scholarly journals P1174STUDY ON THE RELATIONSHIP BETWEEN HYPOCHLOREMIA AND ALL-CAUSE DEATH IN PATIENTS RECEIVING CONTINUOUS AMBULATORY PERITONEAL DIALYSIS

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Tao Xu ◽  
Niansong Wang ◽  
Cheng Qiao
Keyword(s):  
Logistic Regression ◽  
Risk Factor ◽  
Peritoneal Dialysis ◽  
Continuous Ambulatory Peritoneal Dialysis ◽  
Roc Curve ◽  
Independent Risk Factor ◽  
Chloride Level ◽  
Kaplan Meier ◽  
Serum Chloride ◽  
The Relationship

Abstract Background and Aims To investigate the relationship between hypochloremia on all-cause death in patients receiving continuous ambulatory peritoneal dialysis (CAPD). Method 300 CAPD patients from January 2013 to December 2019 in the Sixth People's Hospital affiliated to Shanghai Jiaotong University. According to the serum chloride level, the patients were divided into two groups: hypochloremia group (serum chlorine ≤ 96mmol / L, n = 135) and normal chloride group (106mmol / L < serum chlorine > 96mmol / L, n = 165). The endpoint was all-cause death. We used the receiver-operating characteristic (ROC) curve to analysis the diagnostic value and logistic regression to assess the predictive value in relation to serum chloride with all-cause death in CAPD patients. Kaplan Meier curve was used to evaluate the effect of serum chloride on all-cause death survival analysis. All statistics were analyzed by SPSS 20.0 software, P < 0.05, indicating significant difference. Results 114 cases of all-cause death occurred in CAPD patients during follow-up (62.1 ± 11.1 months). The results of correlation analysis showed that serum chloride was positively correlated with serum sodium and potassium (r=0.721,0.199, P=0.001) and the negative correlation between serum chloride and dialysis age and serum phosphorus (r=-0.321, - 0.300, P=0.001). ROC curve analysis showed that serum chloride was statistically significant in predicting all-cause death in CAPD patients (AUC = 0.666, 95% Cl = 0.601-0.730, sensitivity / specificity = 64.6% / 59.8%, best threshold = 95.5mmol/l). Kaplan Meier analysis of all-cause death risk curve shows that the incidence of all-cause death in the low chloride group is higher than that in the normal serum chloride group. Logistic regression analysis showed that low chloride level was an independent risk factor for all-cause death in CAPD patients. Conclusion Hypochloremia is an independent risk factor for all-cause death in CAPD patients.

scholarly journals The Relationship between Alcohol Consumption and Incidence of Glycometabolic Abnormality in Middle-Aged and Elderly Chinese Men

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Siwen Zhang ◽  
Yujia Liu ◽  
Gang Wang ◽  
Xianchao Xiao ◽  
Xiaokun Gang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Risk Factor ◽  
Alcohol Consumption ◽  
Independent Risk Factor ◽  
Univariate Analysis ◽  
Middle Aged ◽  
Cross Sectional Survey ◽  
Chinese Men ◽  
Elderly Chinese ◽  
The Relationship

Aim. The relationship between alcohol consumption and glycometabolic abnormality is controversial, especially in different ethnic population. In this study, a cross-sectional survey was carried out to examine the relationship between alcohol consumption and glycometabolic abnormality in middle-aged and elderly Chinese men. Methods. Using cluster random sampling, Chinese men aged more than 40 years from Changchun, China, were given standardized questionnaires. In total, 1996 individuals, for whom complete data was available, were recruited into the study. We calculated the incidence of prediabetes and newly diagnosed diabetes by three levels of alcohol consumption: light, moderate, and heavy. Multivariate logistic regression models adjusted for socioeconomic variables and diabetes-related risk factors were used to analyze the association between alcohol consumption and the onset of prediabetes and diabetes. Results. The univariate analysis revealed higher incidence of prediabetes among drinkers (32.8%) compared with nondrinkers (28.6%), particularly in heavy alcohol consumers. The logistic regression analysis showed that alcohol consumption, especially heavy consumption, was an independent risk factor for prediabetes. Conclusions. Alcohol consumption, heavy consumption in particular, is an independent risk factor for the development of prediabetes, but not for diabetes.

