Hypochloraemia is associated with 28-day mortality in patients with septic shock: a retrospective analysis of a multicentre prospective registry

2020 ◽  
pp. emermed-2019-209239
Author(s):  
Min Sung Lee ◽  
Tae Gun Shin ◽  
Won Young Kim ◽  
You Hwan Jo ◽  
Yoon Jung Hwang ◽  
...  
Keyword(s):  
Septic Shock ◽  
Retrospective Analysis ◽  
Logistic Regression Model ◽  
Primary Outcome ◽  
Albumin Level ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Acid Base ◽  
Failure Assessment ◽  
The Republic

ObjectivesHyperchloraemia is associated with poor clinical outcomes in sepsis patients; however, this association is not well studied for hypochloraemia. We investigated the prevalence of chloride imbalance and the association between hypochloraemia and 28-day mortality in ED patients with septic shock.MethodsA retrospective analysis of data from 11 multicentre EDs in the Republic of Korea prospectively collected from October 2015 to April 2018 was performed. Initial chloride levels were categorised as hypochloraemia, normochloraemia and hyperchloraemia, according to sodium chloride difference adjusted criteria. The primary outcome was 28-day mortality. A multivariate logistic regression model adjusting for age, sex, comorbidities, acid-base state, sepsis-related organ failure assessment (SOFA) score, lactate and albumin level was used to test the association between the three chloride categories and 28-day mortality.ResultsAmong 2037 enrolled patients, 394 (19.3%), 1582 (77.7%) and 61 (3.0%) patients had hypochloraemia, normochloraemia and hyperchloraemia, respectively. The unadjusted 28-day mortality rate in patients with hypochloraemia was 27.4% (95% CI, 23.1% to 32.1%), which was higher than in patients with normochloraemia (19.7%; 95% CI, 17.8% to 21.8%). Hypochloraemia was associated with an increase in the risk of 28-day mortality (adjusted OR (aOR), 1.36, 95% CI, 1.00 to 1.83) after adjusting for confounders. However, hyperchloraemia was not associated with 28-day mortality (aOR 1.35, 95% CI, 0.82 to 2.24).ConclusionHypochloraemia was more frequently observed than hyperchloraemia in ED patients with septic shock and it was associated with 28-day mortality.

scholarly journals Clinical Outcomes of Adult Patients Hospitalized with COVID-19 after Vaccination

2021 ◽  
Vol 6 (4) ◽  
pp. 175
Author(s):  
Markos Kalligeros ◽  
Fadi Shehadeh ◽  
Evangelia K. Mylona ◽  
Matthew Kaczynski ◽  
Saisanjana Kalagara ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Clinical Outcomes ◽  
Logistic Regression Model ◽  
Primary Outcome ◽  
Adult Patients ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Absolute Priority ◽  
Risk Of Death

Vaccination remains the most effective way to prevent COVID-19. The aim of the present study was to assess the incidence of COVID-19 hospitalizations after vaccination, as well as the effect of prior vaccination on hospitalization outcomes among patients with COVID-19. We analyzed and compared all consecutive patients, with or without prior vaccination, who were admitted to our hospital network due to COVID-19 from January to April 2021. Our primary outcome was to identify and describe cases of COVID-19 hospitalized after vaccination. We also utilized a multivariate logistic regression model to investigate the association of previous vaccination with hospitalization outcomes. We identified 915 consecutive patients hospitalized due to COVID-19 with 91/915 (10%) previously vaccinated with at least one dose of a COVID-19 vaccine. Utilizing our multivariate logistic regression model, we found that prior vaccination, regardless of the number of doses or days since vaccination, was associated with decreased mortality (aOR 0.44, 95% CI: 0.20–0.98) when compared to unvaccinated individuals. Our study showed that COVID-19 related hospitalization after vaccination may occur to a small percentage of patients, mainly those who are partially vaccinated. However, our findings underline that prior vaccination, even when partial, is associated with a decreased risk of death. Ongoing vaccination efforts should remain an absolute priority.

