Heart-Brain 346-7 Score: the development and validation of a simple mortality prediction score for carbon monoxide poisoning utilizing deep learning

References

• Rose JJ, Wang L, Xu Q, et al. Carbon monoxide poisoning: pathogenesis, management, and future directions of therapy. Am J Respir Crit Care Med. 2017;195(5):596–606. doi: 10.1164/rccm.201606-1275CI.
   PubMed Web of Science ®Google Scholar
• Hampson NB, Piantadosi CA, Thom SR, et al. Practice recommendations in the diagnosis, management, and prevention of carbon monoxide poisoning. Am J Respir Crit Care Med. 2012;186(11):1095–1101. doi: 10.1164/rccm.201207-1284CI.
   PubMed Web of Science ®Google Scholar
• Hampson NB. U.S. Mortality due to carbon monoxide poisoning, 1999–2014. Accidental and intentional deaths. Ann Am Thorac Soc. 2016;13:1768–1774.
   PubMed Web of Science ®Google Scholar
• Rose JJ, Nouraie M, Gauthier MC, et al. Clinical outcomes and mortality impact of hyperbaric oxygen therapy in patients with carbon monoxide poisoning. Crit Care Med. 2018;46(7):e649–e655. doi: 10.1097/CCM.0000000000003135.
   PubMed Web of Science ®Google Scholar
• Henry CR, Satran D, Lindgren B, et al. Myocardial injury and long-term mortality following moderate to severe carbon monoxide poisoning. JAMA. 2006;295(4):398–402. doi: 10.1001/jama.295.4.398.
   PubMed Web of Science ®Google Scholar
• Hampson NB, Rudd RA, Hauff NM. Increased long-term mortality among survivors of acute carbon monoxide poisoning. Crit Care Med. 2009;37(6):1941–1947. doi: 10.1097/CCM.0b013e3181a0064f.
   PubMed Web of Science ®Google Scholar
• Kao H-K, Lien T-C, Kou YR, et al. Assessment of myocardial injury in the emergency department independently predicts the short-term poor outcome in patients with severe carbon monoxide poisoning receiving mechanical ventilation and hyperbaric oxygen therapy. Pulm Pharmacol Ther. 2009;22(6):473–477. doi: 10.1016/j.pupt.2009.04.006.
   PubMed Web of Science ®Google Scholar
• Amirabadizadeh A, Nakhaee S, Jahani F, et al. Prognostic indicators in critically ill poisoned patients: development of a risk-prediction nomogram. Drug Metab Pers Ther. 2020;35(4):20200108.
   Google Scholar
• Huang C-C, Chung M-H, Weng S-F, et al. Long-term prognosis of patients with carbon monoxide poisoning: a nationwide cohort study. PLOS One. 2014;9(8):e105503. doi: 10.1371/journal.pone.0105503.
   PubMed Web of Science ®Google Scholar
• Garg J, Krishnamoorthy P, Palaniswamy C, et al. Cardiovascular abnormalities in carbon monoxide poisoning. Am J Ther. 2018;25(3):e339–e348. doi: 10.1097/MJT.0000000000000016.
   PubMed Web of Science ®Google Scholar
• Weaver LK, Hopkins RO, Churchill SK, et al. Neurological outcomes 6 years after acute carbon monoxide poisoning. Undersea Hyperb Med. 2008;35:241–323.
   PubMedGoogle Scholar
• Hopkins RO, Weaver LK. Cognitive outcomes 6 years after acute carbon monoxide poisoning. Undersea Hyperb Med. 2008;35:258.
   Google Scholar
• Schwarz ES, Kopec KT, Wiegand TJ, et al. Should we be using the poisoning severity score? J Med Toxicol. 2017;13(2):135–145. doi: 10.1007/s13181-017-0609-5.
   PubMed Web of Science ®Google Scholar
• Vincent JL, de Mendonça A, Cantraine F, et al. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on “sepsis-related problems” of the european society of intensive care medicine. Crit Care Med. 1998;26(11):1793–1800. doi: 10.1097/00003246-199811000-00016.
   PubMed Web of Science ®Google Scholar
• Knaus WA, Draper EA, Wagner DP, et al. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818–829. doi: 10.1097/00003246-198510000-00009.
   PubMed Web of Science ®Google Scholar
• Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–383. doi: 10.1016/0021-9681(87)90171-8.
   PubMedGoogle Scholar
• Yount RJ, Vries JK, Councill CD. The medical archival system: an information retrieval system based on distributed parallel processing. Inf Process Manag. 1991;27(4):379–389. doi: 10.1016/0306-4573(91)90091-Y.
   Web of Science ®Google Scholar
• Cheng D, DuMontier C, Yildirim C, et al. Updating and validating the U.S. Veterans affairs frailty index: transitioning from ICD-9 to ICD-10. J Gerontol A Biol Sci Med Sci. 2021;76(7):1318–1325. doi: 10.1093/gerona/glab071.
   PubMed Web of Science ®Google Scholar
• Hernandez-Ibarburu G, Perez-Rey D, Alonso-Oset E, et al. ICD-10-CM extension with ICD-9 diagnosis codes to support integrated access to clinical legacy data. Int J Med Inform. 2019;129:189–197. doi: 10.1016/j.ijmedinf.2019.06.010.
   PubMed Web of Science ®Google Scholar
• Ohnuma T, Raghunathan K, Fuller M, et al. Trends in comorbidities and complications using ICD-9 and ICD-10 in total hip and knee arthroplasties. J Bone Joint Surg Am. 2021;103(8):696–704. doi: 10.2106/JBJS.20.01152.
