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Systematic Reviews
©The Author(s) 2025.
World J Meta-Anal. Dec 18, 2025; 13(4): 112603
Published online Dec 18, 2025. doi: 10.13105/wjma.v13.i4.112603
Table 2 Characteristics of included studies
Ref.
Period of data collection
Location
Study type
Model
Validation
Sample size
Chi et al[38], 20231 July 2015 to 30 November 2015Tainan, TaiwanRetrospective cross-sectionalMultivariate binary logistic regression with significant coefficient transformed to scores by inverse odds ratioExternal validation (separate region and time)701
Yang et al[37], 2023August 15, 2019 and September 30, 2019Dhaka, BangladeshCross-sectionalCART model used on univariate and multivariate logistic regression modelsInternal validation via split-sample with random assignment (80% training sample, 20% hold-out sample)1090
Gayathri et al[10], 2023Model: October 2019; Validation: September 2019 to January 2021Chennai, IndiaProspective cohortBinary logistic regression to develop prediction severity model with forward stepwise method in 3 steps to identify 3 significant variables and Nagelkerke square to quantify influence of variablesTemporal validation on 2021 data (n = 312)312
McBride et al[11], 2022June 2019 to June 2021Ho Chi Minh city, VietnamProspective observational cohortmSOFA score and delta excluding bilirubin calculated from day 0 and 2. Brier score rescaled from 0 to 1Internal validation via bootstrap procedure with 500 resamples with replacement124
Bhaskar et al[12], 2022January 2016 to December 2020Manipal, IndiaProspective case cohortLogistic regression model of significant variablesNo validation303
Srisuphanunt et al[23], 20222017 to 2019Bangkok, ThailandRetrospective cohortPotential predictor tested for trend with nonparametric methodInternal validation (method not mentioned)302
Sachdev et al[13], 2021July 1, 2016 to December 31, 2019New Deli, IndiaProspective cohortMultivariate logistic regression model to identify independent risk factors, stepwise entry of new terms into modelNo validation78
Marois et al[24], 2021January 1, 2017 to July 31, 2017New CaledoniaRetrospective cohortPredictive model built using multiple logistic regression and descending stepwise analysisInternal validation via k-fold cross-validation (k = 10)383
Devarbhavi et al[25], 2020January 2014 to December 2017Bangalore, IndiaRetrospective cohortMELD score, arterial pH, lactate used to generate ROC with C-statisticsNo validation36
Tangnararatchakit et al[26], 20202004 to 2018Bangkok, ThailandRetrospective cohortDaily Dengue severity score created in Phase I (n = 191)Temporal validation on Phase II (n = 51)242
Lee et al[27], 2018Kaohsiung Chang Gung Memorial Hospital: 2022 to 2015; Kaohsiung Medical University Hospital[2]: 2009 to 2013Kaohsiung, TaiwanRetrospective cohortMultivariate logistic regression model and assigning points by dividing its regression coefficient by smallest coefficient in model (rounded to nearest whole number)No validation1068
Phakhounthong et al[28], 2018October 12, 2009 to October 12, 2010Siem Reap, CambodiaRetrospective cohortCART tree constructed with J48 algorithm to generate decision treeInternal validation via 10-fold cross-validation by Weka sed to estimate out-of-sample accuracy (split data into 10, 9 for training, 1 for testing). Multiple rounds of cross-validation performed using different partitions198
Park et al[14], 2018Queen Sirikit National Institute of Child Health[3]: 1994 to 1997, 1999 to 2002, 2004 to 2007; Kamphaeng Phet Provincial Hospital[4]: 1994 to 1997Bangkok, Thailand; Nai Mueang, ThailandProspective cohortSEM using data from n = 257 with complete dataInternal validation via multiple imputation via Markov-chain Monte Carlo method to create 50 imputed datasets without missing data on n = 1244 to assess Sn744
Md-Sani et al[29], 2018September 8, 2022 to November 18, 2022Kuala Lumpur, MalaysiaRetrospective cohortVariable selection via 5-fold cross-validated Lasso regression used to build logistic regression modelInternal validation via cross-validation199
Suwarto et al[30], 2018January 2011 to March 2016Jarkarta, IndonesiaRetrospective cohortDengue Score (Suwarto et al[18], 2016)External validation207
