scholarly journals Correlation between Fasting Blood Glucose Level at Admission and Mortality in COVID-19 Patients: A Retrospective Study

2020 ◽  
Author(s):  
Bin Zhu ◽  
Chunguo Jiang ◽  
Xiaokai Feng ◽  
Yanfei Zheng ◽  
Jie Yang ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Blood Glucose ◽  
Fasting Blood Glucose ◽  
Proportional Hazard ◽  
Cox Proportional Hazard ◽  
Single Center Study ◽  
And Gender ◽  
Cox Proportional Hazard Regression ◽  
Relationship Of ◽  
The Relationship

Abstract Background Coronavirus disease-19 (COVID-19) has spread rapidly, with a growing number of cases confirmed around the world. This study explores the relationship of fasting blood glucose (FBG) at admission with mortality. Methods In this retrospective, single-center study, we analyzed the clinical characteristics of confirmed cases of COVID-19 in Wu Han from 29 January 2020 to 23 February 2020. Cox proportional hazard regression analysis was performed to evaluate the relationship between FBG and mortality. Results A total of 107 patients were enrolled in our study. The average age was 59.49 ± 13.33 and the FBG at admission was 7.35 ± 3.13 mmol/L. There were 16 people died of COVID-19 with an average age 68.1 ± 9.5 and the FBG was 8.94 ± 4.76 mmol/L. Regression analysis showed that there were significant association between FBG and death (HR = 1.13, 95%CI: 1.02-1.24). After adjusting for covariables, the significance still exists. In addition, our result showed that FBG > 7.0 mmol/L or diabetic mellitus can significantly increase mortality after adjusting for the age and gender. Conclusions This study suggests that FBG at admission is an effective and reliable indicator for disease prognosis in COVID-19 patients.

scholarly journals Correlation between Fasting Blood Glucose Level at Admission and Mortality in COVID-19 Patients: A Retrospective Study

2020 ◽  
Author(s):  
Bin Zhu ◽  
Chunguo Jiang ◽  
Xiaokai Feng ◽  
Yanfei Zheng ◽  
Jie Yang ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Blood Glucose ◽  
Fasting Blood Glucose ◽  
Proportional Hazard ◽  
Cox Proportional Hazard ◽  
Single Center Study ◽  
And Gender ◽  
Cox Proportional Hazard Regression ◽  
Relationship Of ◽  
The Relationship

Abstract Background: Coronavirus disease-19 (COVID-19) has spread rapidly, with a growing number of cases confirmed around the world. This study explores the relationship of fasting blood glucose (FBG) at admission with mortality.Methods: In this retrospective, single-center study, we analyzed the clinical characteristics of confirmed cases of COVID-19 in Wu Han from 29 January 2020 to 23 February 2020. Cox proportional hazard regression analysis was performed to evaluate the relationship between FBG and mortality.Results: A total of 107 patients were enrolled in our study. The average age was 59.49 ± 13.33 and the FBG at admission was 7.35 ± 3.13 mmol/L. There were 16 people died of COVID-19 with an average age 68.1 ± 9.5 and the FBG was 8.94 ± 4.76 mmol/L. Regression analysis showed that there were significant association between FBG and death (HR = 1.13, 95%CI: 1.02-1.24). After adjusting for covariables, the significance still exists. In addition, our result showed that FBG > 7.0 mmol/L or diabetic mellitus can significantly increase mortality after adjusting for the age and gender.Conclusions: This study suggests that FBG at admission is an effective and reliable indicator for disease prognosis in COVID-19 patients.

scholarly journals Patient flow dynamics in hospital systems during times of COVID-19: Cox proportional hazard regression analysis.

