNRP accurately reflects the diagnoses recorded in medical charts. The DNRP is a suitable source of data on SAs for epidemiologic research.

Indexed as

Danish National Registry of Patientsdiagnosispositive predictive valuespontaneous abortionvalidation

Identifiers

PMID21152251
PMCPMC2998814
OpenAlexW2003648701

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.