{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T14:56:45Z","timestamp":1790089005351,"version":"4.0.1"},"reference-count":59,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,4,27]],"date-time":"2020-04-27T00:00:00Z","timestamp":1587945600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["Postgraduate Scholarship"],"award-info":[{"award-number":["Postgraduate Scholarship"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["Career Development Fellowship"],"award-info":[{"award-number":["Career Development Fellowship"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Diabetes Australia Research Program","award":["National Health and Medical Research Council Top-up Scholarship"],"award-info":[{"award-number":["National Health and Medical Research Council Top-up Scholarship"]}]},{"DOI":"10.13039\/501100000969","name":"Australian Academy of Science","doi-asserted-by":"publisher","award":["Douglas and Lola Douglas Scholarship"],"award-info":[{"award-number":["Douglas and Lola Douglas Scholarship"]}],"id":[{"id":"10.13039\/501100000969","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Australian Government Department of Education and Training","award":["Endeavour Research Leadership Award"],"award-info":[{"award-number":["Endeavour Research Leadership Award"]}]},{"name":"Medical Research Future Fund","award":["National Health and Medical Research Council Fellowship"],"award-info":[{"award-number":["National Health and Medical Research Council Fellowship"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Gestational diabetes (GDM) increases the risk of pregnancy complications. However, these risks are not the same for all affected women and may be mediated by inter-related factors including ethnicity, body mass index and gestational weight gain. This study was conducted to identify, compare, and critically appraise prognostic prediction models for pregnancy complications in women with gestational diabetes (GDM). A systematic review of prognostic prediction models for pregnancy complications in women with GDM was conducted. Critical appraisal was conducted using the prediction model risk of bias assessment tool (PROBAST). Five prediction modelling studies were identified, from which ten prognostic models primarily intended to predict pregnancy complications related to GDM were developed. While the composition of the pregnancy complications predicted varied, the delivery of a large-for-gestational age neonate was the subject of prediction in four studies, either alone or as a component of a composite outcome. Glycaemic measures and body mass index were selected as predictors in four studies. Model evaluation was limited to internal validation in four studies and not reported in the fifth. Performance was inadequately reported with no useful measures of calibration nor formal evaluation of clinical usefulness. Critical appraisal using PROBAST revealed that all studies were subject to a high risk of bias overall driven by methodologic limitations in statistical analysis. This review demonstrates the potential for prediction models to provide an individualised absolute risk of pregnancy complications for women affected by GDM. However, at present, a lack of external validation and high risk of bias limit clinical application. Future model development and validation should utilise the latest methodological advances in prediction modelling to achieve the evolution required to create a useful clinical tool. Such a tool may enhance clinical decision-making and support a risk-stratified approach to the management of GDM. Systematic review registration: PROSPERO CRD42019115223.<\/jats:p>","DOI":"10.3390\/ijerph17093048","type":"journal-article","created":{"date-parts":[[2020,4,28]],"date-time":"2020-04-28T05:05:32Z","timestamp":1588050332000},"page":"3048","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["The Unrealised Potential for Predicting Pregnancy Complications in Women with Gestational Diabetes: A Systematic Review and Critical Appraisal"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6825-4440","authenticated-orcid":false,"given":"Shamil D.","family":"Cooray","sequence":"first","affiliation":[{"name":"Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3800, Australia"},{"name":"Diabetes Unit, Monash Health, Clayton, VIC 3168, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lihini A.","family":"Wijeyaratne","sequence":"additional","affiliation":[{"name":"Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Georgia","family":"Soldatos","sequence":"additional","affiliation":[{"name":"Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3800, Australia"},{"name":"Diabetes Unit, Monash Health, Clayton, VIC 3168, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Allotey","sequence":"additional","affiliation":[{"name":"Barts Research Centre for Women\u2019s Health, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AB, UK"},{"name":"Multidisciplinary Evidence Synthesis Hub, Queen Mary University of London, London E1 2AB, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3616-1637","authenticated-orcid":false,"given":"Jacqueline A.","family":"Boyle","sequence":"additional","affiliation":[{"name":"Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3800, Australia"},{"name":"Monash Women\u2019s Program, Monash Health, Clayton, VIC 3168, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7609-577X","authenticated-orcid":false,"given":"Helena J.","family":"Teede","sequence":"additional","affiliation":[{"name":"Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3800, Australia"},{"name":"Diabetes Unit, Monash Health, Clayton, VIC 3168, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1097\/AOG.0000000000000928","article-title":"Adverse Outcomes and Potential Targets for Intervention in Gestational Diabetes and Obesity","volume":"126","author":"Scifres","year":"2015","journal-title":"Obstet. Gynecol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.jogoh.2018.08.003","article-title":"Joint impact of gestational diabetes and obesity on perinatal outcomes","volume":"47","author":"Huet","year":"2018","journal-title":"J. Gynecol. Obstet. Hum. Reprod."