Evidence map›Paper›PMID 30522591›Full record

ArticleMayo Clinic proceedings2018

Electronic Algorithm Is Superior to Hospital Discharge Codes for Diagnoses of Hypertensive Disorders of Pregnancy in Historical Cohorts.

Natasa M Milic, Elisabeth Codsi, Yvonne S Butler Tobah, Wendy M White, Andrea G Kattah, Tracey L Weissgerber, Mie Saiki, Santosh Parashuram, Lisa E Vaughan, Amy L Weaver and 3 more

Abstract readComparative StudyValidation Study
In one paragraph

Article in Mayo Clinic proceedings, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Incidence and Long-Term Outcomes of Hypertensive Disorders of Pregnancy.Journal of the American College of Cardiology · 2020
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Natasa M MilicDivision of Nephrology and Hypertension, University of Belgrade, Belgrade, Serbia; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia.
Elisabeth CodsiDepartment of Obstetrics and Gynecology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN.
Yvonne S Butler TobahDepartment of Obstetrics and Gynecology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN.
Wendy M WhiteDepartment of Obstetrics and Gynecology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN.
Andrea G KattahDivision of Nephrology and Hypertension, University of Belgrade, Belgrade, Serbia.
Tracey L WeissgerberDivision of Nephrology and Hypertension, University of Belgrade, Belgrade, Serbia.
Mie SaikiDivision of Nephrology and Hypertension, University of Belgrade, Belgrade, Serbia.
Santosh ParashuramDivision of Nephrology and Hypertension, University of Belgrade, Belgrade, Serbia.
Lisa E VaughanDivision of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN.
Amy L WeaverDivision of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN.
Marko SavicDepartment of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia.
Michelle M MielkeDepartment of Health Sciences Research and Department of Neurology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN.
Vesna D GarovicDivision of Nephrology and Hypertension, University of Belgrade, Belgrade, Serbia; Department of Obstetrics and Gynecology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN. Electronic address: garovic.vesna@mayo.edu.

Funding

Rochester Epidemiology ProjectR01AG034676 · NIA · MAYO CLINIC ROCHESTER · PI ROCCA, WALTER A, ST SAUVER, JENNIFER LYNN · 2010 to 2019
$9.5M
Sex-specific Risk for Vascular Dysfunction and Cognitive DeclineP50AG044170 · NIA · MAYO CLINIC ROCHESTER · PI MILLER, VIRGINIA M · 2012 to 2017
$6.1M
Reproductive risk factors for Alzheimer's disease dementia and pathologyRF1AG055151 · NIA · MAYO CLINIC ROCHESTER · PI MIELKE, MICHELLE M, ROCCA, WALTER A · 2017 to 2017
$4.0M
Hypertensive pregnancy disorders and future coronary artery diseaseR01HL136348 · NHLBI · MAYO CLINIC ROCHESTER · PI GAROVIC, VESNA D · 2018 to 2022
$2.6M
NHLBI NIH HHS R01 HL136348NIA NIH HHS P50 AG044170NIA NIH HHS R01 AG034676NIA NIH HHS RF1 AG055151
6 · The paper itself

Abstract

objectivesTo develop and validate criteria for the retrospective diagnoses of hypertensive disorders of pregnancy that would be amenable to the development of an electronic algorithm, and to compare the accuracy of diagnoses based on both the algorithm and diagnostic codes with the gold standard, of physician-made diagnoses based on a detailed review of medical records using accepted clinical criteria. PATIENTS AND

methodsAn algorithm for hypertensive disorders of pregnancy was developed by first defining a set of criteria for retrospective diagnoses, which included relevant clinical variables and diagnosis of hypertension that required blood pressure elevations in greater than 50% of readings ("the 50% rule"). The algorithm was validated using the Rochester Epidemiology Project (Rochester, Minnesota). A stratified random sample of pregnancies and deliveries between January 1, 1976, and December 31, 1982, with the algorithm-based diagnoses was generated for review and physician-made diagnoses (normotensive, gestational hypertension, and preeclampsia), which served as the gold standard; the targeted cohort size for analysis was 25 per diagnosis category according to the gold standard. Agreements between (1) algorithm-based diagnoses and (2) diagnostic codes and the gold standard were analyzed.

resultsSensitivities of the algorithm for 25 normotensive pregnancies, 25 with gestational hypertension, and 25 with preeclampsia were 100%, 88%, and 100%, respectively, and specificities were 94%, 100%, and 100%, respectively. Diagnostic code sensitivities were 96% for normotensive pregnancies, 32% for gestational hypertension, and 96% for preeclampsia, and specificities were 78%, 96%, and 88%, respectively.

conclusionThe electronic diagnostic algorithm was highly sensitive and specific in identifying and classifying hypertensive disorders of pregnancy and was superior to diagnostic codes.

Indexed as

AlgorithmsPredictive Value of TestsAdultCase-Control StudiesCohort StudiesDatabases, FactualFemaleGestational AgeHumansHypertension, Pregnancy-InducedPregnancyYoung Adult

Identifiers

PMID30522591
PMCPMC6353636

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.