scholarly journals PO-035 Association between sedentary behavior and diabetes mellitus in the prevalence of middle-aged and elderly people

2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Xinzheng Wang ◽  
Hongbin Luo
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Risk Factor ◽  
Sedentary Behavior ◽  
Elderly People ◽  
Independent Risk Factor ◽  
Sedentary Time ◽  
Middle Aged ◽  
The Relationship

Objective This study aims to explore the relationship between sedentary behavior and the diabetes mellitus prevalence of middle-aged and elderly people. Methods  we conduct a questionnaire survey and physical examination for a total of 3,000 middle-aged and elderly people (≥45 years old) ,analysing by he software of  SPSS21.0 and Stata12.0. Results The logistic regression analysis shows that the risk of diabetes is 1.617 (95% CI, 0.762-1.789, P <0.05) at 2-4h, 4-6h, 6-8h, ≥8h, = 0.003), 1.235 (95% CI, 0.818-1.865, P = 0.034), 3.420 (95% CI, 2.241-5.218, P = 0.000), 5.014 (95% CI, 3.049-8.247, P = 0.000). With each additional one-hour sedentariness the risk of diabetes increases by 23% (OR1.23, 95% CI 1.18-1.29, p <0.0001). Conclusions The sedentary behavior is an independent risk factor for diabetes. The prevalence of diabetes is gradually increasing with the increase of sedentary time, which indicates the longer sedentary time, the higher prevalence of diabetes.

scholarly journals Predictive value of three Inflammation-based Glasgow Prognostic Scores for major cardiovascular adverse events in patients with acute myocardial infarction during hospitalization: a retrospective study

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9068
Author(s):  
Houyong Zhu ◽  
Zhaodong Li ◽  
Xiaoqun Xu ◽  
Xiaojiang Fang ◽  
Tielong Chen ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Logistic Regression ◽  
Risk Factor ◽  
Roc Curve ◽  
Predictive Value ◽  
Independent Risk Factor ◽  
Prognostic Scores ◽  
All Cause Mortality ◽  
Grace Score

Aim Inflammation-based Glasgow Prognostic Scores (GPS) have been reported to predict the prognosis of patients with acute ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). The goal of this study was to investigate whether three kinds of GPSs can effectively predict major cardiovascular adverse events (MACEs) in STEMI or non-ST-segment elevation myocardial infarction (NSTEMI) patients undergoing PPCI, elective PCI (EPCI) or conservative drug therapy during hospitalization. Methods In this retrospective cohort study, patients with acute myocardial infarction (AMI) were divided into 0, 1 or 2 score according to the GPSs. Logistic regression and receiver operating characteristic (ROC) curve analysis were performed to assess the predictive value of GPSs for MACE and all-cause mortality during hospitalization. Three kinds of GPSs, Inflammation-based Glasgow Prognostic Score (GPS), modified GPS (MGPS) and high-sensitivity CRP-modified GPS (HS-MGPS) and Global Registry of Acute Coronary Events (GRACE) score were applied in this study. Results A total of 188 patients were enrolled. The ROC curve with MACE showed that the AUC of GPS (0.820 (95% confidence interval (CI) [0.754–0.885]), P < 0.001) was larger than that of MGPS (0.789 (95% CI [0.715–0.863]), P < 0.001), HS-MGPS (0.787 (95% CI [0.717–0.856]), P < 0.001) and GRACE score (0.743 (95% CI [0.672–0.814]), P < 0.001). The ROC curve with all-cause mortality showed that the AUC of GPS (0.696 (95% CI [0.561–0.831]), P = 0.005) was similar to the HS-MGPS (0.698 (95% CI [0.569–0.826]), P = 0.005) and higher than the MGPS (0.668 (95% CI [0.525–0.812]), P = 0.016), but lower than the GRACE score (0.812 (95% CI [0.734–0.889]), P < 0.001). Multivariate logistic regression analysis showed that the GPS was an independent risk factor for the incidence of MACE during hospitalization. Compared with the odds ratio (OR) value for a GPS of 0, the OR for a GPS of 1 was 7.173 (95% CI [2.425–21.216]), P < 0.001), and that for a GPS of 2 was 18.636 (95% CI [5.813–59.746]), P < 0.001), but not an independent risk factor for all-cause mortality (P = 0.302). GRACE score was an independent risk factor for MACE (1.019 (95% CI [1.004–1.035]), P = 0.015) and all-cause mortality (1.040 (95% CI [1.017–1.064]), P = 0.001). In the subgroups classified according to the type of AMI, the presence of disease interference GPSs and the type of PCI, the ability of GPS to predict the occurrence of MACE seemed to be greater than that of MGPS and HS-MGPS. Conclusion The GPS has a good predictive value for the occurrence of MACE during hospitalization in patients with AMI, regardless of STEMI or NSTEMI, the choice of PCI mode and the presence or absence of diseases that interfere with GPS. However, GPS is less predictive of all-cause mortality during hospitalization than GRACE score, which may be due to the interference of patients with other diseases.