2020 ◽  
Author(s):  
Sudhir Bhandari ◽  
Amit Tak ◽  
Sanjay Singhal ◽  
Jyotsna Shukla ◽  
Bhoopendra Patel ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Survival Rate ◽  
Hospital Stay ◽  
Cox Model ◽  
Patient Flow ◽  
Proportional Hazard ◽  
Age And Gender ◽  
Cox Proportional Hazard ◽  
And Gender ◽  
Cox Proportional Hazard Regression

Abstract Objectives: The present study is aimed at estimating patient flow dynamical parameters and requirement of hospital beds. Secondly, the effects of age and gender on parameters were evaluated. Patients and Methods: In this retrospective cohort study, 987 COVID-19 patients were enrolled from SMS Medical College, Jaipur (Rajasthan, India). The survival analysis was carried out from 29 Feb to 19 May 2020 for two hazards – ‘Hazard 1’ was hospital discharge and ‘Hazard 2’ was hospital death. The starting point for survival analysis of the two hazards was considered to be hospital admission . The survival curves were estimated and additional effects of age and gender were evaluated using Cox proportional hazard regression analysis. Results: The Kaplan Meier estimates of lengths of hospital stay (Median =10 days, IQR =10 days) and median survival rate ( more than 60 days due to large amount of censored data) were obtained. The Cox Model for ‘Hazard 1’ showed no significant effect of age and gender on duration of hospital stay. Similarly, the Cox Model 2 showed no significant difference of gender on survival rate. The case fatality rate 8.1 % , recovery rate 78.8% , mortality rate 0.10 per 100 person--days and hospital admission rate 0.35 per 105 person-days were estimated.Conclusion : The study estimates hospital bed requirement based on patient flow dynamic parameters. Furthermore, study concludes that average length of hospital stay were similar for patients of both genders and all age groups.

scholarly journals AB0292 EFFICACY AND SAFETY OF TWO BIOSIMILAR ETANERCEPT AFTER THE SWITCH FROM THEIR CORRESPONDING ORIGINATOR IN THE TREATMENT OF PATIENTS WITH AUTOIMMUNE ARTHRITIS; A RETROSPECTIVE ANALYSIS IN A REAL LIFE SETTING

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1445.1-1445
Author(s):  
F. Girelli ◽  
A. Ariani ◽  
M. Bruschi ◽  
A. Becciolini ◽  
L. Gardelli ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Disease Duration ◽  
Retention Rate ◽  
Real Life ◽  
Autoimmune Arthritis ◽  
Proportional Hazard ◽  
Hazard Regression ◽  
Cox Proportional Hazard ◽  
Real Life Setting ◽  
Cox Proportional Hazard Regression

Background:The available biosimilars of etanercept are as effective and well tolerated as their bio originator molecule in the naive treatment of chronic autoimmune arthritis. More data about the switching from the bio originator are needed.Objectives:To compare the clinical outcomes of the treatment with etanercept biosimilars (SB4 and GP2015) naïve and after the switch from their corresponding originator in patients affected by autoimmune arthritis in a real life settingMethods:We retrospectively analyzed the baseline characteristics and the retention rate in a cohort of patients who received at least a course of etanercept (originator or biosimilar) in our Rheumatology Units from January 2000 to January 2020. We stratified the study population according to biosimilar use. Descriptive data are presented by medians (interquartile range [IQR]) for continuous data or as numbers (percentages) for categorical data. Drug survival distribution curves were computed by the Kaplan-Meier method and compared by a stratified log-rank test. A Cox proportional hazards regression analysis stratified by indication, drug, age, disease duration, sex, treatment line, biosimilar use and prescription year was performed. P values≤0.05 were considered statistically significant.Results:477 patients (65% female, median age 56 [46-75] years, median disease duration 97 [40.25-178.75] months) treated with etanercept were included in the analysis. 257 (53.9%) were affect by rheumatoid arthritis, 139 (29.1%) by psoriatic arthritis, and 81 (17%) by axial spondylarthritis. 298 (62.5%) were treated with etanercept originator, 97 (20.3%) with SB4, and 82 (17.2%) with GP2015. Among the biosimilars 90/179 (50.3%) patients were naïve to etanercept treatment. Among the 89 switchers we observed 8 treatment discontinuations: one due to surgical infection complication, three due to disease flare, two due to subjective worsening and one due to remission. The overall 6- and 12-month retentions rate were 92.8% and 80.2%. The 6- and 12-month retention rate for etanercept, SB4 and GP2015 were 92.7%, 93.4% and 90.2%, and 82%, 74.5% and 88.1% respectively, without significant differences among the three groups (p=0.374). Patients switching from originator to biosimilars showed and overall higher treatment survival when compared to naive (12-month retention rate 81.2% vs 70.8%, p=0.036). The Cox proportional hazard regression analysis highlighted that the only predictor significantly associated with an overall higher risk of treatment discontinuation was the year of prescription (HR 1.08, 95% CI 1.04 to 1.13; p<0.0001).Conclusion:In our retrospective study etanercept originator and its biosimilars (SB4 and GP2015) showed the same effectiveness. Patients switching from originator to biosimilar showed an significant higher retention rate when compared to naive. The only predictor of treatment discontinuation highlighted by the Cox proportional hazard regression analysis was the year of treatment prescription.Disclosure of Interests:Francesco Girelli: None declared, Alarico Ariani: None declared, Marco Bruschi: None declared, Andrea Becciolini Speakers bureau: Sanofi-Genzyme, UCB and AbbVie, Lucia Gardelli: None declared, Maurizio Nizzoli: None declared

