Exploiting Electronic Data to Advance Knowledge and Management of Severe Infections

Pastorino R, De Vito C, Migliara G, Glocker K, Binenbaum I, Ricciardi W, Boccia S. Benefits and challenges of big data in healthcare: an overview of the European initiatives. Eur J Public Health. 2019;29(Supplement_3):23–7.

Article  PubMed  PubMed Central  Google Scholar 

Delahanty RJ, Alvarez J, Flynn LM, Sherwin RL, Jones SS. Development and evaluation of a machine learning model for the early identification of patients at risk for sepsis. Ann Emerg Med. 2019;73(4):334–44.

Article  PubMed  Google Scholar 

García-Gallo JE, Fonseca-Ruiz NJ, Celi LA, Duitama-Muñoz JF. A machine learning-based model for 1-year mortality prediction in patients admitted to an intensive care unit with a diagnosis of sepsis. Med Intensiva. 2020;44(3):160–70.

Article  PubMed  Google Scholar 

Laupland KB, Davies HD, Church DL, Louie TJ, Dool JS, Zygun DA, Doig CJ. Bloodstream infection-associated sepsis and septic shock in critically ill adults: a population-based study. Infection. 2004;32(2):59–64.

Article  CAS  PubMed  Google Scholar 

Laupland KB, Paiva JA, Timsit JF. Focus on severe infections. Intensive Care Med. 2017;43(7):1033–6.

Article  PubMed  Google Scholar 

Shankar-Hari M, Phillips GS, Levy ML, Seymour CW, Liu VX, Deutschman CS, Angus DC, Rubenfeld GD, Singer M. Developing a new definition and assessing new clinical criteria for septic shock: for the third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016;315(8):775–87.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Leal J, Gregson DB, Ross T, Flemons WW, Church DL, Laupland KB. Development of a novel electronic surveillance system for monitoring of bloodstream infections. Infect Control Hosp Epidemiol. 2010;31(7):740–7.

Article  PubMed  Google Scholar 

Laupland KB, Leal JR. Defining microbial invasion of the bloodstream: a structured review. Infect Dis (London, England). 2020;52(6):391–5.

CAS  Google Scholar 

Zhu NJ, Rawson TM, Mookerjee S, Price JR, Davies F, Otter J, Aylin P, Hope R, Gilchrist M, Shersing Y, et al. Changing patterns of bloodstream infections in the community and acute care across 2 coronavirus disease 2019 epidemic waves: a retrospective analysis using data linkage. Clin Infect Dis Offic Publ Infect Dis Soc Am. 2022;75(1):e1082–91.

Article  Google Scholar 

Seymour CW, Kennedy JN, Wang S, Chang CH, Elliott CF, Xu Z, Berry S, Clermont G, Cooper G, Gomez H, et al. Derivation, validation, and potential treatment implications of novel clinical phenotypes for sepsis. JAMA. 2019;321(20):2003–17.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Streefkerk HRA, Verkooijen RP, Bramer WM, Verbrugh HA. Electronically assisted surveillance systems of healthcare-associated infections: a systematic review. Euro surveillance: bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin. 2020;25(2).

Jones BE, Sarvet AL, Ying J, Jin R, Nevers MR, Stern SE, Ocho A, McKenna C, McLean LE, Christensen MA, et al. Incidence and outcomes of non-ventilator-associated hospital-acquired pneumonia in 284 US hospitals using electronic surveillance criteria. JAMA Netw Open. 2023;6(5): e2314185.

Article  PubMed  PubMed Central  Google Scholar 

Schaumburg T, Köhler N, Breitenstein Y, Kolbe-Busch S, Hasenclever D, Chaberny IF. ICU infection surveillance can be based on electronic routine data: results of a case study. BMC Infect Dis. 2023;23(1):126.