scholarly journals Correlation analysis between preoperative systemic immune inflammation index and prognosis of patients after radical gastric cancer surgery: based on propensity score matching method

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Xu Zhaojun ◽  
Chen Xiaobin ◽  
An Juan ◽  
Yuan Jiaqi ◽  
Jiang Shuyun ◽  
...  
Keyword(s):  
Overall Survival ◽  
Risk Factor ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Roc Curve ◽  
Independent Risk Factor ◽  
Gastrointestinal Surgery ◽  
Kaplan Meier ◽  
Significant Difference ◽  
Immune Inflammation

Abstract Background To explore the correlation between the preoperative systemic immune inflammation index (SII) and the prognosis of patients with gastric carcinoma (GC). Methods The clinical data of 771 GC patients surgically treated in the Department of Gastrointestinal Surgery, Qinghai University Affiliated Hospital from June 2010 to June 2015 were retrospectively analyzed, and their preoperative SII was calculated. The optimal cut-off value of preoperative SII was determined using the receiver operating characteristic (ROC) curve, the confounding factors between the two groups were eliminated using the propensity score matching (PSM) method, and the correlation between preoperative SII and clinicopathological characteristics was assessed by chi-square test. Moreover, the overall survival was calculated using Kaplan-Meier method, the survival curve was plotted, and log-rank test was performed for the significance analysis between the curves. Univariate and multivariate analyses were also conducted using the Cox proportional hazards model. Results It was determined by the ROC curve that the optimal cut-off value of preoperative SII was 489.52, based on which 771 GC patients were divided into high SII (H-SII) group and low SII (L-SII) group, followed by PSM in the two groups. The results of Kaplan-Meier analysis showed that before and after PSM, the postoperative 1-, 3-, and 5-year survival rates in L-SII group were superior to those in H-SII group, and the overall survival rate had a statistically significant difference between the two groups (P < 0.05). Before PSM, preoperative SII [hazard ratio (HR) = 2.707, 95% confidence interval (CI) 2.074-3.533, P < 0.001] was an independent risk factor for the prognosis of GC patients. After 1:1 PSM, preoperative SII (HR = 2.669, 95%CI 1.881–3.788, P < 0.001) was still an independent risk factor for the prognosis of GC patients. Conclusions Preoperative SII is an independent risk factor for the prognosis of GC patients. The increase in preoperative SII in peripheral blood indicates a worse prognosis.

scholarly journals Correlation of Indoleamine-2,3-Dioxygenase and Chronic Kidney Disease: A Pilot Study

