scholarly journals Postoperative Neutrophil-to-Lymphocyte Ratio Is Associated with Mortality in Adult Patients After Cardiopulmonary Bypass Surgery: A Cohort Study

2021 ◽  
Vol 27 ◽  
Author(s):  
Yanhong Zhu ◽  
Wenyong Peng ◽  
Shuai Zhen ◽  
Xiaofeng Jiang
Keyword(s):  
Cohort Study ◽  
Cardiopulmonary Bypass ◽  
Bypass Surgery ◽  
Adult Patients ◽  
Neutrophil To Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Cardiopulmonary Bypass Surgery

scholarly journals P0589 / #723: PREDICTORS OF MORTALITY IN CHILDREN WHO DEVELOPED SEPSIS AFTER CARDIOPULMONARY BYPASS SURGERY: A COHORT STUDY

2021 ◽  
Vol 22 (Supplement 1 3S) ◽  
pp. 290-290
Author(s):  
J. Lopez Kerlegand ◽  
K. Navar Gallegos ◽  
M. Ibarra Sarlat ◽  
R. Cruz Floriano ◽  
M. Labra Zamora ◽  
...  
Keyword(s):  
Cohort Study ◽  
Cardiopulmonary Bypass ◽  
Bypass Surgery ◽  
Predictors Of Mortality ◽  
Cardiopulmonary Bypass Surgery

Prevalence of Heparin-Associated Antibodies Without Thrombosis in Patients Undergoing Cardiopulmonary Bypass Surgery

Circulation ◽  
1997 ◽  
Vol 95 (5) ◽  
pp. 1242-1246 ◽  
Author(s):  
Thomas L. Bauer ◽  
Gowthami Arepally ◽  
Barbara A. Konkle ◽  
Bernadette Mestichelli ◽  
Sandor S. Shapiro ◽  
...  
Keyword(s):  
Cardiopulmonary Bypass ◽  
Bypass Surgery ◽  
Cardiopulmonary Bypass Surgery

scholarly journals Predictive value of the neutrophil to lymphocyte ratio for disease deterioration and serious adverse outcomes in patients with COVID-19: a prospective cohort study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhi-Yong Zeng ◽  
Shao-Dan Feng ◽  
Gong-Ping Chen ◽  
Jiang-Nan Wu
Keyword(s):  
Cohort Study ◽  
Hospital Admission ◽  
Clinical Outcomes ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Characteristic Curve ◽  
Adverse Outcomes ◽  
Neutrophil To Lymphocyte Ratio ◽  
Predictive Values ◽  
Lymphocyte Ratio

Abstract Background Early identification of patients who are at high risk of poor clinical outcomes is of great importance in saving the lives of patients with novel coronavirus disease 2019 (COVID-19) in the context of limited medical resources. Objective To evaluate the value of the neutrophil to lymphocyte ratio (NLR), calculated at hospital admission and in isolation, for the prediction of the subsequent presence of disease progression and serious clinical outcomes (e.g., shock, death). Methods We designed a prospective cohort study of 352 hospitalized patients with COVID-19 between January 9 and February 26, 2020, in Yichang City, Hubei Province. Patients with an NLR equal to or higher than the cutoff value derived from the receiver operating characteristic curve method were classified as the exposed group. The primary outcome was disease deterioration, defined as an increase of the clinical disease severity classification during hospitalization (e.g., moderate to severe/critical; severe to critical). The secondary outcomes were shock and death during the treatment. Results During the follow-up period, 51 (14.5%) patients’ conditions deteriorated, 15 patients (4.3%) had complicated septic shock, and 15 patients (4.3%) died. The NLR was higher in patients with deterioration than in those without deterioration (median: 5.33 vs. 2.14, P < 0.001), and higher in patients with serious clinical outcomes than in those without serious clinical outcomes (shock vs. no shock: 6.19 vs. 2.25, P < 0.001; death vs. survival: 7.19 vs. 2.25, P < 0.001). The NLR measured at hospital admission had high value in predicting subsequent disease deterioration, shock and death (all the areas under the curve > 0.80). The sensitivity of an NLR ≥ 2.6937 for predicting subsequent disease deterioration, shock and death was 82.0% (95% confidence interval, 69.0 to 91.0), 93.3% (68.0 to 100), and 92.9% (66.0 to 100), and the corresponding negative predictive values were 95.7% (93.0 to 99.2), 99.5% (98.6 to 100) and 99.5% (98.6 to 100), respectively. Conclusions The NLR measured at admission and in isolation can be used to effectively predict the subsequent presence of disease deterioration and serious clinical outcomes in patients with COVID-19.

scholarly journals Pulmonary infection after cardiopulmonary bypass surgery in children: a risk estimation model in China

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Chunnian Ren ◽  
Chun Wu ◽  
Zhengxia Pan ◽  
Quan Wang ◽  
Yonggang Li
Keyword(s):  
Risk Factors ◽  
Cardiopulmonary Bypass ◽  
Prediction Model ◽  
Congenital Heart ◽  
Bypass Surgery ◽  
Pulmonary Infection ◽  
Regression Analyses ◽  
Cardiopulmonary Bypass Surgery ◽  
Independent Risk Factors ◽  
Individualized Prediction

Abstract Objectives The occurrence of pulmonary infection after congenital heart disease (CHD) surgery can lead to significant increases in intensive care in cardiac intensive care unit (CICU) retention time, medical expenses, and risk of death risk. We hypothesized that patients with a high risk of pulmonary infection could be screened out as early after surgery. Hence, we developed and validated the first risk prediction model to verify our hypothesis. Methods Patients who underwent CHD surgery from October 2012 to December 2017 in the Children’s Hospital of Chongqing Medical University were included in the development group, while patients who underwent CHD surgery from December 2017 to October 2018 were included in the validation group. The independent risk factors associated with pulmonary infection following CHD surgery were screened using univariable and multivariable logistic regression analyses. The corresponding nomogram prediction model was constructed according to the regression coefficients. Model discrimination was evaluated by the area under the receiver operating characteristic curve (ROC) (AUC), and model calibration was conducted with the Hosmer-Lemeshow test. Results The univariate and multivariate logistic regression analyses identified the following six independent risk factors of pulmonary infection after cardiac surgery: age, weight, preoperative hospital stay, risk-adjusted classification for congenital heart surgery (RACHS)-1 score, cardiopulmonary bypass time and intraoperative blood transfusion. We established an individualized prediction model of pulmonary infection following cardiopulmonary bypass surgery for CHD in children. The model displayed accuracy and reliability and was evaluated by discrimination and calibration analyses. The AUCs for the development and validation groups were 0.900 and 0.908, respectively, and the P-values of the calibration tests were 0.999 and 0.452 respectively. Therefore, the predicted probability of the model was consistent with the actual probability. Conclusions Identified the independent risk factors of pulmonary infection after cardiopulmonary bypass surgery. An individualized prediction model was developed to evaluate the pulmonary infection of patients after surgery. For high-risk patients, after surgery, targeted interventions can reduce the risk of pulmonary infection.

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