Impact of high neutrophil-to-lymphocyte ratio on survival in hospitalized cancer patients with COVID-19.

Neutrophil-to-lymphocyte ratio (NLR) has been studied as a prognostic factor for mortality in COVID-19 patients. Our study aimed to evaluate the association between NLR at COVID-19 diagnosis and survival during the following 90 days in hospitalized patients with solid cancer. Between May 2020 and June 2021, 120 patients were included in a retrospective cohort study. Univariable analysis showed patients with an NLR > 8.3 were associated with an increased risk of death (HR: 4.34; 95% CI: 1.74-10.84) compared to patients with NLR < 3.82 and with NLR ≥3.82 and ≤8.30 (HR: 2.89; 95% CI: 1.32-6.36). Furthermore, on multivariable analysis, NLR > 8.30 independently correlated with increased mortality. In patients with solid malignancies with COVID-19, an NLR > 8.3 is associated with an increased risk of death.

[Clinical outcomes in cancer patients hospitalized with COVID-19]. / Evolución clínica de pacientes internados con cáncer e infección por COVID-19.

Cancer patients are exposed to more complications from COVID-19 than non-cancer patients. We report a cohort of 74 cancer patients (87.8% with solid neoplasia and 12.2% with hematological diseases) with COVID-19 infection admitted to a tertiary medical cancer center in Argentina. Pulmonary infiltrates were diagnosed at admission in 78.3% (N = 58) of the cases. COVID-19 infection was hospital-acquired in 20 (27.0%) patients. Thirty-nine patients (52.7%) received anticancer therapy within the 30 days prior to COVID-19 diagnosis; one was on radiation therapy. Twenty-four (32.4%) patients were admitted in the intensive care unit (ICU) and 18 (75.0%) required mechanical ventilation. All cause in-hospital mortality was 32.4% (N = 24) and ICU mortality was 62.5% (N = 15). Mortality under mechanical ventilation was 72.2% (N = 13). In the univariate analysis age, neutrophil count, neutrophil/lymphocyte index, D-dimer, ferritin, smoking, and nosocomial acquired infection were associated with in-hospital mortality. There were no statistically significant differences in mortality related to disease stage for solid tumors, neither cancer treatment within 30 days of COVID-19 diagnosis. Age and smoking were associated with mortality in the multivariate analysis. The adjusted odds ratios (95 CI) for age = 65 years and smoking were 8.87 (1.35-58.02) and 8.64 (1.32 - 56.64), respectively. Our experience can be useful for other institutions that assist cancer patients during the pandemic.

Los pacientes con cáncer y COVID-19 tienen más complicaciones que la población general. Comunicamos una cohorte de 74 pacientes con cáncer y COVID-19 internados en una institución oncológica. El 87.8% tenía diagnóstico de tumores sólidos y 12.2% oncohematológicos. Entre los tumores sólidos, el 61.5% presentó enfermedad metastásica. El 78.3% (N = 58) tenía infiltrados pulmonares al diagnóstico de COVID-19. La infección fue intrahospitalaria en 20 pacientes. Habían recibido tratamiento antineoplásico dentro de los 30 días anteriores al diagnóstico 39 pacientes (52.7%); uno se encontraba recibiendo radioterapia. Veinticuatro pacientes (32.4%) se derivaron a terapia intensiva (UTI) y 18 (75%) de ellos requirieron asistencia respiratoria mecánica (ARM). La mortalidad general durante la internación fue 32.4% (N = 24). La mortalidad en UTI fue 62.5% (N = 15). La mortalidad en ARM fue 72.2% (N = 13). La edad, recuento de neutrófilos, índice neutrófilo/linfocito, dímero D, ferritina, tabaquismo y haber adquirido la infección durante la internación resultaron estadísticamente significativos en el análisis univariado para mortalidad. No hallamos diferencias en mortalidad por estadio de enfermedad, en los pacientes con tumores sólidos, ni por haber recibido tratamiento antineoplásico dentro de los 30 días del diagnóstico de COVID-19. En el análisis multivariado con el modelo de regresión logística, solo la edad y el tabaquismo fueron predictores de mortalidad. Los odds ratios (IC 95) ajustados para la edad =65 años y el tabaquismo fueron 8.87 (1.35-58.02) y 8.64 (1.32-56.64), respectivamente. Este trabajo puede resultar de utilidad para instituciones polivalentes que asistan pacientes oncológicos durante la pandemia.