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Binbin Pan ◽  
Feng Zhang ◽  
Jian Sun ◽  
Dawei Chen ◽  
Wenjuan Huang ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Logistic Regression ◽  
Risk Factor ◽  
Pilot Study ◽  
Kidney Disease ◽  
Serum Creatinine ◽  
Roc Curve ◽  
Independent Risk Factor ◽  
Binary Logistic Regression ◽  
Indoleamine 2,3 Dioxygenase

Objective. To explore the correlation of indoleamine-2,3-dioxygenase (IDO) and chronic kidney disease (CKD). Methods. A total of 154 CKD patients and 42 non-CKD patients were recruited. Patients were grouped into ACR1~ACR3 (<30 mg/g, 30-300 mg/g, and >300 mg/g). Biomarkers in different groups were compared by ANOVA. Correlation was calculated by Pearson or Spearman analysis and binary logistic regression. The ROC curve was also performed. Results. The levels of albumin, serum creatinine (sCr), and IDO in non-CKD patients were significantly different from those in CKD3-CKD5 stages ( p < 0.05 ). IDO was correlated with age, proteinuria, ACR, and eGFR ( p < 0.01 ). After adjusting for CKD-related indices, ln(IDO) was an independent risk factor for CKD (3.48, p < 0.05 ). The analysis of ROC curve revealed a best cut­off for IDO was 0.0466 and yielded a sensitivity of 83.8% and a specificity of 75%. Hemoglobin, total protein, and albumin in the ACR1 group were significantly higher than those in the ACR2 and ACR3 groups ( p < 0.01 ), while sCr and IDO levels were significantly lower than those in the ACR2 and ACR3 groups ( p < 0.01 or p < 0.05 ). After adjusting for CKD-related indices, ln(IDO) was still an independent risk factor for ACR ( OR = 2.7 , p < 0.05 ). The analysis of ROC curve revealed a best cut­off for IDO was 0.075 and yielded a sensitivity of 71.9% and a specificity of 72.2%. Conclusion. IDO may be a promising biomarker to predict CKD and assess kidney function.

scholarly journals CONUT score is associated with mortality in patients with COVID-19: a retrospective study in Wuhan

2020 ◽  
Author(s):  
Ruoran Wang ◽  
Min He ◽  
Jirong Yue ◽  
Lang Bai ◽  
Dan Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Risk Factor ◽  
Logistic Regression Analysis ◽  
Roc Curve ◽  
Prognostic Value ◽  
Independent Risk Factor ◽  
Multivariate Logistic Regression Analysis ◽  
Operating Characteristics ◽  
Conut Score

Abstract Background The coronavirus disease 2019 (COVID-19) pneumonia, outbreak in Wuhan, China, has led to a global pandemic. The high mortality of COVID-19 patients makes it significant to evaluate possible disease progression. This study was designed to explore the prognostic value of Controlling Nutritional Status (CONUT) score in patients with COVID-19. Methods Patients diagnosed with COVID-19 of a single center in Wuhan, China from January 2020 to February 2020 were enrolled in this study. Logistic regression analysis was performed to find independent risk factor of mortality. Receiver operating characteristics (ROC) curve was drawn to evaluate the prognostic value of CONUT score. Results Among 442 included patients, there were 79 non-survivors with mortality of 17.9%. Compared with survivors, the median age (p < 0.001) and male ratio (p = 0.042) were higher in non-survivors. Non-survivors had higher incidence of comorbidities including hypertension (p < 0.001), chronic lung disease (p = 0.001) and cardiovascular disease (p = 0.005). Complications such as respiratory failure(p < 0.001), acute kidney injury (AKI) (p < 0.001) occurred more frequently in non-survivors. Multivariate logistic regression analysis showed that CONUT (p = 0.002), lactate dehydrogenase (LDH) (p < 0.001), C-reactive protein (CRP) (p = 0.020) were risk factor of mortality in COVID-19 patients. Area under the ROC curve (AUC) of CONUT and Nutrition risk screening 2002 (NRS2002) score were 0.813 and 0.795, respectively. Comprised of CONUT, LDH, CRP, the constructed prognostic model had higher AUC of 0.923 (Z = 3.5210, p < 0.001). Conclusion CONUT is an independent risk factor of mortality in COVID-19 patients. Evaluating CONUT is beneficial for clinicians to predict the progression of COVID-19 patients and strengthen monitoring and management to improve prognosis.

