Sabahat Naz, Samreen Jamal, Ali Jaffar, Iqbal Azam, Subhash Chandir, Rahat Qureshi, Neelofur Babar, Aisha Syed Wali, Romaina Iqbal
{"title":"开发和验证用于筛查巴基斯坦妊娠糖尿病高危孕妇的非 INvaSive Pregnancy RIsk ScoRE (INSPIRE)","authors":"Sabahat Naz, Samreen Jamal, Ali Jaffar, Iqbal Azam, Subhash Chandir, Rahat Qureshi, Neelofur Babar, Aisha Syed Wali, Romaina Iqbal","doi":"10.1136/bmjph-2024-000920","DOIUrl":null,"url":null,"abstract":"The prevalence of gestational diabetes mellitus (GDM) is on the rise in low-income and middle-income countries, such as Pakistan. Therefore, the development of a risk score that is simple, affordable and easy to administer is needed. Our study aimed to develop a Non-INvaSive Pregnancy RIsk ScoRE (INSPIRE) for GDM screening in Pakistani pregnant women based on risk factors reported in the literature.Using a cross-sectional study design, we enrolled 500 pregnant women who attended antenatal clinics at one tertiary and two secondary care hospitals in Karachi between the 28th and 32nd weeks of gestation. We randomly divided data into derivation (n=404; 80%) and validation datasets (n=96; 20%). We conducted interviews to collect information on sociodemographic factors and family history of diabetes, measured mid-upper arm circumference (MUAC) and reviewed the medical records of women for obstetric history and oral glucose tolerance test (OGTT) results. We performed a multivariable logistic regression analysis to obtain coefficients of selected predictors for GDM in the derivation dataset. Calibration was estimated using Pearson’s χ2 goodness of fit test while discrimination was checked using the area under the curve (AUC) in the validation dataset.Overall, the GDM prevalence was 26% (n=130). INSPIRE was based on six predictors: maternal age, MUAC, family history of diabetes, a history of GDM, previous bad obstetrical outcome and a history of macrosomia. INSPIRE achieved a good calibration (Pearson’s χ2=29.55, p=0.08) and acceptable discrimination with an AUC of 0.721 (95% CI 0.61 to 0.83) with a sensitivity of 74.1% and specificity of 59.4% in the validation dataset.We developed and validated an INSPIRE that efficiently differentiates Pakistani pregnant women at high risk of GDM from those at low risk, thus reducing the unnecessary burden of the OGTT test.","PeriodicalId":117861,"journal":{"name":"BMJ Public Health","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development and validation of a Non-INvaSive Pregnancy RIsk ScoRE (INSPIRE) for the screening of high-risk pregnant women for gestational diabetes mellitus in Pakistan\",\"authors\":\"Sabahat Naz, Samreen Jamal, Ali Jaffar, Iqbal Azam, Subhash Chandir, Rahat Qureshi, Neelofur Babar, Aisha Syed Wali, Romaina Iqbal\",\"doi\":\"10.1136/bmjph-2024-000920\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The prevalence of gestational diabetes mellitus (GDM) is on the rise in low-income and middle-income countries, such as Pakistan. Therefore, the development of a risk score that is simple, affordable and easy to administer is needed. Our study aimed to develop a Non-INvaSive Pregnancy RIsk ScoRE (INSPIRE) for GDM screening in Pakistani pregnant women based on risk factors reported in the literature.Using a cross-sectional study design, we enrolled 500 pregnant women who attended antenatal clinics at one tertiary and two secondary care hospitals in Karachi between the 28th and 32nd weeks of gestation. We randomly divided data into derivation (n=404; 80%) and validation datasets (n=96; 20%). We conducted interviews to collect information on sociodemographic factors and family history of diabetes, measured mid-upper arm circumference (MUAC) and reviewed the medical records of women for obstetric history and oral glucose tolerance test (OGTT) results. We performed a multivariable logistic regression analysis to obtain coefficients of selected predictors for GDM in the derivation dataset. Calibration was estimated using Pearson’s χ2 goodness of fit test while discrimination was checked using the area under the curve (AUC) in the validation dataset.Overall, the GDM prevalence was 26% (n=130). INSPIRE was based on six predictors: maternal age, MUAC, family history of diabetes, a history of GDM, previous bad obstetrical outcome and a history of macrosomia. INSPIRE achieved a good calibration (Pearson’s χ2=29.55, p=0.08) and acceptable discrimination with an AUC of 0.721 (95% CI 0.61 to 0.83) with a sensitivity of 74.1% and specificity of 59.4% in the validation dataset.We developed and validated an INSPIRE that efficiently differentiates Pakistani pregnant women at high risk of GDM from those at low risk, thus reducing the unnecessary burden of the OGTT test.\",\"PeriodicalId\":117861,\"journal\":{\"name\":\"BMJ Public Health\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMJ Public Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1136/bmjph-2024-000920\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Public Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmjph-2024-000920","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development and validation of a Non-INvaSive Pregnancy RIsk ScoRE (INSPIRE) for the screening of high-risk pregnant women for gestational diabetes mellitus in Pakistan
The prevalence of gestational diabetes mellitus (GDM) is on the rise in low-income and middle-income countries, such as Pakistan. Therefore, the development of a risk score that is simple, affordable and easy to administer is needed. Our study aimed to develop a Non-INvaSive Pregnancy RIsk ScoRE (INSPIRE) for GDM screening in Pakistani pregnant women based on risk factors reported in the literature.Using a cross-sectional study design, we enrolled 500 pregnant women who attended antenatal clinics at one tertiary and two secondary care hospitals in Karachi between the 28th and 32nd weeks of gestation. We randomly divided data into derivation (n=404; 80%) and validation datasets (n=96; 20%). We conducted interviews to collect information on sociodemographic factors and family history of diabetes, measured mid-upper arm circumference (MUAC) and reviewed the medical records of women for obstetric history and oral glucose tolerance test (OGTT) results. We performed a multivariable logistic regression analysis to obtain coefficients of selected predictors for GDM in the derivation dataset. Calibration was estimated using Pearson’s χ2 goodness of fit test while discrimination was checked using the area under the curve (AUC) in the validation dataset.Overall, the GDM prevalence was 26% (n=130). INSPIRE was based on six predictors: maternal age, MUAC, family history of diabetes, a history of GDM, previous bad obstetrical outcome and a history of macrosomia. INSPIRE achieved a good calibration (Pearson’s χ2=29.55, p=0.08) and acceptable discrimination with an AUC of 0.721 (95% CI 0.61 to 0.83) with a sensitivity of 74.1% and specificity of 59.4% in the validation dataset.We developed and validated an INSPIRE that efficiently differentiates Pakistani pregnant women at high risk of GDM from those at low risk, thus reducing the unnecessary burden of the OGTT test.