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.1001\/jama.2017.3635","article-title":"Association of Gestational Weight Gain With Maternal and Infant Outcomes: A Systematic Review and Meta-analysis","volume":"317","author":"Goldstein","year":"2017","journal-title":"JAMA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1007\/s11892-018-1040-2","article-title":"Ethnic Disparities in Gestational Diabetes","volume":"18","author":"Yuen","year":"2018","journal-title":"Curr. Diab. Rep."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.2337\/dc15-2672","article-title":"Heterogeneous Contribution of Insulin Sensitivity and Secretion Defects to Gestational Diabetes Mellitus","volume":"39","author":"Powe","year":"2016","journal-title":"Diabetes Care"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2118","DOI":"10.1007\/s00125-019-4961-7","article-title":"Characteristics and pregnancy outcomes across gestational diabetes mellitus subtypes based on insulin resistance","volume":"62","author":"Benhalima","year":"2019","journal-title":"Diabetologia"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1111\/1753-0407.12909","article-title":"Ethnic differences in prevalence, risk factors, and perinatal outcomes of gestational diabetes mellitus: A comparison between immigrant ethnic Chinese women and Australian-born Caucasian women in Australia","volume":"11","author":"Wan","year":"2019","journal-title":"J. Diabetes"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1111\/ajo.12676","article-title":"The IADPSG diagnostic criteria identify women with increased risk of adverse pregnancy outcomes in Victoria","volume":"57","author":"Abell","year":"2017","journal-title":"Aust. N. Z. J. Obstet. Gynaecol."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Behboudi-Gandevani, S., Amiri, M., Bidhendi Yarandi, R., and Ramezani Tehrani, F. (2019). The impact of diagnostic criteria for gestational diabetes on its prevalence: A systematic review and meta-analysis. Diabetol. Metab. Syndr., 11.","DOI":"10.1186\/s13098-019-0406-1"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1111\/1471-0528.14236","article-title":"Gestational diabetes in the United States: Temporal changes in prevalence rates between 1979 and 2010","volume":"124","author":"Lavery","year":"2017","journal-title":"BJOG"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1111\/ajo.12447","article-title":"The prevalence of hyperglycaemia in pregnancy in Australia","volume":"56","author":"Moses","year":"2016","journal-title":"Aust. N. Z. J. Obstet. Gynaecol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.diabres.2017.04.018","article-title":"Adopting the new World Health Organization diagnostic criteria for gestational diabetes: How the prevalence changes in a high-risk region in Australia","volume":"129","author":"Wong","year":"2017","journal-title":"Diabetes Res. Clin. Pract."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.ajog.2015.06.013","article-title":"Prognostic models in obstetrics: Available, but far from applicable","volume":"214","author":"Kleinrouweler","year":"2016","journal-title":"Am. J. Obstet. Gynecol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1539","DOI":"10.1136\/bmj.311.7019.1539","article-title":"Commentary: Prognostic models: Clinically useful or quickly forgotten?","volume":"311","author":"Wyatt","year":"1995","journal-title":"BMJ"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1186\/s41512-019-0049-6","article-title":"The increasing need for systematic reviews of prognosis studies: Strategies to facilitate review production and improve quality of primary research","volume":"3","author":"Damen","year":"2019","journal-title":"Diagn. Progn. Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1186\/s13643-019-1151-0","article-title":"Prognostic prediction models for pregnancy complications in women with gestational diabetes: A protocol for systematic review, critical appraisal and meta-analysis","volume":"8","author":"Cooray","year":"2019","journal-title":"Syst. Rev."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1136\/jamia.2001.0080391","article-title":"Searching for clinical prediction rules in MEDLINE","volume":"8","author":"Ingui","year":"2001","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Geersing, G.J., Bouwmeester, W., Zuithoff, P., Spijker, R., Leeflang, M., and Moons, K.G. (2012). Search filters for finding prognostic and diagnostic prediction studies in Medline to enhance systematic reviews. PLoS ONE, 7.","DOI":"10.1371\/annotation\/96bdb520-d704-45f0-a143-43a48552952e"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Moons, K.G., de Groot, J.A., Bouwmeester, W., Vergouwe, Y., Mallett, S., Altman, D.G., Reitsma, J.B., and Collins, G.S. (2014). Critical appraisal and data extraction for systematic reviews of prediction modelling studies: The CHARMS checklist. PLoS Med., 11.","DOI":"10.1371\/journal.pmed.1001744"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"51","DOI":"10.7326\/M18-1376","article-title":"PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies","volume":"170","author":"Wolff","year":"2019","journal-title":"Ann. Intern. Med."