Electronic Resource

“Preeclampsia.com” App To Preeclampsia Screening At Community Level: A Cohort Study

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Indonesian maternal mortality in 2012, 32.5% was caused by hypertension, preeclampsia, and
eclampsia, while 24.22% in 2015 and 26% in 2016. Currently, there is no method of screening for
preeclampsia based on maternal characteristics that were carried out during the first visit antenatal. The use
of technology has great potential to improve health care at the community, especially in low-middle income
countries. It is necessary to make a breakthrough in the form of developing a screening model for
preeclampsia by utilizing information technology. This study aims to determine the detection rate of the
application of preeclampsia.com as a community-based preeclampsia screening tool. This study was
conducted by cohort study on 549 pregnant women who had their first antenatal visit before 16 weeks
followed up to delivery. Data analysis was data of factors for the occurrence of preeclampsia using Chi
square, while to determine the strength of the “Preeclampsia.com” model as a screening method and early
detection of preeclampsia using multilevel logistic regression, analysis performed using SPSS version 23.0.
The results of the analysis showed that the sensitivity value of the "Preeclampsia.com" application was
64.1% and the specificity value was 85.5% (95% CI). The Positive Predictive Value (PPV) from the
"preeclampsia.com" application is 25.3% and the Negative Predictive Value (NPV) from the
"preeclampsia.com" application is 96.9%. Based on the results of multilevel logistic regression analysis, it
was found that the ability of the model to predict the incidence of preeclampsia was 96.4%. The use of the
Preeclampsia.com application is quite good for community-based preeclampsia screening

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Ketersediaan

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Informasi Detail

Judul Seri

JURNAL KEBIDANAN

No. Panggil

618.2 JOH p

Penerbit

Semarang : Prodi S1 Kebidanan Poltekkes Kemenkes Semarang., 2023

Deskripsi Fisik

10 p

Bahasa

Indonesia

ISBN/ISSN

2621-2870

Klasifikasi

618.2

Tipe Isi

text

Tipe Media

unmediated

Tipe Pembawa

-

Edisi

Volume 13 Nomor 1 (2023)

Subjek

kebidanan

Info Detail Spesifik

-

Pernyataan Tanggungjawab

-

Versi lain/terkait

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