{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T01:59:10Z","timestamp":1793066350128,"version":"4.5.0"},"reference-count":52,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2024,12,19]],"date-time":"2024-12-19T00:00:00Z","timestamp":1734566400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Non-invasive ventilation (NIV) has emerged as a possible first-step treatment to avoid invasive intubation in pediatric intensive care units (PICUs) due to its advantages in reducing intubation-associated risks. However, the timely identification of NIV failure is crucial to prevent adverse outcomes. This study aims to identify predictors of first-attempt NIV failure in PICU patients by testing various machine learning techniques and comparing their predictive abilities. Methods: Data were sourced from the TIPNet registry, which comprised patients admitted to 23 Italian Paediatric Intensive Care Units (PICUs). We selected patients between January 2010 and January 2024 who received non-invasive ventilation (NIV) as their initial approach to respiratory support. The study aimed to develop a predictive model for NIV failure, selecting the best Machine Learning technique, including Generalized Linear Models, Random Forest, Extreme Gradient Boosting, and Neural Networks. Additionally, an ensemble approach was implemented. Model performances were measured using sensitivity, specificity, AUROC, and predictive values. Moreover, the model calibration was evaluated. Results: Out of 43,794 records, 1861 admissions met the inclusion criteria, with 678 complete cases and 97 NIV failures. The RF model demonstrated the highest AUROC and sensitivity equal to 0.83 (0.64, 0.94). Base excess, weight, age, systolic blood pressure, and fraction of inspired oxygen were identified as the most predictive features. A check for model calibration ensured the model\u2019s reliability in predicting NIV failure probabilities. Conclusions: This study identified highly sensitive models for predicting NIV failure in PICU patients, with RF as a robust option.<\/jats:p>","DOI":"10.3390\/diagnostics14242857","type":"journal-article","created":{"date-parts":[[2024,12,19]],"date-time":"2024-12-19T10:54:20Z","timestamp":1734605660000},"page":"2857","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Non-Invasive Ventilation Failure in Pediatric ICU: A Machine Learning Driven Prediction"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8612-237X","authenticated-orcid":false,"given":"Maria Vittoria","family":"Chiaruttini","sequence":"first","affiliation":[{"name":"Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University of Padova, Via Loredan 18, 35131 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1771-4686","authenticated-orcid":false,"given":"Giulia","family":"Lorenzoni","sequence":"additional","affiliation":[{"name":"Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University of Padova, Via Loredan 18, 35131 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3127-8836","authenticated-orcid":false,"given":"Marco","family":"Daverio","sequence":"additional","affiliation":[{"name":"Pediatric Intensive Care Unit, Department of Women\u2019s and Children\u2019s Health, University Hospital of Padova, Via Giustiniani 3, 35128 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5678-3006","authenticated-orcid":false,"given":"Luca","family":"Marchetto","sequence":"additional","affiliation":[{"name":"Pediatric Intensive Care Unit, Department of Women\u2019s and Children\u2019s Health, University Hospital of Padova, Via Giustiniani 3, 35128 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2924-6904","authenticated-orcid":false,"given":"Francesca","family":"Izzo","sequence":"additional","affiliation":[{"name":"Pediatric Intensive Care Unit, Buzzi Children\u2019s Hospital, Via Lodovico Castelvetro 32, 20154 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanna","family":"Chidini","sequence":"additional","affiliation":[{"name":"Department of Anesthesia Resuscitation Emergency Care, Fondazione IRCCS Ca\u2019 Granda Ospedale Maggiore Policlinico di Milano, Via Francesco Sforza 35, 20122 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1808-0665","authenticated-orcid":false,"given":"Enzo","family":"Picconi","sequence":"additional","affiliation":[{"name":"Pediatric Intensive Care Unit, Pediatric Trauma Center, Fondazione IRCCS Policlinico Universitario \u201cA. Gemelli\u201d, Largo Agostino Gemelli 8, 00136 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudio","family":"Nettuno","sequence":"additional","affiliation":[{"name":"Anaesthesia and Pediatric Resuscitation, AOU Alessandria, SS Antonio e Biagio e Cesare