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1.
Rev. clín. esp. (Ed. impr.) ; 224(1): 35-42, ene. 2024. tab, graf
Article in Spanish | IBECS | ID: ibc-EMG-528

ABSTRACT

Introducción Durante la pandemia de COVID se especuló que los pacientes con el virus que tenían relación con el tabaco podrían tener una menor probabilidad de agravamiento de la enfermedad o muerte. Para evaluar si existe una asociación entre el tabaquismo y el riesgo de mortalidad intrahospitalaria se utiliza la tecnología de Big Data y Procesamiento del Lenguaje Natural (PLN) de SAVANA. Método Se llevó a cabo un estudio de cohortes retrospectivo, observacional y sin intervención basado en datos de vida real extraídos de registros médicos de toda Castilla-La Mancha utilizando las técnicas de PLN e inteligencia artificial desarrolladas por SAVANA. El estudio abarcó toda la población de esta Comunidad con historia clínica electrónica en SESCAM que presentara diagnóstico de COVID desde el 1 de marzo de 2020 al 28 de febrero de 2021. Resultados Los fumadores tienen mayor porcentaje de factores de riesgo cardiovascular (hipertensión arterial, dislipemia y diabetes), EPOC, asma, EPID, CI, ECV, TEP, cáncer en general y cáncer de pulmón en particular, bronquiectasias, insuficiencia cardíaca y antecedentes de neumonía, de forma significativa (p<0,0001). Los pacientes exfumadores, fumadores y no fumadores tienen una diferencia de edad significativa. En cuanto a las muertes hospitalarias, fueron más frecuentes en el caso de los exfumadores, siguiendo los fumadores y luego los no fumadores (p<0,0001). Conclusión Existe un mayor riesgo de mortalidad intrahospitalaria en los pacientes infectados por SARS-CoV-2 que sean fumadores activos o hayan fumado en el pasado. (AU)


Introduction During the COVID pandemic, it was speculated that patients with the virus who were smoking-related might have a lower likelihood of disease exacerbation or death. To assess whether there is an association between smoking and risk of in-hospital mortality, SAVANA's big data and natural language processing (NLP) technology is used. Method A retrospective, observational, non-interventional cohort study was conducted based on real-life data extracted from medical records throughout Castilla-La Mancha using natural language processing and artificial intelligence techniques developed by SAVANA. The study covered the entire population of this region with Electronic Medical Records in SESCAM presenting with a diagnosis of COVID from March 1, 2020 to February 28, 2021. Results Smokers had a significantly higher percentage of cardiovascular risk factors (hypertension, dyslipidemia and diabetes), COPD, asthma, IDP, IC, CVD, PTE, cancer in general and lung cancer in particular, bronchiectasis, heart failure and a history of pneumonia (P<.0001). Former smokers, current smokers and non-smokers have a significant age difference. As for in-hospital deaths, they were more frequent in the case of ex-smokers, followed by smokers and then non-smokers (P<.0001). Conclusion There is an increased risk of dying in hospital in SARS-CoV-2-infected patients who are active smokers or have smoked in the past. (AU)


Subject(s)
Humans , Young Adult , Adult , Middle Aged , Aged , Aged, 80 and over , Coronavirus Infections/epidemiology , Nicotiana , Mortality , Big Data , Retrospective Studies , Cohort Studies
2.
Rev. clín. esp. (Ed. impr.) ; 224(1): 35-42, ene. 2024. tab, graf
Article in Spanish | IBECS | ID: ibc-229910

