Evidence map›Paper›PMID 37873883›Full record

ArticleEpidemiologia (Basel, Switzerland)2023

Agreement in All-in-One Dataset between Diagnosis and Prescribed Medication for Common Cardiometabolic Diseases in the NDB-K7Ps.

Airi Sekine, Kei Nakajima

Open access · goldAbstract read
In one paragraph

Article in Epidemiologia (Basel, Switzerland), 2023. 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
0.4field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Airi SekineDepartment of Food and Nutrition, Faculty of Human Sciences and Design, Japan Women's University, Tokyo 112-8681, Japan.ORCID 0000-0002-2372-8200
Kei NakajimaDepartment of Food and Nutrition, Faculty of Human Sciences and Design, Japan Women's University, Tokyo 112-8681, Japan.ORCID 0000-0002-1788-3896
Japan Women's University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Japanese National Database (NDB), a useful data source for epidemiological studies, contains information on health checkups, disease diagnoses, and medications, which can be used when investigating common cardiometabolic diseases. However, before the initiation of an integrated analysis, we need to combine several pieces of information prepared separately into an all-in-one dataset (AIOD) and confirm the validation of the dataset for the study. In this study, we aimed to confirm the degree of agreement in data entries between diagnoses and prescribed medications and self-reported pharmacotherapy for common cardiometabolic diseases in newly assembled AIODs. The present study included 10,183,619 people who underwent health checkups from April 2018 to March 2019. Over 95% of patients prescribed antihypertensive and antidiabetic medications were diagnosed with each disease. For dyslipidemia, over 95% of patients prescribed medications were diagnosed with at least one of the following: dyslipidemia, hypercholesterolemia, or hyperlipidemia. Similarly, over 95% of patients prescribed medications for hyperuricemia were diagnosed with either hyperuricemia or gout. Additionally, over 90% of patients with self-reported medications for hypertension, diabetes, and dyslipidemia were diagnosed with each disease, although the proportions differed among age groups. Our study demonstrated high levels of agreement between diagnoses and prescribed medications for common cardiometabolic diseases and self-reported pharmacotherapy in our AIOD.

Indexed as

cardiometabolic diseasesdiagnosishealth checkupsnational databaseprescribed medication

Identifiers

PMID37873883
PMCPMC10594522
OpenAlexW4387251868

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.