Arrigo Hospital, Spalto Marengo 43, 15121 Alessandria, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elisa","family":"Zanonato","sequence":"additional","affiliation":[{"name":"Pediatric Intensive Care Unit, San Bortolo Hospital, Viale Ferdinando Rodolfi 37, 36100 Vicenza, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raffaella","family":"Sagredini","sequence":"additional","affiliation":[{"name":"Anesthesia and Resuscitation Unit, IRCCS Burlo Garofolo, Via dell\u2019Istria 65, 34137 Trieste, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emanuele","family":"Rossetti","sequence":"additional","affiliation":[{"name":"Anaesthesia, Emergency and Pediatric Intensive Care Unit, Bambino Gesu\u2019 Children Hospital IRCCS, Piazza di Sant\u2019Onofrio 4, 00165 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8398-3166","authenticated-orcid":false,"given":"Maria Cristina","family":"Mondardini","sequence":"additional","affiliation":[{"name":"IRCCS AOU di Bologna, Via Giuseppe Massarenti 9, 40138 Bologna, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Corrado","family":"Cecchetti","sequence":"additional","affiliation":[{"name":"Department of Emergency Acceptance, Bambino Ges\u00f9 Children\u2019s Hospital, Piazza di Sant\u2019Onofrio 4, 00165 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pasquale","family":"Vitale","sequence":"additional","affiliation":[{"name":"Pediatric and Neonatal Intensive Care Unit, Children\u2019s Hospital Regina Margherita, Piazza Polonia 94, 10126 Turin, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicola","family":"Alaimo","sequence":"additional","affiliation":[{"name":"ARNAS G. di Cristina Hospital, 90127 Palermo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Denise","family":"Colosimo","sequence":"additional","affiliation":[{"name":"Pediatric Intensive Care Unit, Children\u2019s Hospital Meyer, IRCCS, Viale Gaetano Pieraccini 24, 50139 Florence, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0329-2896","authenticated-orcid":false,"given":"Francesco","family":"Sacco","sequence":"additional","affiliation":[{"name":"Paediatric Intensive Care Unit, Azienda Ospedaliera Universitaria Integrata di Verona, Piazzale Aristide Stefani 1, 37126 Verona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulia","family":"Genoni","sequence":"additional","affiliation":[{"name":"Neonatal and Pediatric Intensive Care Unit, Maggiore della Carit\u00e0 University Hospital, L.go Bellini, 28100 Novara, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9926-6292","authenticated-orcid":false,"given":"Daniela","family":"Perrotta","sequence":"additional","affiliation":[{"name":"A.R.C.O. Palidoro, Bambino Ges\u00f9 Children\u2019s Hospital, Piazza di Sant\u2019Onofrio 4, 00165 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Camilla","family":"Micalizzi","sequence":"additional","affiliation":[{"name":"Pediatric and Neonatal Intensive Care Unit, IRCCS G Gaslini, Via Gerolamo Gaslini 5, 16147 Genoa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silvia","family":"Moggia","sequence":"additional","affiliation":[{"name":"Pediatric Intensive Care Unit, AORN Santobono-Pausilipon, Via della Croce Rossa 8, 80122 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giosu\u00e8","family":"Chisari","sequence":"additional","affiliation":[{"name":"UOSD Pediatric Resuscitation, ARNAS Garibaldi PO Nesima, Piazza Santa Maria di Ges\u00f9 5, 95124 Catania, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Immacolata","family":"Rulli","sequence":"additional","affiliation":[{"name":"UOC Neonatal Pathology and TIN, AOU G MARTINO, Via Consolare Valeria 1, 98124 Messina, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6389-3692","authenticated-orcid":false,"given":"Andrea","family":"Wolfler","sequence":"additional","affiliation":[{"name":"Department of Emergency, Division of Anesthesia IRCCS G Gaslini, Via Gerolamo Gaslini 5, 16147 Genoa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5654-0506","authenticated-orcid":false,"given":"Angela","family":"Amigoni","sequence":"additional","affiliation":[{"name":"Pediatric Intensive Care Unit, Department of Women\u2019s and Children\u2019s Health, University Hospital of Padova, Via Giustiniani 3, 35128 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7906-0580","authenticated-orcid":false,"given":"Dario","family":"Gregori","sequence":"additional","affiliation":[{"name":"Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University of Padova, Via Loredan 18, 35131 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.arcped.2016.10.012","article-title":"Int\u00e9r\u00eat de la ventilation non invasive en r\u00e9animation