scholarly journals The relationship between leukocyte level and hypertension in elderly patients with hyperuricemia.

2020 ◽  
Author(s):  
Lijin Shen ◽  
Wei Zhao ◽  
Mingzhen Li ◽  
Bei Sun ◽  
Zhichao Zhou ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Risk Factor ◽  
Elderly Patients ◽  
Independent Risk Factor ◽  
Serum Uric Acid Level ◽  
Control Group ◽  
Multiple Logistic Regression ◽  
Cross Sectional ◽  
Increased Risk ◽  
The Relationship

Abstract Background : This study was to evaluate the change of leukocyte level caused by hyperuricemia and explore the relationship between leukocyte level and hypertension in elderly patients with hyperuricemia. Methods: A cross-sectional study of serum uric acid level was conducted in 1352 elderly people over 65 years old . The study samples were divided into three categories according to the tertiles of leukocyte: Tertile 1, leukocyte≤5.2 × 10 9 /L; Tertile 2, leukocyte=5.3~6.3 × 10 9 /L; and Tertile 3, leukocyte≥6.4 × 10 9 /L. Multiple logistic regression models were used for modeling relationships between leukocyte, hyperuricemia and hypertension. In vitro, human vascular endothelial cells (HUVECs) were treated by different concentrations of UA (0, 4, 8, 16 mg/dl) for 24 h, then cells were collected. Some cytokines were measured. Reactive oxygen species (ROS) were analyzed with a fluorescence microscope. Results: The levels of leukocyte were higher in elderly patients with hyperuricemia than without hyperuricemia( P <0.01). In multiple logistic regression, hyperuricemia was an independent risk factor of leukocyte in Tertile 3 (OR=1.657, 95%CI: 1.180～2.328, P =0.004). The prevalences of hypertension were higher in elderly patients with hyperuricemia than without hyperuricemia (77.0% vs 63.5%, χ 2 =11.447, P =0.001). In multiple logistic regression (Model 1), hyperuricemia was an independent risk factor of hypertension (OR=1.536, 95%CI: 1.026～2.302, P =0.037). Leukocyte in Tertile 3 was an independent risk factor of hypertension in Model 2 (OR= 1.333, 95%CI: 1.031~1.724, P =0.028). Expression levels of IL-1β, iNOS and TNF-α were obviously higher in the 8mg/dl UA group and 16mg/dl UA group than that in the control group ( P <0.05). Expression level of eNOS was obviously lower in the 8mg/dl UA group and 16mg/dl UA group than that in the control group ( P <0.05). The production of ROS in the 8mg/dl UA group and in the 16mg/dl UA group were obviously higher than that in the control group ( P <0.05). Conclusion: The present study demonstrated that hyperuricemia was associated with an increased risk for hypertension. The chronic inflammation caused by hyperuricemia maybe one of important pathogenesis of incident hypertension in patients with hyperuricemia.

scholarly journals Correlation Analysis Between Preoperative Systemic Immune Inflammation Index and Prognosis of Gastric Carcinoma Patients: Based on Propensity Score Matching Method

2021 ◽  
Author(s):  
Zhaojun Xu ◽  
Xiaobin Chen ◽  
Juan An ◽  
Jiaqi Yuan ◽  
Shuyun Jiang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Risk Factor ◽  
Propensity Score ◽  
Gastric Carcinoma ◽  
Propensity Score Matching ◽  
Roc Curve ◽  
Independent Risk Factor ◽  
Kaplan Meier ◽  
Significant Difference ◽  
Immune Inflammation