Abstract 328: Cardiovascular Disease Associated with Ability to Achieve Renal Transplant and Post-Transplant Adverse Events

2015 ◽  
Vol 8 (suppl_2) ◽  
Author(s):  
Sahar J Ismail ◽  
Meet Patel ◽  
Ryan Gindi ◽  
Ahmad Salah ◽  
Ignatius Tang ◽  
...  
Keyword(s):  
Renal Transplant ◽  
Regression Model ◽  
Graft Failure ◽  
Logistic Regression Model ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Post Transplant ◽  
History Of

Introduction: Patients with end stage renal disease suffer from a high burden of cardiovascular disease (CVD). Renal transplant offers mortality and morbidity benefits. Hypothesis: We predict that patients with CVD are less likely to obtain a renal transplant after being listed and that CVD may be associated with post-transplant adverse events. Methods: We conducted a retrospective analysis of all adult patients listed for first time renal transplantation at the University Of Illinois Chicago from 2002 till 2006. We defined Coronary Artery Disease (CAD) as a history of myocardial infarction or coronary revascularization. We defined reduced ejection fraction (rEF) as an EF less than or equal to 40%. CAD equivalents were defined as a history of diabetes, stroke or peripheral vascular disease. We assessed the outcome of achieving transplantation in a multivariate logistic regression model. We assessed post-transplant events of death or graft failure in a Cox proportional hazards regression model. Results: Of the 460 patients studied African-Americans accounted for 52% and men for 58%. CAD was present in 10.9% of patients and rEF was present in 9.6%. Pre-operative revascularization occurred in 8.9% of patients (74% percutaneous coronary intervention, 26% bypass surgery. Patients with CAD or a CAD equivalent were older (54.7 vs. 43.2 years old, p <0.01), had higher systolic blood pressure (147.2 vs. 140.6 mmHg, p<0.01) and lower diastolic blood pressure (79.3 vs. 83.6 mmHg, p<0.01). Beta-blocker (63% vs. 54%, p = 0.06) statin (45% vs. 11%, p<0.01) and aspirin (40% vs 12%, p<0.01) use was more common in those with CAD or equivalent. In a multivariate logistic regression model controlling for sex, medications, pre-operative revascularization, and comorbidities, age (OR 0.975, 95% CI 0.954 to 0.997, p = 0.03) and history of CAD (OR 0.385 95% CI 0.159 to 0.932, p= 0.03) were associated with lower odds of receiving transplant. In a Cox proportional hazards model controlling for age, sex, pre-operative revascularization, type of transplant, and comorbidities, CAD (HR 2.56 95% CI 1.08 - 6.10, p = 0.03) and rEF (HR 2.37 95% CI 1.06 - 5.35, p = 0.03) were associated with an increased hazard of graft failure or death. Of 337 patients that received transplant only 4 peri-operative myocardial infarcts and 1 stroke occurred. Conclusions: CVD is common in patients listed for renal transplant. CAD is independently associated with lower odds of receiving a transplant. CAD and rEF are independently associated with increased hazard of post-transplant death or graft failure. Future efforts should focus measures to optimize outcomes in patients with CVD awaiting transplant.

Identification of characteristics associated with long-term survival in patients with metastatic urothelial carcinoma (mUC) who received durvalumab (D) with or without tremelimumab (T) in clinical studies.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 441-441
Author(s):  
Marie Alt ◽  
Carlos Stecca ◽  
Shaum Kabadi ◽  
Benga Kazeem ◽  
Srikala S. Sridhar
Keyword(s):  
Logistic Regression ◽  
Phase I ◽  
Regression Model ◽  
Clinical Studies ◽  
Logistic Regression Model ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Term Survival ◽  
Long Term Survival

