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1.
JCO Clin Cancer Inform ; 7: e2300060, 2023 08.
Article in English | MEDLINE | ID: mdl-37616550

ABSTRACT

PURPOSE: Recent studies have suggested that machine learning (ML) could be used to predict venous thromboembolism (VTE) in cancer patients with high accuracy. METHODS: We aimed to evaluate the performance of ML in predicting VTE events in patients with cancer. PubMed, Web of Science, and EMBASE to identify studies were searched. RESULTS: Seven studies involving 12,249 patients with cancer were included. The combined results of the different ML models demonstrated good accuracy in the prediction of VTE. In the training set, the global pooled sensitivity was 0.87, the global pooled specificity was 0.87, and the AUC was 0.91, and in the test set 0.65, 0.84, and 0.80, respectively. CONCLUSION: The prediction ML models showed good performance to predict VTE. External validation to determine the result's reproducibility is necessary.


Subject(s)
Neoplasms , Venous Thromboembolism , Humans , Venous Thromboembolism/diagnosis , Venous Thromboembolism/etiology , Reproducibility of Results , Neoplasms/complications , Machine Learning , Patients
2.
J Med Virol ; 94(4): 1540-1549, 2022 04.
Article in English | MEDLINE | ID: mdl-34845754

ABSTRACT

Coronavirus disease 2019 (COVID-19) infection in elderly patients is more aggressive and treatments have shown limited efficacy. Our objective is to describe the clinical course and to analyze the prognostic factors associated with a higher risk of mortality of a cohort of patients older than 80 years. In addition, we assess the efficacy of immunosuppressive treatments in this population. We analyzed the data from 163 patients older than 80 years admitted to our institution for COVID-19, during March and April 2020. A Lasso regression model and subsequent multivariate Cox regression were performed to select variables predictive of death. We evaluated the efficacy of immunomodulatory therapy in three cohorts using adjusted survival analysis. The mortality rate was 43%. The mean age was 85.2 years. The disease was considered severe in 76.1% of the cases. Lasso regression and multivariate Cox regression indicated that factors correlated with hospital mortality were: age (hazard ratio [HR] 1.12, 95% confidence interval [CI]: 1.03-1.22), alcohol consumption (HR 3.15, 95% CI: 1.27-7.84), CRP > 10 mg/dL (HR 2.67, 95% CI: 1.36-5.24), and oxygen support with Venturi Mask (HR 6.37, 95% CI: 2.18-18.62) or reservoir (HR 7.87, 95% CI: 3.37-18.38). Previous treatment with antiplatelets was the only protective factor (HR 0.47, 95% CI: 0.23-0.96). In the adjusted treatment efficacy analysis, we found benefit in the combined use of tocilizumab (TCZ) and corticosteroids (CS) (HR 0.09, 95% CI: 0.01-0.74) compared to standard treatment, with no benefit of CS alone (HR 0.95, 95% CI: 0.53-1.71). Hospitalized elderly patients suffer from a severe and often fatal form of COVID-19 disease. In this regard, several parameters might identify high-risk patients upon admission. Combined use of TCZ and CS could improve survival.


Subject(s)
Adrenal Cortex Hormones/administration & dosage , Antibodies, Monoclonal, Humanized/administration & dosage , COVID-19 Drug Treatment , COVID-19/mortality , Aged, 80 and over , COVID-19/virology , Comorbidity , Drug Therapy, Combination , Female , Hospital Mortality , Hospitalization , Humans , Male , Prognosis , Retrospective Studies , SARS-CoV-2/drug effects , SARS-CoV-2/physiology , Spain/epidemiology , Survival Analysis
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