p\u00e9diatrique: Doit-on esp\u00e9rer un autre niveau de preuve ?","volume":"24","author":"Mortamet","year":"2017","journal-title":"Arch. De P\u00e9diatrie"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.1007\/s00134-012-2566-4","article-title":"Increase in use of non-invasive ventilation for infants with severe bronchiolitis is associated with decline in intubation rates over a decade","volume":"38","author":"Ganu","year":"2012","journal-title":"Intensive Care Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"278","DOI":"10.18295\/squmj.2018.18.03.003","article-title":"Noninvasive Ventilation and High-Flow Nasal Cannulae Therapy for Children with Acute Respiratory Failure: An overview","volume":"18","year":"2018","journal-title":"Sultan Qaboos Univ. Med. J."},{"key":"ref_4","first-page":"726","article-title":"Pain among mechanically ventilated patients in critical care units","volume":"19","author":"Abdalrahim","year":"2014","journal-title":"J. Res. Med. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1001\/jama.2020.9524","article-title":"Association of Noninvasive Oxygenation Strategies With All-Cause Mortality in Adults With Acute Hypoxemic Respiratory Failure: A Systematic Review and Meta-analysis","volume":"324","author":"Ferreyro","year":"2020","journal-title":"JAMA"},{"key":"ref_6","first-page":"71","article-title":"Ventilator-associated pneumonia in PICU\u2014How are we doing?","volume":"38","author":"Applegate","year":"2022","journal-title":"S. Afr. J. Crit. Care"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"251","DOI":"10.2174\/1574887115666200603151838","article-title":"Indications for Non-Invasive Ventilation in Respiratory Failure","volume":"15","author":"Navarra","year":"2021","journal-title":"Rev. Recent Clin. Trials"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1055\/s-0041-1731433","article-title":"Predictors of Failure of Noninvasive Ventilation in Critically Ill Children","volume":"12","author":"Baker","year":"2023","journal-title":"J. Pediatr. Intensive Care"},{"key":"ref_9","first-page":"1159","article-title":"A multicentered study on efficiency of noninvasive ventilation procedures (SAFE-NIV)","volume":"51","author":"Ongun","year":"2021","journal-title":"Turk. J. Med. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"e1076","DOI":"10.1097\/CCE.0000000000001076","article-title":"First-Line Respiratory Support for Children With Hematologic Malignancy and Acute Respiratory Failure","volume":"6","author":"Asif","year":"2024","journal-title":"Crit. Care Explor."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1602426","DOI":"10.1183\/13993003.02426-2016","article-title":"Official ERS\/ATS clinical practice guidelines: Noninvasive ventilation for acute respiratory failure","volume":"50","author":"Rochwerg","year":"2017","journal-title":"Eur. Respir. J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1007\/s00134-015-3693-5","article-title":"Failure of high-flow nasal cannula therapy may delay intubation and increase mortality","volume":"41","author":"Kang","year":"2015","journal-title":"Intensive Care Med."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"S135","DOI":"10.1097\/PCC.0000000000003165","article-title":"Noninvasive Respiratory Support for Pediatric Acute Respiratory Distress Syndrome: From the Second Pediatric Acute Lung Injury Consensus Conference","volume":"24","author":"Carroll","year":"2023","journal-title":"Pediatr. Crit. Care Med."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e140847","DOI":"10.5812\/aapm-140847","article-title":"Predictors of Non-invasive Ventilation Failure and Associated Factors Among the COVID-19 Patients Admitted to Intensive Care Unit","volume":"13","author":"Varpaei","year":"2023","journal-title":"Anesth. Pain Med."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"e20180053","DOI":"10.36416\/1806-3756\/e20180053","article-title":"Noninvasive ventilation in a pediatric ICU: Factors associated with failure","volume":"46","author":"Cohen","year":"2020","journal-title":"J. Bras. Pneumol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Rowan, C.M., Fitzgerald, J.C., Agulnik, A., Zinter, M.S., Sharron, M.P., Slaven, J.E., Kreml, E.M., Bajwa, R.P., Mahadeo, K.M., and Moffet, J. (2021). Risk Factors for Noninvasive Ventilation Failure in Children Post-Hematopoietic Cell Transplant. Front. Oncol., 11.","DOI":"10.3389\/fonc.2021.653607"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.24953\/turkjped.2021.06.009","article-title":"Predictive factors of high-flow nasal cannula oxygen therapy failure in children with respiratory distress treated in a Pediatric Emergency