441 Background: Immune checkpoint inhibitors (ICI) have changed the landscape of mUC, yet outcomes are variable as some patients (pts) do not respond to treatment while others have a durable response. To optimally select pts who may derive benefit from ICIs, predictive factors are required. This retrospective, post-hoc analysis evaluated pt characteristics to determine differences between short and long-term survivors among pts with mUC who received D (anti–PD-L1) with or without T (anti–CTLA-4) in two clinical studies. Methods: Pts with platinum-refractory mUC who received D monotherapy in the phase I/II study 1108 (10 mg/kg Q2W, up to 12 mo) or D+T in the phase I study 10 (D at 20 mg/kg + T at 1 mg/kg Q4W for 4 mo, then D at 10 mg/kg Q2W for 12 mo) were included. Pt characteristics, tumor characteristics, radiological assessments, and biological assessments were collected. The primary outcome measure was long-term overall survival (OS). Pts were categorized as OS ≥2 yrs (from 1st dose of study drug) or OS <2 yrs. A univariate analysis was conducted on each baseline characteristic to assess independent associations with long-term OS; a multivariate logistic regression model was employed including each variable with a p-value ≤0.1 as factors or covariates. Results: A total of 367 pts with mUC were included in the analysis: 88 (24.0%) had OS ≥2 yrs (range: 2.09–4.99) and 279 (76.0%) had OS <2 yrs (range: 0.03–1.98). Pts with OS ≥2 yrs had a significantly higher objective response rates than those with OS <2 yrs (71.6% vs 5.7%; p<0.0001) and a significantly longer duration of response (median 2.3 yrs vs 0.39 yrs; p<0.0001). The characteristics included in the multivariate logistic regression model are listed in the Table. Long-term OS was significantly associated with ECOG PS, PD-L1 status, baseline hemoglobin level, and baseline absolute neutrophils count. Conclusions: Our analyses show that several characteristics, including tumor response to treatment, are associated with long-term OS for pts with mUC treated with D or D+T. Further investigation into these and other characteristics may provide additional insights into long-term survival outcomes with ICIs. [Table: see text]

scholarly journals A nomogram for predicting mortality in patients with COVID-19 and solid tumors: a multicenter retrospective cohort study

2020 ◽  
Vol 8 (2) ◽  
pp. e001314
Author(s):  
Chao Liu ◽  
Li Li ◽  
Kehan Song ◽  
Zhi-Ying Zhan ◽  
Yi Yao ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Solid Tumors ◽  
Neutrophil Count ◽  
Mortality Risk ◽  
Logistic Regression Model ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Lemeshow Test ◽  
Wbc Count

BackgroundIndividualized prediction of mortality risk can inform the treatment strategy for patients with COVID-19 and solid tumors and potentially improve patient outcomes. We aimed to develop a nomogram for predicting in-hospital mortality of patients with COVID-19 with solid tumors.MethodsWe enrolled patients with COVID-19 with solid tumors admitted to 32 hospitals in China between December 17, 2020, and March 18, 2020. A multivariate logistic regression model was constructed via stepwise regression analysis, and a nomogram was subsequently developed based on the fitted multivariate logistic regression model. Discrimination and calibration of the nomogram were evaluated by estimating the area under the receiver operator characteristic curve (AUC) for the model and by bootstrap resampling, a Hosmer-Lemeshow test, and visual inspection of the calibration curve.ResultsThere were 216 patients with COVID-19 with solid tumors included in the present study, of whom 37 (17%) died and the other 179 all recovered from COVID-19 and were discharged. The median age of the enrolled patients was 63.0 years and 113 (52.3%) were men. Multivariate logistic regression revealed that increasing age (OR=1.08, 95% CI 1.00 to 1.16), receipt of antitumor treatment within 3 months before COVID-19 (OR=28.65, 95% CI 3.54 to 231.97), peripheral white blood cell (WBC) count ≥6.93 ×109/L (OR=14.52, 95% CI 2.45 to 86.14), derived neutrophil-to-lymphocyte ratio (dNLR; neutrophil count/(WBC count minus neutrophil count)) ≥4.19 (OR=18.99, 95% CI 3.58 to 100.65), and dyspnea on admission (OR=20.38, 95% CI 3.55 to 117.02) were associated with elevated mortality risk. The performance of the established nomogram was satisfactory, with an AUC of 0.953 (95% CI 0.908 to 0.997) for the model, non-significant findings on the Hosmer-Lemeshow test, and rough agreement between predicted and observed probabilities as suggested in calibration curves. The sensitivity and specificity of the model were 86.4% and 92.5%.ConclusionIncreasing age, receipt of antitumor treatment within 3 months before COVID-19 diagnosis, elevated WBC count and dNLR, and having dyspnea on admission were independent risk factors for mortality among patients with COVID-19 and solid tumors. The nomogram based on these factors accurately predicted mortality risk for individual patients.

Does radiation therapy increase late cardiac death in patients with left breast cancer?