Hsieh et al[15], 2017July 1, 2015 to December 31, 2015Tainan, TaiwanProspective cohortUnivariate and multivariate with binary variables Cox model to identify predictive factors for mortality with cut-off values selected using Youden indexNo validation625
Huang et al[35], 2017September 1, 2015 to December 31, 2015Tainan, TaiwanCase controlUnivariate analysis and Multivariate logistic regression analysis to investigate independent predictors for 30-day mortality. Novel prediction score developed by assigning a score of 1 to each independent variableInternal validation via bootstrapping method by generating 1000 hypothetical study population using random sampling from study sample2358
Fernández et al[31], 20172009 to 2010Tegucigalpa and San Pedro Sula, HondurasRetrospective cohortUnivariable analysis and multivariable logistic regression analysis using forward stepwise selection to construct a predictive model for severe dengueInternal validation via bootstrap technique (sampling with replacement using 320 individuals sampling 1000 times)320
Nguyen et al[16], 2017October 1, 2010 to December 31, 2013Southern VietnamProspective cohortLogistic regression to develop prognostic modelInternal validation via "leave-one-site-out cross validation" (develop algorithm on all but 1 study site and validate using that study site) and Temporal validation2060
Djossou et al[17], 2016March 17, 2013 to September 30, 2013Cayenne, French GuianaProspective cohortFinal model include variables with significant association in single covariable analysisInternal validation via bootstrapping 1000 replications806
Lee et al[32], 2016Kaohsiung Chang Gung Memorial Hospital: July 1, 2002 to May 31, 2015; Kaohsiung Medical University Hospital[6]: 2009 to 2011Kaohsiung, TaiwanRetrospective cohortSignificant variables in univariate analysis entered into multivariate logistic regression and point assignment calculated by dividing regression coefficient by smallest coefficient in modelTemporal validation (model set before 31 Jul 2014 n = 1063, validation set after Aug 1 2014 n = 190)1253
Suwarto et al[18], 2016March 2010 to August 2015Jarkarta, IndonesiaProspective cohortVariables entered into multiple regression analysis using backward selection algorithm to estimate coefficient and independent diagnostic predictors and converted into simplified risk score systemValidation published separately[30]172
Lam et al[19], 20152003 to 2009Ho Chi Minh City, VietnamProspective cohort Univariate and multivariate analysis via logistic regression and model simplified using stepwise backwards model selection based on Akaike Information CriterionTemporal validation (model from n = 939 enrolled before 2009 and validated on 268 enrolled during 2009) and internal validation via repeated 10-fold cross-validation1207
Pang et al[36], 2014January 1, 2004 to December 31, 2008SingaporeCase controlUnivariate and multivariate conditional logistic regression performed to assess associationNo validation135
Pongpan et al[33], 20142007 to 2010Phrae, Thailand; Lamphun, Thailand; Chiang Mai, ThailandRetrospective cohortScoring system (Pongpan et al[34], 2013)External validation400
Pongpan et al[34], 20132007 to 2010Nakorn Sawan, Thailand; Kampaeng Phet, Thailand; Uttaradit, ThailandRetrospective cohortScoring system analysed by multivariable ordinal logistic regression and assigned item scores derived from coefficient transformationValidation published separately[33]777
Leo et al[20], 2013January 2010 to September 2012SingaporeProspective cohortVariables selected from World Health Organization[7] Warning SignsExternal validation499
Diaz-Quijano et al[21], 2010Not reportedBucaramanga, ColombiaProspective cohortRisk score based on independent predictors and risk group formedNo validation729
Potts et al[22], 2010Queen Sirikit National Institute of Child Health: 1994 to 1997, 1999 to 2002, 2004 to 2007; Kamphaeng Phet Provincial Hospital: 1994 to 1997Bangkok, Thailand; Kamphaeng Phet, ThailandProspective cohortCART analysis with age, gender, and clinical laboratory data to establish a diagnostic decision treeInternal validation via k-fold cross validation method (k = 5) of each tree582


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