Evolución clínica de pacientes internados con cáncer e infección por COVID-19 / Clinical outcomes in cancer patients hospitalized with COVID-19

Resumen Los pacientes con cáncer y COVID-19 tienen más complicaciones que la población general. Comunicamos una cohorte de 74 pacientes con cáncer y COVID-19 internados en una institución on cológica. El 87.8% tenía diagnóstico de tumores sólidos y 12.2% oncohematológicos. Entre los tumores sólidos, el 61.5% presentó enfermedad metastásica. El 78.3% (N = 58) tenía infiltrados pulmonares al diagnóstico de COVID-19. La infección fue intrahospitalaria en 20 pacientes. Habían recibido tratamiento antineoplásico den tro de los 30 días anteriores al diagnóstico 39 pacientes (52.7%); uno se encontraba recibiendo radioterapia. Veinticuatro pacientes (32.4%) se derivaron a terapia intensiva (UTI) y 18 (75%) de ellos requirieron asistencia respiratoria mecánica (ARM). La mortalidad general durante la internación fue 32.4% (N = 24). La mortalidad en UTI fue 62.5% (N = 15). La mortalidad en ARM fue 72.2% (N = 13). La edad, recuento de neutrófilos, índice neutrófilo/linfocito, dímero D, ferritina, tabaquismo y haber adquirido la infección durante la internación resultaron estadísticamente significativos en el análisis univariado para mortalidad. No hallamos diferencias en mortalidad por estadio de enfermedad, en los pacientes con tumores sólidos, ni por haber recibido tratamiento antineoplá sico dentro de los 30 días del diagnóstico de COVID-19. En el análisis multivariado con el modelo de regresión logística, solo la edad y el tabaquismo fueron predictores de mortalidad. Los odds ratios (IC 95) ajustados para la edad ≥65 años y el tabaquismo fueron 8.87 (1.35-58.02) y 8.64 (1.32-56.64), respectivamente. Este trabajo puede resultar de utilidad para instituciones polivalentes que asistan pacientes oncológicos durante la pandemia.

Abstract Cancer patients are exposed to more complications from COVID-19 than non-cancer patients. We report a cohort of 74 cancer patients (87.8% with solid neoplasia and 12.2% with hematological diseases) with COVID-19 infection admitted to a tertiary medical cancer center in Argentina. Pulmonary infiltrates were diagnosed at admission in 78.3% (N = 58) of the cases. COVID-19 infection was hospital-acquired in 20 (27.0%) patients. Thirty-nine patients (52.7%) received anticancer therapy within the 30 days prior to COVID-19 diagnosis; one was on radiation therapy. Twenty-four (32.4%) patients were admitted in the intensive care unit (ICU) and 18 (75.0%) required mechanical ventilation. All cause in-hospital mortality was 32.4% (N = 24) and ICU mortality was 62.5% (N = 15). Mortality under me chanical ventilation was 72.2% (N = 13). In the univariate analysis age, neutrophil count, neutrophil/lymphocyte index, D-dimer, ferritin, smoking, and nosocomial acquired infection were associated with in-hospital mortality. There were no statistically significant differences in mortality related to disease stage for solid tumors, neither cancer treatment within 30 days of COVID-19 diagnosis. Age and smoking were associated with mortality in the multivariate analysis. The adjusted odds ratios (95 CI) for age ≥ 65 years and smoking were 8.87 (1.35-58.02) and 8.64 (1.32 - 56.64), respectively. Our experience can be useful for other institutions that assist cancer patients during the pandemic.

Vitamin D deficiency in patients admitted to the general ward with breast, lung, and colorectal cancer in Buenos Aires, Argentina.

