{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T06:48:29Z","timestamp":1775112509865,"version":"3.50.1"},"reference-count":30,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T00:00:00Z","timestamp":1698278400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Introduction<\/jats:title>\n<jats:p>The diagnosis of acute respiratory distress syndrome (ARDS) includes the ratio of pressure arterial oxygen and inspired oxygen fraction (P\/F) \u2264 300, which is often adjusted in locations more than 1,000 meters above sea level (masl) due to hypobaric hypoxemia. The main objective of this study was to develop a prediction model for in-hospital mortality among patients with ARDS due to coronavirus disease 2019 (COVID-19) (C-ARDS) at 2,600 masl with easily available variables at patient admission and to compare its discrimination capacity with a second model using the P\/F adjusted for this high altitude.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>This study was an analysis of data from patients with C-ARDS treated between March 2020 and July 2021 in a university hospital located in the city of Bogot\u00e1, Colombia, at 2,600 masl. Demographic and laboratory data were extracted from electronic records. For the prediction model, univariate analyses were performed to screen variables with p &lt;0.25. Then, these variables were automatically selected with a backward stepwise approach with a significance level of 0.1. The interaction terms and fractional polynomials were also examined in the final model. Multiple imputation procedures and bootstraps were used to obtain the coefficients with the best external validation. In addition, total adjustment of the model and logistic regression diagnostics were performed. The same methodology was used to develop a second model with the P\/F adjusted for altitude. Finally, the areas under the curve (AUCs) of the receiver operating characteristic (ROC) curves of the two models were compared.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>A total of 2,210 subjects were included in the final analysis. The final model included 11 variables without interaction terms or nonlinear functions. The coefficients are presented excluding influential observations. The final equation for the model fit was g(x) = age(0.04819)+weight(0.00653)+height(-0.01856)+haemoglobin(-0.0916)+platelet count(-0.003614)+ creatinine(0.0958)+lactate dehydrogenase(0.001589)+sodium(-0.02298)+potassium(0.1574)+systolic pressure(-0.00308)+if moderate ARDS(0.628)+if severe ARDS(1.379), and the probability of in-hospital death was p (x) = e <jats:sup>g (x)<\/jats:sup>\/(1+ e <jats:sup>g (x)<\/jats:sup>). The AUC of the ROC curve was 0.7601 (95% confidence interval (CI) 0.74\u20130, 78). The second model with the adjusted P\/F presented an AUC of 0.754 (95% CI 0.73\u20130.77). No statistically significant difference was found between the AUC curves (p value = 0.6795).<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>This study presents a prediction model for patients with C-ARDS at 2,600 masl with easily available admission variables for early stratification of in-hospital mortality risk. Adjusting the P\/F for 2,600 masl did not improve the predictive capacity of the model. We do not recommend adjusting the P\/F for altitude.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0293476","type":"journal-article","created":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T17:33:52Z","timestamp":1698341632000},"page":"e0293476","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":8,"title":["Prediction model for in-hospital mortality in patients at high altitudes with ARDS due to COVID-19"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7089-018X","authenticated-orcid":true,"given":"David Rene","family":"Rodriguez Lima","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cristhian","family":"Rubio Ramos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andr\u00e9s Felipe","family":"Yepes Velasco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6728-0498","authenticated-orcid":true,"given":"Leonardo Andr\u00e9s","family":"G\u00f3mez Cortes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dar\u00edo Isa\u00edas","family":"Pinilla Rojas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u00c1ngela Mar\u00eda","family":"Pinz\u00f3n Rond\u00f3n","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u00c1ngela Mar\u00eda","family":"Ru\u00edz Sternberg","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2023,10,26]]},"reference":[{"key":"pone.0293476.ref001","article-title":"Acute Respiratory Distress Syndrome: The Berlin Definition.","year":"2012","journal-title":"JAMA [Internet]."},{"issue":"8","key":"pone.0293476.ref002","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1001\/jama.2016.0291","article-title":"Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries.","volume":"315","author":"G Bellani","year":"2016","journal-title":"JAMA"},{"issue":"6","key":"pone.0293476.ref003","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.medin.2017.08.006","article-title":"Un viaje entre la hipoxia de la gran altitud y la hipoxia del enfermo cr\u00edtico: \u00bfqu\u00e9 puede ense\u00f1arnos en la compresi\u00f3n y manejo de las enfermedades cr\u00edticas?","volume":"42","author":"ML Avellanas Chavala","year":"2018","journal-title":"Med Intensiva."},{"issue":"1","key":"pone.0293476.ref004","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1186\/s12245-022-00426-4","article-title":"Clinical characteristics and mortality associated with COVID-19 at high altitude: a cohort of 5161 patients in Bogot\u00e1, Colombia.","volume":"15","author":"DR Rodriguez Lima","year":"2022","journal-title":"Int J Emerg Med."},{"issue":"12","key":"pone.0293476.ref005","doi-asserted-by":"crossref","first-page":"1075","DOI":"10.1016\/j.recesp.2012.06.027","article-title":"Efectos de la exposici\u00f3n a grandes alturas en la circulaci\u00f3n pulmonar.","volume":"65","author":"D. 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