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Queipo M, Barbado J, Torres AM, Mateo J. Approaching Personalized Medicine: The Use of Machine Learning to Determine Predictors of Mortality in a Population with SARS-CoV-2 Infection. Biomedicines 2024; 12:409. [PMID: 38398012 PMCID: PMC10886784 DOI: 10.3390/biomedicines12020409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024] Open
Abstract
The COVID-19 pandemic demonstrated the need to develop strategies to control a new viral infection. However, the different characteristics of the health system and population of each country and hospital would require the implementation of self-systems adapted to their characteristics. The objective of this work was to determine predictors that should identify the most severe patients with COVID-19 infection. Given the poor situation of the hospitals in the first wave, the analysis of the data from that period with an accurate and fast technique can be an important contribution. In this regard, machine learning is able to objectively analyze data in hourly sets and is used in many fields. This study included 291 patients admitted to a hospital in Spain during the first three months of the pandemic. After screening seventy-one features with machine learning methods, the variables with the greatest influence on predicting mortality in this population were lymphocyte count, urea, FiO2, potassium, and serum pH. The XGB method achieved the highest accuracy, with a precision of >95%. Our study shows that the machine learning-based system can identify patterns and, thus, create a tool to help hospitals classify patients according to their severity of illness in order to optimize admission.
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Affiliation(s)
- Mónica Queipo
- Autoimmunity and Inflammation Research Group, Río Hortega University Hospital, 47012 Valladolid, Spain
- Cooperative Research Network Focused on Health Results—Advanced Therapies (RICORS TERAV), 28220 Madrid, Spain
| | - Julia Barbado
- Autoimmunity and Inflammation Research Group, Río Hortega University Hospital, 47012 Valladolid, Spain
- Cooperative Research Network Focused on Health Results—Advanced Therapies (RICORS TERAV), 28220 Madrid, Spain
- Internal Medicine, Río Hortega University Hospital, 47012 Valladolid, Spain
| | - Ana María Torres
- Medical Analysis Expert Group, Institute of Technology, University of Castilla-La Mancha, 16071 Cuenca, Spain
- Medical Analysis Expert Group, Instituto de Investigación Sanitaria de Castilla-La Mancha (IDISCAM), 45071 Toledo, Spain
| | - Jorge Mateo
- Medical Analysis Expert Group, Institute of Technology, University of Castilla-La Mancha, 16071 Cuenca, Spain
- Medical Analysis Expert Group, Instituto de Investigación Sanitaria de Castilla-La Mancha (IDISCAM), 45071 Toledo, Spain
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Impact of the first wave of the COVID-19 pandemic on non-COVID inpatient care in southern Spain. Sci Rep 2023; 13:1634. [PMID: 36717651 PMCID: PMC9885064 DOI: 10.1038/s41598-023-28831-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 01/25/2023] [Indexed: 01/31/2023] Open
Abstract
We assessed the impact of the first wave of COVID-19 pandemic on non-COVID hospital admissions, non-COVID mortality, factors associated with non-COVID mortality, and changes in the profile of non-COVID patients admitted to hospital. We used the Spanish Minimum Basic Data Set with diagnosis grouped according to the Diagnostic Related Groups. A total of 10,594 patients (3% COVID-19; 97% non-COVID) hospitalised during the first wave in 2020 (27-February/07-June) were compared with those hospitalised within the same dates of 2017-2019 (average annual admissions: 14,037). We found a decrease in non-COVID medical (22%) and surgical (33%) hospitalisations and a 25.7% increase in hospital mortality among non-COVID patients during the first pandemic wave compared to pre-pandemic years. During the officially declared sub-period of excess mortality in the area (17-March/20-April, in-hospital non-COVID mortality was even higher (58.7% higher than the pre-pandemic years). Non-COVID patients hospitalised during the first pandemic wave (compared to pre-pandemic years) were older, more frequently men, with longer hospital stay and increased disease severity. Hospitalisation during the first pandemic wave in 2020, compared to hospitalisation during the pre-pandemic years, was an independent risk factor for non-COVID mortality (HR 1.30, 95% CI 1.07-1.57, p = 0.008), reflecting the negative impact of the pandemic on hospitalised patients.
