RESUMEN
Introdution: Immune checkpoint inhibitors (ICIs) have significantly improved clinical outcomes for a wide range of cancers but can also lead to serious or fatal immune-related adverse events (irAEs). Although ICI-related pericardial toxicities have been reported, the clinical features are not well characterized in real-world studies. Objective: To characterize the main features of ICI-related pericardial toxicities and identify factors associated with death. Methods: Data from January 1, 2011 to March 31, 2020 in the FDA Adverse Event Reporting System database were retrieved for disproportionality analysis. We used the reporting odds ratio and the information component (IC) to evaluate the association between ICIs and pericardial adverse events. Clinical characteristics of patients with ICI-associated pericardial toxicities were collected and compared between fatal and non-fatal groups. The time to onset following different ICI regimens was further investigated. Results: We identified a total of 705 ICI-associated pericardial toxicities which appeared to influence more men (53.90%) than women (36.03%), with a median age of 63 (interquartile range [IQR] 54-69) years. Patients with lung cancer accounted for the largest proportion (55.6%). ICI therapies were detected with pharmacovigilance signals of pericardial toxicities, corresponding to IC025 = 2.11 and ROR 4.87 [4.51-5.25]. Nevertheless, there was a lack of association between anti-CTLA-4 and pericardial toxicities. There was no difference in onset time among all ICI regimens. However, TTO of fatal cases (25 days (interquartile range [IQR] 6-70)) occurred statistically earlier than non-fatal cases (42 days (IQR 12-114), p = 0.003). Conclusion: ICI monotherapy (PD-1/PD-L1 therapy) and combination therapy can lead to pericardial toxicities that can result in serious outcomes and tend to occur early. Early recognition and management of ICI-related pericardial disorders should attract clinical attention. The findings require further clinical surveillance for the quantification.
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This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 (COVID-19). A retrospective study of the inpatients with COVID-19 admitted from 15 January to 15 March 2020 in Wuhan is reported. The data of symptoms, comorbidity, demographic, vital sign, CT scans results and laboratory test results on admission were collected. Machine-learning methods (Random Forest and XGboost) were used to rank clinical features for mortality risk. Multivariate logistic regression models were applied to identify clinical features with statistical significance. The predictors of mortality were lactate dehydrogenase (LDH), C-reactive protein (CRP) and age based on 500 bootstrapped samples. A multivariate logistic regression model was formed to predict mortality 292 in-sample patients with area under the receiver operating characteristics (AUROC) of 0.9521, which was better than CURB-65 (AUROC of 0.8501) and the machine-learning-based model (AUROC of 0.4530). An out-sample data set of 13 patients was further tested to show our model (AUROC of 0.6061) was also better than CURB-65 (AUROC of 0.4608) and the machine-learning-based model (AUROC of 0.2292). LDH, CRP and age can be used to identify severe patients with COVID-19 on hospital admission.
Asunto(s)
Infecciones por Coronavirus/mortalidad , Infecciones por Coronavirus/terapia , Modelos Logísticos , Aprendizaje Automático , Neumonía Viral/mortalidad , Neumonía Viral/terapia , Adolescente , Adulto , Anciano , COVID-19 , China/epidemiología , Femenino , Hospitalización , Humanos , Masculino , Persona de Mediana Edad , Pandemias , Pronóstico , Curva ROC , Reproducibilidad de los Resultados , Estudios Retrospectivos , Medición de Riesgo/métodos , Adulto JovenRESUMEN
OBJECTIVE: To describe the characteristics and outcomes of patients with severe COVID-19 and in-hospital cardiac arrest (IHCA) in Wuhan, China. METHODS: The outcomes of patients with severe COVID-19 pneumonia after IHCA over a 40-day period were retrospectively evaluated. Between January 15 and February 25, 2020, data for all cardiopulmonary resuscitation (CPR) attempts for IHCA that occurred in a tertiary teaching hospital in Wuhan, China were collected according to the Utstein style. The primary outcome was restoration of spontaneous circulation (ROSC), and the secondary outcomes were 30-day survival, and neurological outcome. RESULTS: Data from 136 patients showed 119 (87.5%) patients had a respiratory cause for their cardiac arrest, and 113 (83.1%) were resuscitated in a general ward. The initial rhythm was asystole in 89.7%, pulseless electrical activity (PEA) in 4.4%, and shockable in 5.9%. Most patients with IHCA were monitored (93.4%) and in most resuscitation (89%) was initiated <1â¯min. The average length of hospital stay was 7 days and the time from illness onset to hospital admission was 10 days. The most frequent comorbidity was hypertension (30.2%), and the most frequent symptom was shortness of breath (75%). Of the patients receiving CPR, ROSC was achieved in 18 (13.2%) patients, 4 (2.9%) patients survived for at least 30 days, and one patient achieved a favourable neurological outcome at 30 days. Cardiac arrest location and initial rhythm were associated with better outcomes. CONCLUSION: Survival of patients with severe COVID-19 pneumonia who had an in-hospital cardiac arrest was poor in Wuhan.