ABSTRACT

Introducción Durante la pandemia de COVID se especuló que los pacientes con el virus que tenían relación con el tabaco podrían tener una menor probabilidad de agravamiento de la enfermedad o muerte. Para evaluar si existe una asociación entre el tabaquismo y el riesgo de mortalidad intrahospitalaria se utiliza la tecnología de Big Data y Procesamiento del Lenguaje Natural (PLN) de SAVANA. Método Se llevó a cabo un estudio de cohortes retrospectivo, observacional y sin intervención basado en datos de vida real extraídos de registros médicos de toda Castilla-La Mancha utilizando las técnicas de PLN e inteligencia artificial desarrolladas por SAVANA. El estudio abarcó toda la población de esta Comunidad con historia clínica electrónica en SESCAM que presentara diagnóstico de COVID desde el 1 de marzo de 2020 al 28 de febrero de 2021. Resultados Los fumadores tienen mayor porcentaje de factores de riesgo cardiovascular (hipertensión arterial, dislipemia y diabetes), EPOC, asma, EPID, CI, ECV, TEP, cáncer en general y cáncer de pulmón en particular, bronquiectasias, insuficiencia cardíaca y antecedentes de neumonía, de forma significativa (p<0,0001). Los pacientes exfumadores, fumadores y no fumadores tienen una diferencia de edad significativa. En cuanto a las muertes hospitalarias, fueron más frecuentes en el caso de los exfumadores, siguiendo los fumadores y luego los no fumadores (p<0,0001). Conclusión Existe un mayor riesgo de mortalidad intrahospitalaria en los pacientes infectados por SARS-CoV-2 que sean fumadores activos o hayan fumado en el pasado. (AU)


Introduction During the COVID pandemic, it was speculated that patients with the virus who were smoking-related might have a lower likelihood of disease exacerbation or death. To assess whether there is an association between smoking and risk of in-hospital mortality, SAVANA's big data and natural language processing (NLP) technology is used. Method A retrospective, observational, non-interventional cohort study was conducted based on real-life data extracted from medical records throughout Castilla-La Mancha using natural language processing and artificial intelligence techniques developed by SAVANA. The study covered the entire population of this region with Electronic Medical Records in SESCAM presenting with a diagnosis of COVID from March 1, 2020 to February 28, 2021. Results Smokers had a significantly higher percentage of cardiovascular risk factors (hypertension, dyslipidemia and diabetes), COPD, asthma, IDP, IC, CVD, PTE, cancer in general and lung cancer in particular, bronchiectasis, heart failure and a history of pneumonia (P<.0001). Former smokers, current smokers and non-smokers have a significant age difference. As for in-hospital deaths, they were more frequent in the case of ex-smokers, followed by smokers and then non-smokers (P<.0001). Conclusion There is an increased risk of dying in hospital in SARS-CoV-2-infected patients who are active smokers or have smoked in the past. (AU)


Subject(s)
Humans , Young Adult , Adult , Middle Aged , Aged , Aged, 80 and over , Coronavirus Infections/epidemiology , Nicotiana , Mortality , Big Data , Retrospective Studies , Cohort Studies
3.
Rev Clin Esp (Barc) ; 224(1): 34-42, 2024 Jan.
Article in English | MEDLINE | ID: mdl-38142978

ABSTRACT

INTRODUCTION: During the COVID pandemic, it was speculated that patients with the virus who were smoking-related might have a lower likelihood of disease exacerbation or death. To assess whether there is an association between smoking and risk of in-hospital mortality, SAVANA's big data and Natural Language Processing (NLP) technology is used. METHOD: A retrospective, observational, non-interventional cohort study was conducted based on real-life data extracted from medical records throughout Castilla La Mancha using Natural Language Processing and Artificial Intelligence techniques developed by SAVANA. The study covered the entire population of this region with Electronic Medical Records in SESCAM presenting with a diagnosis of COVID from March 1, 2020 to February 28, 2021. RESULTS: Smokers had a significantly higher percentage of cardiovascular risk factors (hypertension, dyslipidemia and diabetes), COPD, asthma, IDP, IC, CVD, PTE, cancer in general and lung cancer in particular, bronchiectasis, heart failure and a history of pneumonia (p < 0.0001).Former smokers, current smokers and non-smokers have a significant age difference. As for in-hospital deaths, they were more frequent in the case of ex-smokers, followed by smokers and then non-smokers (p < 0.0001). CONCLUSION: There is an increased risk of dying in hospital in SARS-COV2-infected patients who are active smokers or have smoked in the past.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , SARS-CoV-2 , Retrospective Studies , Smokers , Cohort Studies , Natural Language Processing , Artificial Intelligence , RNA, Viral , Hospitals
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