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 1127-1127
Author(s):  
Chi Lin ◽  
Kyle A. Denniston ◽  
Mary E. Charlton
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Logistic Regression ◽  
Radiation Therapy ◽  
Cardiac Death ◽  
Lower Risk ◽  
Logistic Regression Model ◽  
Left Breast ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression

1127 Background: The objective of this study was to evaluate the effect of external beam radiation therapy (RT) on late cardiac death (CD) in patients with left breast cancer. Methods: A total of 529,246 patients who were diagnosed with adenocarcinoma of the breast between 1983 and 2004 and survived ≥ 5 years were identified from the SEER database. After excluding patients who were male, had right breast cancer, received brachytherapy or had missing data, 163,894 patients remained. Examined risk factors for CD include age (≤49/50-59/60-69/70-100), race (white/non-white), stage (In situ/local/regional/distant), breast subsite (nipple and areola/inner quadrant/outer quadrant), diagnosis year (1983-1993/1994-2004), surgery status (none/less than mastectomy/mastectomy) and RT. Time to CD was evaluated using the Kaplan-Meier method. A multivariate logistic regression model was used to evaluate factors associated with the use of RT and the Cox Proportional Hazards model was used to evaluate risk factors for CD. Results: A multivariate logistic regression model revealed that patients who received RT tended to be younger, white, more recently diagnosed, have inner quadrant and more advanced disease and undergo less than mastectomy. Median overall survival for patients with RT was significantly longer than those without RT (263 vs. 226 months, Log-Rank p < .0001). RT group had a lower risk of CD than no-RT group (Log-Rank p < .0001). Median time to CD was not reached in either group. The probability of CD was increased with increasing age and stage, and decreased with more recent diagnosis year and after mastectomy. Cox model found RT to be associated with lower probability of CD (HR 0.66, 95% CI 0.62-0.70), after adjusting for age, stage, surgery status and diagnosis year. Race and breast subsite were not associated with CD. Conclusions: Patients with left breast cancer who survived ≥ 5 years and received RT had a lower risk of cardiac death than those who did not. The cause of this difference is unclear but suggests influence from an uninvestigated factor, potentially the increased use of cardiotoxic chemotherapy or other cardiovascular comorbidity in those patients not receiving RT. Continued study, accounting for such factors, is warranted.

scholarly journals Early Prediction of the Carbapenem Resistance Gram-negative Bacteria Carriage in Intensive Care Unit using Machine-Learning

2020 ◽  
Author(s):  
Qiqiang Liang ◽  
Qinyu Zhao ◽  
Xin Xu ◽  
Yu Zhou ◽  
Man Huang
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Carbapenem Resistance ◽  
Multivariate Logistic Regression Model ◽  
Gram Negative Bacteria ◽  
Multivariate Logistic Regression ◽  
Gram Negative ◽  
Better Than

Abstract Background The prevention and control of carbapenem-resistance gram-negative bacteria (CR-GNB) is the difficulty and focus for clinicians in the intensive care unit (ICU). This study construct a CR-GNB carriage prediction model in order to predict the CR-GNB incidence in one week. Methods The database is comprised of nearly 10,000 patients. the model is constructed by the multivariate logistic regression model and three machine learning algorithms. Then we choose the optimal model and verify the accuracy by daily predicted and recorded the occurrence of CR-GNB of all patients admitted for 4 months. Results There are 1385 patients with positive CR-GNB cultures and 1535 negative patients in this study. Forty-five variables have statistical significant differences. We include the 17 variables in the multivariate logistic regression model and build three machine learning models for all variables. In terms of accuracy and the area under the receiver operating characteristic (AUROC) curve, the random forest is better than XGBoost and multivariate logistic regression model, and better than decision tree model (accuracy: 84% >82%>81%>72%), (AUROC: 0.9089 > 0.8947 ≈ 0.8987 > 0.7845). In the 4-month prospective study, 81 cases were predicted to be positive in CR-GNB culture within 7 days, 146 cases were predicted to be negative, 86 cases were positive, and 120 cases were negative, with an overall accuracy of 84% and AUROC of 91.98%. Conclusions Prediction models by machine learning can predict the occurrence of CR-GNB colonization or infection within a week period, and can real-time predict and guide medical staff to identify high-risk groups more accurately.

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