Abstract Background: To explore the correlation between the preoperative systemic immune inflammation index (SII) and the prognosis of patients with gastric carcinoma (GC).Methods: The clinical data of 771 GC patients surgically treated in the Department of Gastrointestinal Surgery, Qinghai University Affiliated Hospital from June 2010 to June 2015 were retrospectively analyzed, and their preoperative SII was calculated. The optimal cut-off value of preoperative SII was determined using the receiver operating characteristic (ROC) curve, the confounding factors between the two groups were eliminated using the propensity score matching (PSM) method, and the correlation between preoperative SII and clinicopathological characteristics was assessed by chi-square test. Moreover, the overall survival was calculated using Kaplan-Meier method, the survival curve was plotted, and log-rank test was performed for the significance analysis between the curves. Univariate and multivariate analyses were also conducted using the Cox proportional hazards model.Results: It was determined by the ROC curve that the optimal cut-off value of preoperative SII was 489.52, based on which 771 GC patients were divided into high SII (H-SII) group and low SII (L-SII) group, followed by PSM in the two groups. The results of Kaplan-Meier analysis showed that before and after PSM, the postoperative 1-, 3- and 5-year survival rates in L-SII group were superior to those in H-SII group, and the overall survival rate had a statistically significant difference between the two groups (P<0.05). Before PSM, preoperative SII [hazard ratio (HR) =2.707, 95% confidence interval (CI): 2.074-3.533, P<0.001] was an independent risk factor for the prognosis of GC patients. After 1:1 PSM, preoperative SII (HR=2.669, 95%CI: 1.881-3.788, P<0.001) was still an independent risk factor for the prognosis of GC patients.Conclusions: Preoperative SII is an independent risk factor for the prognosis of GC patients. The increase in preoperative SII in peripheral blood indicates a worse prognosis.

scholarly journals LDH, CRP and ALB predict nucleic acid turn negative within 14 days in symptomatic patients with COVID-19

2021 ◽  
pp. 003693302199424
Author(s):  
Gaoli Liu ◽  
Bicheng Zhang ◽  
Shaowen Zhang ◽  
Haifeng Hu ◽  
TingTing Liu
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Nucleic Acid ◽  
Hospital Stay ◽  
Prognostic Marker ◽  
Roc Curve ◽  
Prognostic Value ◽  
Statistical Significance ◽  
Biochemical Indicators ◽  
The Relationship

Aims To search for biochemical indicators that can identify symptomatic patients with COVID-19 whose nucleic acid could turn negative within 14 days, and assess the prognostic value of these biochemical indicators in patients with COVID-19. Patients and methods We collected the clinical data of patients with COVID-19 admitted to our hospital, by using logistic regression analysis and AUC curves, explored the relationship between biochemical indicators and nucleic acid positive duration, the severity of COVID-19, and hospital stay respectively. Results A total of two hundred and thirty-three patients with COVID-19 were enrolled in the study. We found patients whose nucleic acid turned negative within 14 days had lower LDH, CRP and higher ALB ( P < 0.05). ROC curve results indicated that lower LDH, TP, CRP and higher ALB predicted the nucleic acid of patients turned negative within 14 days with statistical significance( P < 0.05), AST, LDH, CRP and PCT predicted the severe COVID-19 with statistical significance, and CRP predicted hospital stay >31days with statistical significance ( P < 0.05). After verification, the probability of nucleic acid turning negative within 14 days in patients with low LDH (<256 U/L), CRP (<44.5 mg/L) and high ALB (>35.8 g/L) was about 4 times higher than that in patients with high LDH, CRP and low ALB ( P < 0.05). Conclusions LDH, CRP and ALB are useful prognostic marker for predicting nucleic acid turn negative within 14 days in symptomatic patients with COVID-19.

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