UNLABELLED: A high prevalence of hypovitaminosis D has been reported in cancer patients. Low levels of 25-(OH)-vitamin D were found in 158 of 162 (97.5%) inpatients with breast, lung, and colorectal cancer under active treatment, with severe deficiency (<20 ng/ml) in 77.2% and mild deficiency (20-30 ng/ml) in 20.4%. PURPOSE: A high prevalence of vitamin D deficiency has been reported in cancer patients. Nevertheless, vitamin D serum levels have been checked in few patients. Information about the frequency of hypovitaminosis D in cancer patients in Argentina is unknown. The aim of the study was to assess the frequency of vitamin D deficiency in patients with breast, lung, and colorectal cancer. METHODS: A prospective observational study was designed for cancer patients admitted to the general ward in 2014. The patients included had breast, lung, and colorectal cancer. All of them were under active treatment. The serum level of 25-(OH)-vitamin D [25-(OH)-D] was measured and categorized as sufficiency (>30 ng/ml), mild deficiency (20-30 ng/ml), and severe deficiency (<20 ng/ml). RESULTS: A total of 162 patients were included, 98.2% were in stages III-IV. Median level of 25-(OH)-D was 15.3 ng/ml (range 4.1-103.6 ng/ml). Serum levels <30 ng/ml were found in 158 (97.5%) patients, severe deficiency in 125 cases (77.2%) and mild deficiency in 33 cases (20.4%). In patients under chemo/hormone therapy, the median level was 15.3 ng/ml (range 4.1-103.6 ng/ml) and in those under concurrent therapy was 17.1 ng/ml (range 7.4-58.5 ng/ml); p = 0.1944. There were no statistical differences in severe or mild deficiency of vitamin D among breast, lung, and colorectal cancer patients. CONCLUSION: The study found a high prevalence of vitamin D deficiency in hospitalized cancer patients under active treatment. Many authors have recommended dosing vitamin D levels in this population; normalizing serum levels is difficult.

[Hyponatremia as a risk factor of death in patients with community-acquired pneumonia requiring hospitalization]. / Hiponatremia como factor de riesgo de muerte en pacientes internados por neumonia adquirida en la comunidad.

We investigated whether hyponatremia is a risk factor of death in patients hospitalized with community-acquired pneumonia (CAP) and estimated the relative risk of death by CAP of other risk factors. The design was prospective multicentre cohort study. In 5 centers in Buenos Aires, Argentina, we studied adults hospitalized with CAP between March 21, 2000 and December 21, 2000. Using stepwise logistic regression, we analyzed risk factors that showed a univariate association with mortality; alpha significance level was 0.05. During a 9-month period, 238 patients were admitted with CAP: 150 (63%) male and 88 (36%) female, mean age 52.99 (+/-20.35) and 55.06 (+/-20.94), respectively. Mortality was 10.5% (25/238). By multivariate analysis, the following variables were statistically associated with evolution: cerebrovascular disease (CD) (B: 2.614, p < 0.001, RRE: 13.6, IC 95%: 3.7-49.6); hyponatremia at admission or during hospitalization (B: 1.994, p<0.001, RRE: 7.3, IC 95%: 2.5-20.8); and elevated blood urea (B: 0.016, p= 0.003, RRE: 1.016, IC 95%: 1.005-1.02). We developed a formula to predict mortality by CAP: P (death) = 1/1 + exp - (-4.03 + 2.61 x l + 1.99 x 2 + 0.016x3), where: x1=CD (yes = 1/ no=0); x2= hyponatremia (yes = 1/ no=0); x3 = blood urea (mg/dl). The predictability was 91.1%. The mortality risk by CAP was statistically higher in patients with CD, hyponatremia and elevated blood urea.

Hiponatremia como factor de riesgo de muerte en pacientes internados por neumonia adquirida en la comunidad / Hyponatremia as a risk factor of death in patients with community-acquired pneumonia requiring hospitalization

Investigamos si la hiponatremia es un factor de riesgo de muerte en pacientes internados por neumoníaadquirida en la comunidad (NAC) y estimamos el peso relativo de otros factores de riesgo de muerte por NAC, en un estudio de cohorte, prospectivo, multicéntrico, en 5 Servicios de Clínica Médica del Area Metropolitana de Buenos Aires. Evaluamos adultos con NAC ingresados entre 21 de marzo de 2000 y 21 de diciembre del mismo año. Los factores de riesgo que mostraron asociación con evolución por análisis univariado, fueron sometidos a análisis de regresión logística, con un nivel de significación de α de 0.05. En 9 meses seinternaron 238 pacientes con NAC: 150 (63%) varones y 88 (36%) mujeres, con edades medias 52.99 (±20.35)y 55.06 (±20.94) años, respectivamente. Fallecieron 25/238 (10.5%). En análisis multivariado, se asociaron significativamente con evolución: enfermedad vascular encefálica (EVE) (B: 2.614, p<0.001, RRE: 13.6, IC 95%: 3.7-49.6); hiponatremia al ingreso o durante la internación (B: 1.994, p<0.001, RRE: 7.3, IC 95%: 2.5-20.8); urea plasmática elevada (B: 0.016, p= 0.003, RRE: 1.016, IC 95%: 1.005-1.02). Desarrollamos una fórmula deprobabilidad de fallecer por NAC: P (óbito)= 1/1+ exp. – (-4.03 + 2.61x1 + 1.99x2 + 0.016x3), donde: x1= EVE(sí =1/no =0); x2= hiponatremia (sí =1/no =0); x3 = urea plasmática (mg/dl). La predictibilidad fue 91.1%. Elriesgo de fallecer por NAC fue significativamente mayor entre quienes presentaron EVE, hiponatremia y ureaplasmática elevada