Department","volume":"63","author":"Birbilen","year":"2021","journal-title":"Turk. J. Pediatr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.jcrc.2016.11.038","article-title":"Factors predicting failure of noninvasive ventilation assist for preventing reintubation among medical critically ill patients","volume":"38","author":"Thomrongpairoj","year":"2017","journal-title":"J. Crit. Care"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Corr\u00eaa, T.D., Sanches, P.R., De Morais, L.C., Scarin, F.C., Silva, E., and Barbas, C.S.V. (2015). Performance of noninvasive ventilation in acute respiratory failure in critically ill patients: A prospective, observational, cohort study. BMC Pulm. Med., 15.","DOI":"10.1186\/s12890-015-0139-3"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1307","DOI":"10.4187\/respcare.05481","article-title":"Risk Factors for Noninvasive Ventilation Failure in Critically Ill Subjects With Confirmed Influenza Infection","volume":"62","author":"Ferri","year":"2017","journal-title":"Respir. Care."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1186\/s12873-020-00376-1","article-title":"Early detection of non-invasive ventilation failure among acute respiratory failure patients in the emergency department","volume":"20","author":"Liengswangwong","year":"2020","journal-title":"BMC Emerg. Med."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1186\/s12890-021-01421-w","article-title":"A scoring system derived from electronic health records to identify patients at high risk for noninvasive ventilation failure","volume":"21","author":"Stefan","year":"2021","journal-title":"BMC Pulm. Med."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Feng, X., Pan, S., Yan, M., Shen, Y., Liu, X., Cai, G., and Ning, G. (2021). Dynamic prediction of late noninvasive ventilation failure in intensive care unit using a time adaptive machine model. Comput. Methods Programs Biomed., 208.","DOI":"10.1016\/j.cmpb.2021.106290"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e31760","DOI":"10.2196\/31760","article-title":"Predicting High Flow Nasal Cannula Failure in an Intensive Care Unit Using a Recurrent Neural Network With Transfer Learning and Input Data Perseveration: Retrospective Analysis","volume":"10","author":"Pappy","year":"2022","journal-title":"JMIR Med. Inform."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Bose, S.N., Defante, A., Greenstein, J.L., Haddad, G.G., Ryu, J., and Winslow, R.L. (2023). A data-driven model for early prediction of need for invasive mechanical ventilation in pediatric intensive care unit patients. Ajagbe SA, curatore. PLoS ONE, 18.","DOI":"10.1371\/journal.pone.0289763"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"333","DOI":"10.5935\/0103-507X.20190045","article-title":"Noninvasive ventilation as the first choice of ventilatory support in children","volume":"31","author":"Lins","year":"2019","journal-title":"Rev. Bras. Ter. Intensiv."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s10462-024-10759-6","article-title":"A survey on imbalanced learning: Latest research, applications and future directions","volume":"57","author":"Chen","year":"2024","journal-title":"Artif. Intell. Rev."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/j.jbi.2008.08.010","article-title":"Research electronic data capture (REDCap)\u2014A metadata-driven methodology and workflow process for providing translational research informatics support","volume":"42","author":"Harris","year":"2009","journal-title":"J. Biomed. Inform."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1007\/s10916-009-9363-9","article-title":"Using Data Mining Techniques in Monitoring Diabetes Care. The Simpler the Better?","volume":"35","author":"Gregori","year":"2011","journal-title":"J. Med. Syst."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Chen, T., and Guestrin, C. (2016, January 13\u201317). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA. Available online: https:\/\/dl.acm.org\/doi\/10.1145\/2939672.2939785.","DOI":"10.1145\/2939672.2939785"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhou, Z.-H. (2012). Ensemble Methods: Foundations and Algorithms, Taylor & Francis.","DOI":"10.1201\/b12207"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Bishop, C.M. (1996). Neural Networks for Pattern Recognition, Clarendon Pr.","DOI":"10.1201\/9781420050646.ptb6"},{"key":"ref_33","unstructured":"Polley, E. (2024, June 09). SuperLearner: Super Learner Prediction. Available online: https:\/\/CRAN.R-project.org\/package=SuperLearner."