Smoking can play a key role in SARS-CoV-2 infection and in the course of the disease. Previous studies have conflicting or inconclusive results on the prevalence of smoking and the severity of the ...coronavirus disease (COVID-19).
Observational, multicenter, retrospective cohort study of 14,260 patients admitted for COVID-19 in Spanish hospitals between February and September 2020. Their clinical characteristics were recorded and the patients were classified into a smoking group (active or former smokers) or a non-smoking group (never smokers). The patients were followed up to one month after discharge. Differences between groups were analyzed. A multivariate logistic regression and Kapplan Meier curves analyzed the relationship between smoking and in-hospital mortality.
The median age was 68.6 (55.8-79.1) years, with 57.7% of males. Smoking patients were older (69.9 59.6-78.0 years), more frequently male (80.3%) and with higher Charlson index (4 2-6) than non-smoking patients. Smoking patients presented a worse evolution, with a higher rate of admission to the intensive care unit (ICU) (10.4 vs 8.1%), higher in-hospital mortality (22.5 vs. 16.4%) and readmission at one month (5.8 vs. 4.0%) than in non-smoking patients. After multivariate analysis, smoking remained associated with these events.
Active or past smoking is an independent predictor of poor prognosis in patients with COVID-19. It is associated with higher ICU admissions and in-hospital mortality.
OBJECTIVETo explore the clinical and epidemiological characteristics of chronic obstructive pulmonary disease (COPD) patients with Aspergillus spp. isolation from respiratory samples, and to identify ...which factors may help us to distinguish between colonisation and infection. METHODSA retrospective cohort study was performed. All patients with COPD and respiratory isolation of Aspergillus spp. over a 12-year period were included. Patients were assigned to 2 categories: colonisation and pulmonary aspergillosis (PA), which includes the different clinical forms of aspergillosis. A binary logistic regression model was performed to identify the predictive factors of PA. RESULTSA total of 123 patients were included in the study: 48 (39.0%) with colonisation and 75 (61.0%) with PA: 68 with probable invasive pulmonary aspergillosis and 7 with chronic pulmonary aspergillosis. Spirometric stages of the GOLD classification were not correlated with a higher risk of PA. Four independent predictive factors of PA in COPD patients were identified: home oxygen therapy (OR: 4.39; 95% CI: 1.60-12.01; P=.004), bronchiectasis (OR: 3.61; 95% CI: 1.40-9.30; P=.008), hospital admission in the previous three months (OR: 3.12; 95% CI: 1.24-7.87; P=.016) and antifungal therapy against Candida spp. in the previous month (OR: 3.18; 95% CI: 1.16-8.73; P=.024). CONCLUSIONSContinuous home oxygen therapy, bronchiectasis, hospital admission in the previous three months and administration of antifungal medication against Candida spp. in the previous month were associated with a higher risk of pulmonary aspergillosis in patients with COPD.
Primary lymphoma of the bladder represents 0.2% of all bladder malignancies. Secondary involvement of the bladder by malignant lymphoma occurs in 10% to 50% of cases. Most lymphomas of the bladder ...are non-Hodgkin's lymphomas of the B-cell type, with preponderance among women. The impact of positron emission tomography (PET) on tumor staging has recently become very important due to its use in the study of diagnosis extension and individual therapy design.
We report the case of a 79-year-old Caucasian man with intermittent haematuria as the presenting symptom of non-Hodgkin's lymphoma of the bladder. He was first diagnosed with primary lymphoma of the bladder using the current staging method, but a positron emission tomography study subsequently revealed that he instead had a secondary involvement of the bladder.
The staging of non-Hodgkin's lymphomas, which is useful in order to plan accurate therapy, has been changing since the introduction of positron emission tomography scanning. Primary lymphomas of the bladder, although very rare, may be even more uncommon when this imaging technique is used to assess the extension of the disease. Although the interpretation of this technique has some limitations that should be taken into account, the extensive use of positron emission tomography should nonetheless help improve the diagnosis of this disease.
Smoking can play a key role in SARS-CoV-2 infection and in the course of the disease. Previous studies have conflicting or inconclusive results on the prevalence of smoking and the severity of the ...coronavirus disease (COVID-19).