Article  PubMed  PubMed Central  Google Scholar 

•• Gerver SM, Mihalkova M, Bion JF, Wilson APR, Chudasama D, Johnson AP, Hope R. Surveillance of bloodstream infections in intensive care units in England, May 2016-April 2017: epidemiology and ecology. J Hosp Infect. 2020;106(1):1–9. A large study from England that demonstrates the value of objective electronic information for infection surveillance in ICUs.

Yan MY, Gustad LT, Nytrø Ø. Sepsis prediction, early detection, and identification using clinical text for machine learning: a systematic review. J Am Med Inform Assoc JAMIA. 2022;29(3):559–75.

Article  PubMed  Google Scholar 

Goh KH, Wang L, Yeow AYK, Poh H, Li K, Yeow JJL, Tan GYH. Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare. Nat Commun. 2021;12(1):711.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Liu R, Greenstein JL, Sarma SV, Winslow RL. Natural language processing of clinical notes for improved early prediction of septic shock in the ICU. Ann Int Conf IEEE Eng Med Biol Soc IEEE Eng Med Biol Soc Ann Int Conf. 2019;2019:6103–8.

Google Scholar 

Amrollahi F, Shashikumar SP, Razmi F, Nemati S. Contextual embeddings from clinical notes improves prediction of sepsis. AMIA Ann Symp Proc AMIA Symp. 2020;2020:197–202.

Google Scholar 

Vermassen J, Colpaert K, De Bus L, Depuydt P, Decruyenaere J. Automated screening of natural language in electronic health records for the diagnosis septic shock is feasible and outperforms an approach based on explicit administrative codes. J Crit Care. 2020;56:203–7.

Article  PubMed  Google Scholar 

McGoldrick DM, Edwards J, Praveen P, Parmar S. Admission patterns and outcomes of patients admitted to critical care in the UK with surgically treated facial infection: an analysis of the Intensive Care National Audit and Research Centre Case Mix Programme database. Br J Oral Maxillofac Surg. 2022;60(8):1074–9.

Article  PubMed  Google Scholar 

Magee F, Bailey M, Pilcher DV, Mårtensson J, Bellomo R. Early glycemia and mortality in critically ill septic patients: interaction with insulin-treated diabetes. J Crit Care. 2018;45:170–7.

Article  CAS  PubMed  Google Scholar 

Zahar JR, Schwebel C, Adrie C, Garrouste-Orgeas M, Français A, Vesin A, Nguile-Makao M, Tabah A, Laupland K, Le-Monnier A, et al. Outcome of ICU patients with Clostridium difficile infection. CritCare (London, England). 2012;16(6):R215.

Article  Google Scholar 

Bagshaw SM, Zuege DJ, Stelfox HT, Opgenorth D, Wasylak T, Fraser N, Nguyen TX. Association Between pandemic coronavirus disease 2019 public health measures and reduction in critical care utilization across ICUs in Alberta. Can Crit Care Med. 2022;50(3):353–62.

Article  CAS  PubMed  Google Scholar 

Lakbar I, Munoz M, Pauly V, Orleans V, Fabre C, Fond G, Vincent JL, Boyer L, Leone M. Septic shock: incidence, mortality and hospital readmission rates in French intensive care units from 2014 to 2018. Anaesth Crit Care Pain Med. 2022;41(3):101082.

Article  PubMed  Google Scholar 

Tabah A, Buetti N, Staiquly Q, Ruckly S, Akova M, Aslan AT, Leone M, Conway Morris A, Bassetti M, Arvaniti K, et al. Epidemiology and outcomes of hospital-acquired bloodstream infections in intensive care unit patients: the EUROBACT-2 international cohort study. Intensive Care Med. 2023;49(2):178–90.