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.diabres.2018.02.036","article-title":"Development of a risk engine relating maternal glycemia and body mass index to pregnancy outcomes","volume":"139","author":"McIntyre","year":"2018","journal-title":"Diabetes Res. Clin. Pract."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e2204","DOI":"10.1097\/MD.0000000000002204","article-title":"Development of a Screening Tool for Predicting Adverse Outcomes of Gestational Diabetes Mellitus: A Retrospective Cohort Study","volume":"95","author":"Park","year":"2016","journal-title":"Medicine (Baltimore)"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1515\/JPM.2009.108","article-title":"Risk assessment for preeclampsia in women with gestational diabetes mellitus","volume":"37","author":"Phaloprakarn","year":"2009","journal-title":"J. Perinat. Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1007\/s00592-018-1208-x","article-title":"The risk stratification of adverse neonatal outcomes in women with gestational diabetes (STRONG) study","volume":"55","author":"Pintaudi","year":"2018","journal-title":"Acta Diabetol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s00404-018-4758-9","article-title":"Fetal overgrowth in pregnancies complicated by diabetes: Development of a clinical prediction index","volume":"298","author":"Tomlinson","year":"2018","journal-title":"Arch. Gynecol. Obstet."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1991","DOI":"10.1056\/NEJMoa0707943","article-title":"Hyperglycemia and Adverse Pregnancy Outcomes","volume":"358","author":"Metzger","year":"2008","journal-title":"New Engl. J. Med."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1016\/0002-9378(82)90349-0","article-title":"Criteria for screening tests for gestational diabetes","volume":"144","author":"Carpenter","year":"1982","journal-title":"Am. J. Obstet. Gynecol."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Committee on Practice Bulletins-Obstetrics (2018). ACOG Practice Bulletin No. 190: Gestational Diabetes Mellitus. Obstet. Gynecol., 131, e49\u2013e64.","DOI":"10.1097\/AOG.0000000000002501"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"International Association of Diabetes Pregnancy Study Groups Consensus Panel, Metzger, B.E., Gabbe, S.G., Persson, B., Buchanan, T.A., Catalano, P.A., Damm, P., Dyer, A.R., Leiva, A., and Hod, M. (2010). International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care, 33, 676\u2013682.","DOI":"10.2337\/dc09-1848"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"e011190","DOI":"10.1136\/bmjopen-2016-011190","article-title":"Systematic review of prognostic models for recurrent venous thromboembolism (VTE) post-treatment of first unprovoked VTE","volume":"6","author":"Ensor","year":"2016","journal-title":"BMJ Open"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/s41512-016-0005-7","article-title":"Prediction models for the risk of gestational diabetes: A systematic review","volume":"1","author":"Kwee","year":"2017","journal-title":"Diagn. Progn. Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2331","DOI":"10.1007\/s00125-016-4047-8","article-title":"A novel validated model for the prediction of insulin therapy initiation and adverse perinatal outcomes in women with gestational diabetes mellitus","volume":"59","author":"Barnes","year":"2016","journal-title":"Diabetologia"},{"key":"ref_33","unstructured":"Pedersen, J. (1952). Diabetes and Pregnancy: Blood Sugar of Newborn Infants. [Ph.D. Thesis, Danish Science Press]."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.2337\/diab.29.12.1023","article-title":"Banting Lecture 1980. Of pregnancy and progeny","volume":"29","author":"Freinkel","year":"1980","journal-title":"Diabetes"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"372","DOI":"10.2337\/dc18-1646","article-title":"Hyperglycemia and Adverse Pregnancy Outcome Follow-up Study (HAPO FUS): Maternal Gestational Diabetes Mellitus and Childhood Glucose Metabolism","volume":"42","author":"Lowe","year":"2019","journal-title":"Diabetes Care"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1007\/s00125-010-2008-1","article-title":"Cardiovascular risk factors in children exposed to maternal diabetes in utero","volume":"54","author":"West","year":"2011","journal-title":"Diabetologia"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s00125-010-1925-3","article-title":"Association of exposure to diabetes in utero with adiposity and fat distribution in a multiethnic population of youth: The Exploring Perinatal Outcomes among Children (EPOCH) Study","volume":"54","author":"Crume","year":"2011","journal-title":"Diabetologia"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.1007\/s00125-018-4584-4","article-title":"Long-term BMI and growth profiles in offspring of women with gestational diabetes","volume":"61","author":"Hammoud","year":"2018","journal-title":"Diabetologia"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1159\/000439487","article-title":"Interrupting Intergenerational Cycles of Maternal Obesity","volume":"85","author":"Gillman","year":"2016","journal-title":"Nestle Nutr. Inst. Workshop Ser."