We investigated whether hyponatremia is a risk factor of death in patients hospitalized with community-acquired pneumonia (CAP) and estimated the relative risk of death by CAP of otherrisk factors. The design was prospective multicentre cohort study. In 5 centers in Buenos Aires, Argentina, westudied adults hospitalized with CAP between March 21, 2000 and December 21, 2000. Using stepwise logisticregression, we analyzed risk factors that showed a univariate association with mortality; α significance level was0.05. During a 9-month period, 238 patients were admitted with CAP: 150 (63%) male and 88 (36%) female,mean age 52.99 (±20.35) and 55.06 (±20.94), respectively. Mortality was 10.5% (25/238). By multivariate analysis, the following variables were statistically associated with evolution: cerebrovascular disease (CD) (B: 2.614,p<0.001, RRE: 13.6, IC 95%: 3.7-49.6); hyponatremia at admission or during hospitalization (B: 1.994, p<0.001, RRE: 7.3, IC 95%: 2.5-20.8); and elevated blood urea (B: 0.016, p= 0.003, RRE: 1.016, IC 95%: 1.005-1.02). We developed a formula to predict mortality by CAP: P (death) = 1/1+ exp – (-4.03 + 2.61x1 + 1.99x2 + 0.016x3), where: x1= CD (yes=1/no =0); x2= hyponatremia (yes=1/no =0); x3 = blood urea (mg/dl). The predictability was 91.1%. The mortality risk by CAP was statistically higher in patients with CD, hyponatremia and elevated blood urea

Hiponatremia como factor de riesgo de muerte en pacientes internados por neumonia adquirida en la comunidad / Hyponatremia as a risk factor of death in patients with community-acquired pneumonia requiring hospitalization

Investigamos si la hiponatremia es un factor de riesgo de muerte en pacientes internados por neumoníaadquirida en la comunidad (NAC) y estimamos el peso relativo de otros factores de riesgo de muerte por NAC, en un estudio de cohorte, prospectivo, multicéntrico, en 5 Servicios de Clínica Médica del Area Metropolitana de Buenos Aires. Evaluamos adultos con NAC ingresados entre 21 de marzo de 2000 y 21 de diciembre del mismo año. Los factores de riesgo que mostraron asociación con evolución por análisis univariado, fueron sometidos a análisis de regresión logística, con un nivel de significación de α de 0.05. En 9 meses seinternaron 238 pacientes con NAC: 150 (63%) varones y 88 (36%) mujeres, con edades medias 52.99 (±20.35)y 55.06 (±20.94) años, respectivamente. Fallecieron 25/238 (10.5%). En análisis multivariado, se asociaron significativamente con evolución: enfermedad vascular encefálica (EVE) (B: 2.614, p<0.001, RRE: 13.6, IC 95%: 3.7-49.6); hiponatremia al ingreso o durante la internación (B: 1.994, p<0.001, RRE: 7.3, IC 95%: 2.5-20.8); urea plasmática elevada (B: 0.016, p= 0.003, RRE: 1.016, IC 95%: 1.005-1.02). Desarrollamos una fórmula deprobabilidad de fallecer por NAC: P (óbito)= 1/1+ exp. ¹ (-4.03 + 2.61x1 + 1.99x2 + 0.016x3), donde: x1= EVE(sí =1/no =0); x2= hiponatremia (sí =1/no =0); x3 = urea plasmática (mg/dl). La predictibilidad fue 91.1%. Elriesgo de fallecer por NAC fue significativamente mayor entre quienes presentaron EVE, hiponatremia y ureaplasmática elevada (AU)