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/j.ress.2015.05.018","article-title":"Variable importance analysis: A comprehensive review","volume":"142","author":"Wei","year":"2015","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_35","unstructured":"Kuhn, M., and Johnson, K. (2016). Applied predictive modeling. Corrected at 5th Printing, Springer."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1002\/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3","article-title":"Index for rating diagnostic tests","volume":"3","author":"Youden","year":"1950","journal-title":"Cancer"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3711","DOI":"10.1093\/bioinformatics\/bty373","article-title":"The revival of the Gini importance?","volume":"34","author":"Nembrini","year":"2018","journal-title":"Bioinformatics"},{"key":"ref_38","unstructured":"Williamson, B.D. (2024, June 09). vimp: Perform Inference on Algorithm-Agnostic Variable Importance. Available online: https:\/\/CRAN.R-project.org\/package=vimp."},{"key":"ref_39","unstructured":"R Core Team (2013). R: A Language and Environment for Statistical Computing, Foundation for Statistical Computing."},{"key":"ref_40","unstructured":"Breiman, L., and Liaw, A. (2024, June 09). randomForest: Breiman and Cutler\u2019s Random Forests for Classification and Regression. Available online: https:\/\/CRAN.R-project.org\/package=randomForest."},{"key":"ref_41","unstructured":"Chen, T. (2024, June 09). xgboost: Extreme Gradient Boosting. Available online: https:\/\/CRAN.R-project.org\/package=xgboost."},{"key":"ref_42","unstructured":"Ripley, B. (2024, June 09). nnet: Feed-Forward Neural Networks and Multinomial Log-Linear Models. Available online: https:\/\/CRAN.R-project.org\/package=nnet."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v028.i05","article-title":"Building Predictive Models in R Using the caret Package","volume":"28","author":"Kuhn","year":"2008","journal-title":"J. Stat. Soft"},{"key":"ref_44","unstructured":"Rhodes, S. (2024, June 09). Pmcalibration. Available online: https:\/\/CRAN.R-project.org\/package=pmcalibration."},{"key":"ref_45","unstructured":"Silva Filho, T.M., and Kull, M. (2024, June 09). Betacal: Beta Calibration. Available online: https:\/\/CRAN.R-project.org\/package=DMwR2."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"e319","DOI":"10.1542\/hpeds.2023-007259","article-title":"How to Interact With Interactions: What Clinicians Should Know About Statistical Interactions","volume":"13","author":"Cotter","year":"2023","journal-title":"Hosp. Pediatr."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2938","DOI":"10.1212\/WNL.98.18_supplement.2938","article-title":"The Use of Blood Carbonate (HCO3\u2212) and Base-Excess (SBE) in Predicting Non-Invasive Ventilation (NIV) Adaptation (P1-1.Virtual)","volume":"98","author":"Manera","year":"2022","journal-title":"Neurology"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"111","DOI":"10.3233\/PIC-13059","article-title":"SpO2\/FiO2 as a predictor of non-invasive ventilation failure in children with hypoxemic respiratory insufficiency","volume":"02","author":"Palanca","year":"2015","journal-title":"J. Pediatr. Intensive Care"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1007\/s00134-022-06748-4","article-title":"Understanding base excess (BE): Merits and pitfalls","volume":"48","author":"Langer","year":"2022","journal-title":"Intensive Care Med."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1183\/09031936.00071007","article-title":"Haemodynamically unstable pulmonary embolism in the RIETE Registry: Systolic blood pressure or shock index?","volume":"30","author":"Otero","year":"2007","journal-title":"Eur. Respir. J."},{"key":"ref_51","unstructured":"Harrell, F. (2024, June 09). Classification vs. Prediction. Statistical Thinking, Available online: https:\/\/www.fharrell.com\/post\/classification\/index.html."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"101288","DOI":"10.1016\/j.eclinm.2022.101288","article-title":"Development of a clinical prediction model for perinatal deaths in low resource settings","volume":"44","author":"Housseine","year":"2022","journal-title":"eClinicalMedicine"}],"container-title":["Diagnostics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4418\/14\/24\/2857\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:55:46Z","timestamp":1760115346000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4418\/14\/24\/2857"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,19]]},"references-count":52,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["diagnostics14242857"],"URL":"https:\/\/doi.org\/10.3390\/diagnostics14242857","relation":{},"ISSN":["2075-4418"],"issn-type":[{"value":"2075-4418","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,19]]}}}