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1136\/bmj.330.7491.594","article-title":"Validity of composite end points in clinical trials","volume":"330","author":"Montori","year":"2005","journal-title":"BMJ"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1276","DOI":"10.1002\/sim.7992","article-title":"Minimum sample size for developing a multivariable prediction model: PART II\u2014Binary and time-to-event outcomes","volume":"38","author":"Riley","year":"2019","journal-title":"Stat. Med."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1177\/0272989X12437605","article-title":"Dichotomizing continuous variables in statistical analysis: A practice to avoid","volume":"32","author":"Dawson","year":"2012","journal-title":"Med. Decis. Making"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1159\/000126908","article-title":"Leave \u2019em alone\u2014Why continuous variables should be analyzed as such","volume":"30","author":"Hart","year":"2008","journal-title":"Neuroepidemiology"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1002\/sim.2331","article-title":"Dichotomizing continuous predictors in multiple regression: A bad idea","volume":"25","author":"Royston","year":"2006","journal-title":"Stat. Med."},{"key":"ref_45","unstructured":"Steyerberg, E.W. (2019). Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating, Springer International Publishing. [2nd ed.]."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"W1","DOI":"10.7326\/M18-1377","article-title":"Probast: A tool to assess risk of bias and applicability of prediction model studies: Explanation and elaboration","volume":"170","author":"Moons","year":"2019","journal-title":"Ann. Intern. Med."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"W1","DOI":"10.7326\/M14-0698","article-title":"Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): Explanation and elaboration","volume":"162","author":"Moons","year":"2015","journal-title":"Ann. Intern. Med."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Collins, G.S., de Groot, J.A., Dutton, S., Omar, O., Shanyinde, M., Tajar, A., Voysey, M., Wharton, R., Yu, L.M., and Moons, K.G. (2014). External validation of multivariable prediction models: A systematic review of methodological conduct and reporting. BMC Med. Res. Methodol., 14.","DOI":"10.1186\/1471-2288-14-40"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1097\/EDE.0b013e3181c30fb2","article-title":"Assessing the performance of prediction models: A framework for traditional and novel measures","volume":"21","author":"Steyerberg","year":"2010","journal-title":"Epidemiology"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1177\/0272989X06295361","article-title":"Decision curve analysis: A novel method for evaluating prediction models","volume":"26","author":"Vickers","year":"2006","journal-title":"Med. Decis. Mak."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Allotey, J., Fernandez-Felix, B.M., Zamora, J., Moss, N., Bagary, M., Kelso, A., Khan, R., van der Post, J.A.M., Mol, B.W., and Pirie, A.M. (2019). Predicting seizures in pregnant women with epilepsy: Development and external validation of a prognostic model. PLoS Med., 16.","DOI":"10.1371\/journal.pmed.1002802"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1001\/jama.2015.37","article-title":"Decision curve analysis","volume":"313","author":"Fitzgerald","year":"2015","journal-title":"JAMA"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Holmberg, L., and Vickers, A. (2013). Evaluation of prediction models for decision-making: Beyond calibration and discrimination. PLoS Med., 10.","DOI":"10.1371\/journal.pmed.1001491"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"294","DOI":"10.7326\/0003-4819-157-4-201208210-00014","article-title":"Beyond the usual prediction accuracy metrics: Reporting results for clinical decision making","volume":"157","author":"Localio","year":"2012","journal-title":"Ann. Intern. Med."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"l737","DOI":"10.1136\/bmj.l737","article-title":"Guide to presenting clinical prediction models for use in clinical settings","volume":"365","author":"Bonnett","year":"2019","journal-title":"BMJ"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1925","DOI":"10.1093\/eurheartj\/ehu207","article-title":"Towards better clinical prediction models: Seven steps for development and an ABCD for validation","volume":"35","author":"Steyerberg","year":"2014","journal-title":"Eur. Heart J."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"55","DOI":"10.7326\/M14-0697","article-title":"Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD statement","volume":"162","author":"Collins","year":"2015","journal-title":"Ann. Intern. Med."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1213\/ane.0b013e31818227da","article-title":"The risk of severe postoperative pain: Modification and validation of a clinical prediction rule","volume":"107","author":"Janssen","year":"2008","journal-title":"Anesth. Analg."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"E1","DOI":"10.1177\/0272989X12439755","article-title":"Adaptation of Clinical Prediction Models for Application in Local Settings","volume":"32","author":"Kappen","year":"2012","journal-title":"Med. Decis. Mak."}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/17\/9\/3048\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:32:09Z","timestamp":1760362329000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/17\/9\/3048"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,27]]},"references-count":59,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["ijerph17093048"],"URL":"https:\/\/doi.org\/10.3390\/ijerph17093048","relation":{},"ISSN":["1660-4601"],"issn-type":[{"value":"1660-4601","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,27]]}}}