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Ramos W, Arrasco J, De La Cruz-Vargas JA, Ordóñez L, Vargas M, Seclén-Ubillús Y, Luna M, Guerrero N, Medina J, Sandoval I, Solis-Castro ME, Loayza M. Epidemiological Characteristics of Deaths from COVID-19 in Peru during the Initial Pandemic Response. Healthcare (Basel) 2022; 10:healthcare10122404. [PMID: 36553928 PMCID: PMC9777767 DOI: 10.3390/healthcare10122404] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 11/23/2022] [Accepted: 11/25/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND AND AIM Peru is the country with the highest mortality rate from COVID-19 globally, so the analysis of the characteristics of deaths is of national and international interest. The aim was to determine the epidemiological characteristics of deaths from COVID-19 in Peru from 28 March to 21 May 2020. METHODS Deaths from various sources were investigated, including the COVID-19 Epidemiological Surveillance and the National System of Deaths (SINADEF). In all, 3851 deaths that met the definition of a confirmed case and had a positive result of RT-PCR or rapid test IgM/IgG, were considered for the analysis. We obtained the epidemiological variables and carried out an analysis of time defined as the pre-hospital time from the onset of symptoms to hospitalization, and hospital time from the date of hospitalization to death. RESULTS Deaths were more frequent in males (72.0%), seniors (68.8%) and residents of the region of Lima (42.7%). In 17.8% of cases, the death occurred out-of-hospital, and 31.4% had some comorbidity. The median of pre-hospital time was 7 days (IQR: 4.0-9.0) and for the hospital time was 5 days (IQR: 3.0-9.0). The multivariable analysis with Poisson regression with robust variance found that the age group, comorbidity diagnosis and the region of origin significantly influenced pre-hospital time; while sex, comorbidity diagnosis, healthcare provider and the region of origin significantly influenced hospital time. CONCLUSION Deaths occurred mainly in males, seniors and on the coast, with considerable out-of-hospital deaths. Pre-hospital time was affected by age group, the diagnosis of comorbidities and the region of origin; while, hospital time was influenced by gender, the diagnosis of comorbidities, healthcare provider and the region of origin.
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Affiliation(s)
- Willy Ramos
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Ministerio de Salud, Lima 15072, Peru
- Instituto de Investigaciones en Ciencias Biomédicas (INICIB), Universidad Ricardo Palma, Lima 15039, Peru
- Correspondence:
| | - Juan Arrasco
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Ministerio de Salud, Lima 15072, Peru
| | - Jhony A. De La Cruz-Vargas
- Instituto de Investigaciones en Ciencias Biomédicas (INICIB), Universidad Ricardo Palma, Lima 15039, Peru
| | - Luis Ordóñez
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Ministerio de Salud, Lima 15072, Peru
- Programa de Especialización en Epidemiología de Campo (PREEC), Lima 15072, Peru
| | - María Vargas
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Ministerio de Salud, Lima 15072, Peru
| | - Yovanna Seclén-Ubillús
- Unidad de Post Grado, Facultad de Medicina de San Fernando, Universidad Nacional Mayor de San Marcos, Lima 15001, Peru
| | - Miguel Luna
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Ministerio de Salud, Lima 15072, Peru
- Programa de Especialización en Epidemiología de Campo (PREEC), Lima 15072, Peru
| | - Nadia Guerrero
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Ministerio de Salud, Lima 15072, Peru
| | - José Medina
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Ministerio de Salud, Lima 15072, Peru
| | - Isabel Sandoval
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Ministerio de Salud, Lima 15072, Peru
- Programa de Especialización en Epidemiología de Campo (PREEC), Lima 15072, Peru
| | - Maria Edith Solis-Castro
- Departamento Académico de Medicina Humana, Facultad de Ciencias de la Salud, Universidad Nacional de Tumbes, Tumbes 24001, Peru
| | - Manuel Loayza