Observational, multicenter, retrospective cohort study of 14,260 patients admitted for COVID-19 in Spanish hospitals between February and September 2020. Their clinical characteristics were recorded and the patients were classified into a smoking group (active or former smokers) or a non-smoking group (never smokers). The patients were followed up to one month after discharge. Differences between groups were analysed. A multivariate logistic regression and Kapplan Meier curves analysed the relationship between smoking and in-hospital mortality.
The median age was 68.6 (55.8−79.1) years, with 57.7% of males. Smoking patients were older (69.9 (59.6−78.0 years)), more frequently male (80.3%) and with higher Charlson index (4 (2−6)) than non-smoking patients. Smoking patients presented a worse evolution, with a higher rate of admission to the intensive care unit (ICU) (10.4 vs. 8.1%), higher in-hospital mortality (22.5 vs. 16.4%) and readmission at one month (5.8 vs. 4.0%) than in non-smoking patients. After multivariate analysis, smoking remained associated with these events.
Active or past smoking is an independent predictor of poor prognosis in patients with COVID-19. It is associated with higher ICU admissions and in-hospital mortality.
El tabaquismo puede tener un papel importante en la infección por SARS-CoV-2 y en el curso de la enfermedad. Los estudios previos muestran resultados contradictorios o no concluyentes sobre la prevalencia de fumar y la severidad en la enfermedad por coronavirus (COVID-19).
Estudio de cohortes observacional, multicéntrico y retrospectivo de 14.260 pacientes que ingresaron por COVID-19 en hospitales españoles desde febrero a septiembre de 2020. Se registraron sus características clínicas y se clasificaron en el grupo con tabaquismo si tabaquismo activo o previo o en el grupo sin tabaquismo si nunca habían fumado. Se realizó un seguimiento hasta un mes después del alta. Se analizaron las diferencias entre grupos. La relación entre tabaquismo y mortalidad intrahospitalaria se valoró mediante una regresión logística multivariante y curvas de Kapplan Meier.
La mediana de edad fue 68,6 (55,8–79,1) años, con un 57,7% de varones. El grupo con tabaquismo presentó mayor edad (69,9 (59,6–78,0 años)), predominio masculino (80,3%) y mayor índice de Charlson (4 (2−6)). La evolución fue peor en estos pacientes, con una mayor tasa de ingreso en UCI (10,4 vs 8,1%), mayor mortalidad intrahospitalaria (22,5 vs 16,4%) y reingreso al mes (5,8 vs 4,0%) que el grupo sin tabaquismo. Tras el análisis multivariante, el tabaquismo permanecía asociado a estos eventos.
El tabaquismo de forma activa o pasada es un factor predictor independiente de mal pronóstico en los pacientes con COVID-19, estando asociada a mayor probabilidad de ingreso en UCI y a mayor mortalidad intrahospitalaria.
The prognosis of a patient with COVID-19 pneumonia is uncertain. Our objective was to establish a predictive model of disease progression to facilitate early decision-making. A retrospective study ...was performed of patients admitted with COVID-19 pneumonia, classified as severe (admission to the intensive care unit, mechanic invasive ventilation, or death) or non-severe. A predictive model based on clinical, laboratory, and radiological parameters was built. The probability of progression to severe disease was estimated by logistic regression analysis. Calibration and discrimination (receiver operating characteristics curves and AUC) were assessed to determine model performance. During the study period 1152 patients presented with SARS-CoV-2 infection, of whom 229 (19.9%) were admitted for pneumonia. During hospitalization, 51 (22.3%) progressed to severe disease, of whom 26 required ICU care (11.4); 17 (7.4%) underwent invasive mechanical ventilation, and 32 (14%) died of any cause. Five predictors determined within 24 h of admission were identified: Diabetes, Age, Lymphocyte count, SaO
, and pH (DALSH score). The prediction model showed a good clinical performance, including discrimination (AUC 0.87 CI 0.81, 0.92) and calibration (Brier score = 0.11). In total, 0%, 12%, and 50% of patients with severity risk scores ≤ 5%, 6-25%, and > 25% exhibited disease progression, respectively. A risk score based on five factors predicts disease progression and facilitates early decision-making according to prognosis.
PDF