   PubMed Web of Science ®Google Scholar
• Gupta D, Saul M, Gilbertson J. Evaluation of a deidentification (De-Id) software engine to share pathology reports and clinical documents for research. Am J Clin Pathol. 2004;121(2):176–186. doi: 10.1309/E6K33GBPE5C27FYU.
   PubMed Web of Science ®Google Scholar
• Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43(11):1130–1139. doi: 10.1097/01.mlr.0000182534.19832.83.
   PubMed Web of Science ®Google Scholar
• Akaike H. A new look at the statistical model identification. IEEE Trans. Automat. Contr. 1974;19(6):716–723. doi: 10.1109/TAC.1974.1100705.
   Web of Science ®Google Scholar
• Puhr R, Heinze G, Nold M, et al. Firth’s logistic regression with rare events: accurate effect estimates and predictions? Stat Med. 2017;36:2302–2317.
   PubMed Web of Science ®Google Scholar
• Moons KGM, Altman DG, Reitsma JB, et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1–73. doi: 10.7326/M14-0698.
   PubMed Web of Science ®Google Scholar
• Charlson ME, Carrozzino D, Guidi J, et al. Charlson comorbidity index: a critical review of clinimetric properties. Psychother Psychosom. 2022;91(1):8–35. doi: 10.1159/000521288.
   PubMed Web of Science ®Google Scholar
• Bannay A, Chaignot C, Blotière P-O, et al. The best use of the charlson comorbidity index with electronic health care database to predict mortality. Med Care. 2016;54(2):188–194. doi: 10.1097/MLR.0000000000000471.
   PubMed Web of Science ®Google Scholar
• DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44(3):837–845.
   PubMed Web of Science ®Google Scholar
• Nahm FS. Receiver operating characteristic curve: overview and practical use for clinicians. Korean J Anesthesiol. 2022;75(1):25–36. doi: 10.4097/kja.21209.
   PubMed Web of Science ®Google Scholar
• Vazquez-Zapien GJ, Mata-Miranda MM, Garibay-Gonzalez F, et al. Artificial intelligence model validation before its application in clinical diagnosis assistance. World J Gastroenterol. 2022;28(5):602–604. doi: 10.3748/wjg.v28.i5.602.
   PubMed Web of Science ®Google Scholar
• Domalpally A, Channa R. Real-world validation of artificial intelligence algorithms for ophthalmic imaging. Lancet Digit Health. 2021;3(8):e463–e464. doi: 10.1016/S2589-7500(21)00140-0.
   PubMedGoogle Scholar
• Persson HE, Sjöberg GK, Haines JA, et al. Poisoning severity score. Grading of acute poisoning. J Toxicol Clin Toxicol. 1998;36(3):205–213. doi: 10.3109/15563659809028940.
   PubMed Web of Science ®Google Scholar
• Vincent JL, Moreno R, Takala J, et al. The SOFA (sepsis-related organ failure assessment) score to describe organ dysfunction/failure. On behalf of the working group on sepsis-related problems of the European society of intensive care medicine. Intensive Care Med. 1996;22(7):707–710. doi: 10.1007/BF01709751.
   PubMed Web of Science ®Google Scholar
• Brusselaers N, Lagergren J. The Charlson comorbidity index in registry-based research. Methods Inf Med. 2017;56(5):401–406. doi: 10.3414/ME17-01-0051.
   PubMed Web of Science ®Google Scholar
• Dzeshka MS, Lane DA, Lip GYH. Stroke and bleeding risk in atrial fibrillation: navigating the alphabet soup of risk-score acronyms (CHADS2, CHA2 DS2 -VASc, R2 CHADS2, HAS-BLED, ATRIA, and more). Clin Cardiol. 2014;37(10):634–644. doi: 10.1002/clc.22294.
   PubMed Web of Science ®Google Scholar
• Proietti M, Farcomeni A, Romiti GF, et al. Association between clinical risk scores and mortality in atrial fibrillation: systematic review and network meta-regression of 669,000 patients. Eur J Prev Cardiol. 2020;27(6):633–644. doi: 10.1177/2047487318817662.
   PubMed Web of Science ®Google Scholar
• Liu C, Yin P, Chen R, et al. Ambient carbon monoxide and cardiovascular mortality: a nationwide time-series analysis in 272 cities in China. Lancet Planet Health. 2018;2(1):e12–e18. doi: 10.1016/S2542-5196(17)30181-X.
   PubMedGoogle Scholar
• Sert ET, Kokulu K, Mutlu H. Clinical predictors of delayed neurological sequelae in charcoal-burning carbon monoxide poisoning. Am J Emerg Med. 2021;48:12–17. doi: 10.1016/j.ajem.2021.04.001.
   PubMed Web of Science ®Google Scholar
• Mattiuzzi C, Lippi G. Worldwide epidemiology of carbon monoxide poisoning. Hum Exp Toxicol. 2020;39(4):387–392. doi: 10.1177/0960327119891214.
   PubMed Web of Science ®Google Scholar
• Costantino S, Paneni F, Cosentino F. Ageing, metabolism and cardiovascular disease. J Physiol. 2016;594(8):2061–2073. doi: 10.1113/JP270538.
   PubMed Web of Science ®Google Scholar
• Novy J, Sander JW. Age, comorbidity, frailty in observational and analytic studies of neurological diseases. Front Neurol Neurosci. 2016;39:71–80.
   PubMedGoogle Scholar
• Simonsen C, Thorsteinsson K, Mortensen RN, et al. Carbon monoxide poisoning in Denmark with focus on mortality and factors contributing to mortality. PLOS One. 2019;14(1):e0210767. doi: 10.1371/journal.pone.0210767.
   PubMed Web of Science ®Google Scholar