We investigated whether hyponatremia is a risk factor of death in patients hospitalized with community-acquired pneumonia (CAP) and estimated the relative risk of death by CAP of otherrisk factors. The design was prospective multicentre cohort study. In 5 centers in Buenos Aires, Argentina, westudied adults hospitalized with CAP between March 21, 2000 and December 21, 2000. Using stepwise logisticregression, we analyzed risk factors that showed a univariate association with mortality; α significance level was0.05. During a 9-month period, 238 patients were admitted with CAP: 150 (63%) male and 88 (36%) female,mean age 52.99 (±20.35) and 55.06 (±20.94), respectively. Mortality was 10.5% (25/238). By multivariate analysis, the following variables were statistically associated with evolution: cerebrovascular disease (CD) (B: 2.614,p<0.001, RRE: 13.6, IC 95%: 3.7-49.6); hyponatremia at admission or during hospitalization (B: 1.994, p<0.001, RRE: 7.3, IC 95%: 2.5-20.8); and elevated blood urea (B: 0.016, p= 0.003, RRE: 1.016, IC 95%: 1.005-1.02). We developed a formula to predict mortality by CAP: P (death) = 1/1+ exp ¹ (-4.03 + 2.61x1 + 1.99x2 + 0.016x3), where: x1= CD (yes=1/no =0); x2= hyponatremia (yes=1/no =0); x3 = blood urea (mg/dl). The predictability was 91.1%. The mortality risk by CAP was statistically higher in patients with CD, hyponatremia and elevated blood urea (AU)

Hiponatremia como factor de riesgo de muerte en pacientes internados por neumonia adquirida en la comunidad / Hyponatremia as a risk factor of death in patients with community-acquired pneumonia requiring hospitalization

Investigamos si la hiponatremia es un factor de riesgo de muerte en pacientes internados por neumoníaadquirida en la comunidad (NAC) y estimamos el peso relativo de otros factores de riesgo de muerte por NAC, en un estudio de cohorte, prospectivo, multicéntrico, en 5 Servicios de Clínica Médica del Area Metropolitana de Buenos Aires. Evaluamos adultos con NAC ingresados entre 21 de marzo de 2000 y 21 de diciembre del mismo año. Los factores de riesgo que mostraron asociación con evolución por análisis univariado, fueron sometidos a análisis de regresión logística, con un nivel de significación de α de 0.05. En 9 meses seinternaron 238 pacientes con NAC: 150 (63%) varones y 88 (36%) mujeres, con edades medias 52.99 (±20.35)y 55.06 (±20.94) años, respectivamente. Fallecieron 25/238 (10.5%). En análisis multivariado, se asociaron significativamente con evolución: enfermedad vascular encefálica (EVE) (B: 2.614, p<0.001, RRE: 13.6, IC 95%: 3.7-49.6); hiponatremia al ingreso o durante la internación (B: 1.994, p<0.001, RRE: 7.3, IC 95%: 2.5-20.8); urea plasmática elevada (B: 0.016, p= 0.003, RRE: 1.016, IC 95%: 1.005-1.02). Desarrollamos una fórmula deprobabilidad de fallecer por NAC: P (óbito)= 1/1+ exp. ¹ (-4.03 + 2.61x1 + 1.99x2 + 0.016x3), donde: x1= EVE(sí =1/no =0); x2= hiponatremia (sí =1/no =0); x3 = urea plasmática (mg/dl). La predictibilidad fue 91.1%. Elriesgo de fallecer por NAC fue significativamente mayor entre quienes presentaron EVE, hiponatremia y ureaplasmática elevada (AU)

We investigated whether hyponatremia is a risk factor of death in patients hospitalized with community-acquired pneumonia (CAP) and estimated the relative risk of death by CAP of otherrisk factors. The design was prospective multicentre cohort study. In 5 centers in Buenos Aires, Argentina, westudied adults hospitalized with CAP between March 21, 2000 and December 21, 2000. Using stepwise logisticregression, we analyzed risk factors that showed a univariate association with mortality; α significance level was0.05. During a 9-month period, 238 patients were admitted with CAP: 150 (63%) male and 88 (36%) female,mean age 52.99 (±20.35) and 55.06 (±20.94), respectively. Mortality was 10.5% (25/238). By multivariate analysis, the following variables were statistically associated with evolution: cerebrovascular disease (CD) (B: 2.614,p<0.001, RRE: 13.6, IC 95%: 3.7-49.6); hyponatremia at admission or during hospitalization (B: 1.994, p<0.001, RRE: 7.3, IC 95%: 2.5-20.8); and elevated blood urea (B: 0.016, p= 0.003, RRE: 1.016, IC 95%: 1.005-1.02). We developed a formula to predict mortality by CAP: P (death) = 1/1+ exp ¹ (-4.03 + 2.61x1 + 1.99x2 + 0.016x3), where: x1= CD (yes=1/no =0); x2= hyponatremia (yes=1/no =0); x3 = blood urea (mg/dl). The predictability was 91.1%. The mortality risk by CAP was statistically higher in patients with CD, hyponatremia and elevated blood urea (AU)