Article  CAS  PubMed  PubMed Central  Google Scholar 

•• Fiore MC, Smith SS, Adsit RT, Bolt DM, Conner KL, Bernstein SL, Eng OD, Lazuk D, Gonzalez A, Jorenby DE, et al. The first 20 months of the COVID-19 pandemic: mortality, intubation and ICU rates among 104,590 patients hospitalized at 21 United States health systems. Plos One. 2022;17(9):e0274571. An American study that utilized electronic data to examine outcomes of COVID-19 associated with ICU admission.

Rivera AS, Al-Heeti O, Petito LC, Feinstein MJ, Achenbach CJ, Williams J, Taiwo B. Association of statin use with outcomes of patients admitted with COVID-19: an analysis of electronic health records using superlearner. BMC Infect Dis. 2023;23(1):115.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kim Y, Zhu L, Zhu H, Li X, Huang Y, Gu C, Bush H, Chung C, Zhang GQ. Characterizing cancer and COVID-19 outcomes using electronic health records. Plos One. 2022;17(5): e0267584.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Descamps A, Frenkiel J, Zarca K, Laidi C, Godin O, Launay O, Leboyer M, Durand-Zaleski I. Association between mental disorders and COVID-19 outcomes among inpatients in France: a retrospective nationwide population-based study. J Psychiatr Res. 2022;155:194–201.

Article  PubMed  PubMed Central  Google Scholar 

Gao M, Piernas C, Astbury NM, Hippisley-Cox J, O’Rahilly S, Aveyard P, Jebb SA. Associations between body-mass index and COVID-19 severity in 6·9 million people in England: a prospective, community-based, cohort study. Lancet Diabetes Endocrinol. 2021;9(6):350–9.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Aveyard P, Gao M, Lindson N, Hartmann-Boyce J, Watkinson P, Young D, Coupland CAC, Tan PS, Clift AK, Harrison D, et al. Association between pre-existing respiratory disease and its treatment, and severe COVID-19: a population cohort study. Lancet Respir Med. 2021;9(8):909–23.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Mathur R, Rentsch CT, Morton CE, Hulme WJ, Schultze A, MacKenna B, Eggo RM, Bhaskaran K, Wong AYS, Williamson EJ, et al. Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform. Lancet (London, England). 2021;397(10286):1711–24.

Article  CAS  PubMed  Google Scholar 

Ghonimi TAL, Alkad MM, Abuhelaiqa EA, Othman MM, Elgaali MA, Ibrahim RAM, Joseph SM, Al-Malki HA, Hamad AI. Mortality and associated risk factors of COVID-19 infection in dialysis patients in Qatar: a nationwide cohort study. Plos One. 2021;16(7): e0254246.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Gude-Sampedro F, Fernández-Merino C, Ferreiro L, Lado-Baleato Ó, Espasandín-Domínguez J, Hervada X, Cadarso CM, Valdés L. Development and validation of a prognostic model based on comorbidities to predict COVID-19 severity: a population-based study. Int J Epidemiol. 2021;50(1):64–74.

Article  PubMed  Google Scholar 

Honarvar MR, Roshandel G, Shirzad-Aski H, Tabarraei A, Tahamtan A, Ghelichi-Ghojogh M, Fazel A, Arefnia S, Jafari N, Mansoury M, et al. Epidemiological and clinical characteristics of the COVID-19 epidemic and associated factors for mortality in Golestan province, Iran: a retrospective cohort study. J Prev Med Hyg. 2021;62(2):E298-e304.

PubMed  PubMed Central  Google Scholar 

Ancochea J, Izquierdo JL, Soriano JB. Evidence of gender differences in the diagnosis and management of coronavirus disease 2019 patients: an analysis of electronic health records using natural language processing and machine learning. J Womens Health. 2021;30(3):393–404.

Article  Google Scholar 

Alrawashdeh M, Klompas M, Simpson SQ, Kadri SS, Poland R, Guy JS, Perlin JB, Rhee C. Prevalence and outcomes of previously healthy adults among patients hospitalized with community-onset sepsis. Chest. 2022;162(1):101–10.

Article  PubMed  PubMed Central 

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