- Instituto de Investigaciones en Ciencias Biomédicas (INICIB), Universidad Ricardo Palma, Lima 15039, Peru
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Equiza-Goñi J. Real-time mortality statistics during the COVID-19 pandemic: A proposal based on Spanish data, January-March, 2021. Front Public Health 2022; 10:950469. [PMID: 36424971 PMCID: PMC9679298 DOI: 10.3389/fpubh.2022.950469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Accepted: 10/24/2022] [Indexed: 11/10/2022] Open
Abstract
Objectives During the COVID-19 pandemic, surveillance systems worldwide underestimated mortality in real time due to longer death reporting lags. In Spain, the mortality monitor "MoMo" published downward biased excess mortality estimates daily. I study the correction of such bias using polynomial regressions in data from January to March 2021 for Spain and the Comunitat Valenciana, the region with the highest excess mortality. Methods This adjustment for real-time statistics consisted of (1) estimating forthcoming revisions with polynomial regressions of past revisions, and (2) multiplying the daily-published excess mortality by these estimated revisions. The accuracy of the corrected estimates compared to the original was measured by contrasting their mean absolute errors (MAE) and root mean square errors (RMSE). Results Applying quadratic and cubic regressions improved the first communication of cumulative mortality in Spain by 2-3%, on average, and the flow in registered deaths by 20%. However, for the Comunitat Valenciana, those corrections improved the first publications of the cumulative mortality by 36-45%, on average; their second publication, by 23-30%; and the third, by 15-21%. The flow of deaths registered each day improved by 62-63% on their first publication, by 19-36% on the second, and by 12-17% on the third. Conclusion It is recommended that MoMo's estimates for excess mortality be corrected from the effect of death reporting lags by using polynomial regressions. This holds for the flows in each date and their cumulative sum, as well as national and regional data. These adjustments can be applied by surveillance systems in other countries.
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Affiliation(s)
- Juan Equiza-Goñi
- Facultad de Ciencias Económicas y Empresariales, Universidad de Navarra, Pamplona, España
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Alfaro T, Martinez-Folgar K, Vives A, Bilal U. Excess Mortality during the COVID-19 Pandemic in Cities of Chile: Magnitude, Inequalities, and Urban Determinants. J Urban Health 2022; 99:922-935. [PMID: 35688966 PMCID: PMC9187147 DOI: 10.1007/s11524-022-00658-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/27/2022] [Indexed: 11/30/2022]
Abstract
We estimated excess mortality in Chilean cities during the COVID-19 pandemic and its association with city-level factors. We used mortality, and social and built environment data from the SALURBAL study for 21 Chilean cities, composed of 81 municipalities or "comunas", grouped in 4 macroregions. We estimated excess mortality by comparing deaths from January 2020 up to June 2021 vs 2016-2019, using a generalized additive model. We estimated a total of 21,699 (95%CI 21,693 to 21,704) excess deaths across the 21 cities. Overall relative excess mortality was highest in the Metropolitan (Santiago) and the North regions (28.9% and 22.2%, respectively), followed by the South and Center regions (17.6% and 14.1%). At the city-level, the highest relative excess mortality was found in the Northern cities of Calama and Iquique (around 40%). Cities with higher residential overcrowding had higher excess mortality. In Santiago, capital of Chile, municipalities with higher educational attainment had lower relative excess mortality. These results provide insight into the heterogeneous impact of COVID-19 in Chile, which has served as a magnifier of preexisting urban health inequalities, exhibiting different impacts between and within cities. Delving into these findings could help prioritize strategies addressed to prevent deaths in more vulnerable communities.
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Affiliation(s)
- Tania Alfaro
- Escuela de Salud Pública, Facultad de Medicina, Universidad de Chile, Independencia 939, Santiago, Chile.
| | - Kevin Martinez-Folgar
- Urban Health Collaborative; and Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, Philadelphia, PA, USA
| | - Alejandra Vives
- Departamento de Salud Pública, Pontificia Universidad Católica de Chile, CEDEUS, Santiago, Chile
| | - Usama Bilal
- Urban Health Collaborative; and Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, Philadelphia, PA, USA
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Satué de Velasco E, Gayol Fernández M, Eyaralar Riera MT, Magallón Botaya R, Abal Ferrer F. [Impact of the pandemic on primary care. SESPAS Report 2022]. GACETA SANITARIA 2022; 36 Suppl 1:S30-S35. [PMID: 35781145 PMCID: PMC9244614 DOI: 10.1016/j.gaceta.2022.05.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 05/23/2022] [Accepted: 05/25/2022] [Indexed: 11/16/2022]
Abstract
The COVID-19 pandemic, which last 2 years and still goes on, has pushed the primary health care (PC) to a current worrying situation of saturation and exhaustion. It is a community infectious disease, with a great amount of cases (around 10 million declared in January 2022) due to that, PC has made an extraordinary effort to pay attention on mild cases and on PC and to detect potentially serious cases early. Unfortunately, up to now, a global evaluation of the actions has not been carried out, in order to allow us to learn from this new experience. This article describes the different phases of the pandemic and its impact on PC. Finally, solutions are proposed to reinforce the central criteria that allow PC to be maintained as the foundation of the welfare state, longitudinality, resolution, accessibility, and care coordination and continuity, thanks to the contribution of resources and skills given to the PC. In conclusion, PC must still being the basis of the health system and it is mandatory to recover and claim those competencies and resources that should always have been a part of PC.
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Affiliation(s)
- Eduardo Satué de Velasco
- Farmacia Comunitaria, Maella (Zaragoza), España; Red Española de Atención Primaria (REAP), España
| | - Manuel Gayol Fernández
- Red Española de Atención Primaria (REAP), España; Enfermería de Área Sanitaria VI, SESPA Asturias, Arriondas, España
| | | | - Rosa Magallón Botaya
- Red Española de Atención Primaria (REAP), España; Medicina Familiar y Comunitaria, Centro de Salud de Arrabal, Zaragoza, España.
| | - Francisco Abal Ferrer
- Red Española de Atención Primaria (REAP), España; Medicina Familiar y Comunitaria, Centro de Salud de Siero Sariego, Carbayín Alto (Asturias), España
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Bermúdez-Tamayo C, Hernández MN, Cantero MTR, March JC, Álvarez-Dardet C. [Gaceta Sanitaria's response to the COVID-19 pandemic. Rapid management and transfer]. GACETA SANITARIA 2020; 34:425-427. [PMID: 32892946 PMCID: PMC7472065 DOI: 10.1016/j.gaceta.2020.07.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Affiliation(s)
- Clara Bermúdez-Tamayo
- Comité Editorial de Gaceta Sanitaria; Escuela Andaluza de Salud Pública, Granada, España; CIBER de Epidemiología y Salud Pública (CIBERESP), España.
| | - Miguel Negrín Hernández
- Comité Editorial de Gaceta Sanitaria; Departamento de Métodos Cuantitativos, Universidad de Las Palmas de Gran Canaria, España
| | - María Teresa Ruiz Cantero
- Comité Editorial de Gaceta Sanitaria; CIBER de Epidemiología y Salud Pública (CIBERESP), España; Grupo de Investigación en Salud Pública, Universidad de Alicante, Alicante, España
| | - Joan Carles March
- Escuela Andaluza de Salud Pública, Granada, España; CIBER de Epidemiología y Salud Pública (CIBERESP), España
| | - Carlos Álvarez-Dardet
- Comité Editorial de Gaceta Sanitaria; CIBER de Epidemiología y Salud Pública (CIBERESP), España; Grupo de Investigación en Salud Pública, Universidad de Alicante, Alicante, España
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