scholarly journals CMTM6 significantly relates to PD-L1 and predicts the prognosis of gastric cancer patients

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9536
Author(s):  
Xin Li ◽  
Ling Chen ◽  
Chuan Gu ◽  
Qiaoli Sun ◽  
Jia Li
Keyword(s):  
Gastric Cancer ◽  
Prognostic Indicator ◽  
Proportional Hazard ◽  
Regression Analyses ◽  
Multivariate Logistic Regression ◽  
Related Factors ◽  
Cox Proportional Hazard ◽  
Kaplan Meier ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Background The CKLF-like MARVEL transmembrane domain containing 6 (CMTM6) is a key regulator of the programed death receptor ligand-1 (PD-L1) protein. However, the usefulness of CMTM6 expression as a prognostic indicator and the relationship between CMTM6 and PD-L1 expression in gastric cancer (GC) remains unclear. Objectives We evaluated the expression and prognostic implications of CMTM6 in GC tissue and its relationship with PD-L1 expression. Patients and methods The protein expressions of CMTM6 and PD-L1 were detected in 122 cases of postoperative GC tissue using immunohistochemical (IHC) assays. Kaplan–Meier survival analysis was used to calculate the survival probability and a log-rank test was used to compare the survival curves. Univariate and multivariate Cox proportional hazard regression analyses were used to evaluate the clinically-related factors associated with survival. Pearson’s correlation was used to determine the correlation analysis and estimate the statistical significance. The univariate and multivariate logistic regression analyses were used to analyze the relationship between clinically-related factors and PD-L1 expression. Results Kaplan–Meier survival analysis showed that patients with high CMTM6 expression had shorter overall survival (OS) than those with low expression (P < 0.001). The expression of CMTM6 was an independent risk factor for prognosis in multivariate Cox proportional hazard regression analyses (HR:2.221, CI% [1.36–3.628], P = 0.001). The OS of patients with positively expressed PD-L1 was significantly shorter than those with negatively expressed PD-L1 (P = 0.003). The expression of CMTM6 was significantly related to the positive expression of PD-L1 in gastric cancer tissues (r = 0.186, P = 0.041). The expression of CMTM6 was the independent risk factor for PD-L1 expression in multivariate logistic regression analysis (OR:2.538, CI% [1.128–5.714], P = 0.024). Conclusion CMTM6 expression is significantly related to PD-L1 and may be a useful prognostic indicator and a specific therapeutic target for cancer immunotherapy for GC patients.

scholarly journals Computer-assisted quantification of tumor-associated collagen signatures to improve the prognosis prediction of breast cancer

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Gangqin Xi ◽  
Lida Qiu ◽  
Shuoyu Xu ◽  
Wenhui Guo ◽  
Fangmeng Fu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Validation Cohort ◽  
Proportional Hazard ◽  
Breast Cancer Patients ◽  
Cox Proportional Hazard ◽  
Clinical Center ◽  
Microscopic Features ◽  
Cox Proportional Hazard Regression

Abstract Background Collagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients. Methods In this retrospective and multicenter study, we included 942 invasive breast cancer patients in both a training cohort (n = 355) and an internal validation cohort (n = 334) from one clinical center and in an external validation cohort (n = 253) from a different clinical center. TACS corresponding microscopic features (TCMFs) were firstly extracted from multiphoton images for each patient, and then least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust features to build a TCMF-score. Finally, the Cox proportional hazard regression analysis was used to evaluate the association of TCMF-score with disease-free survival (DFS). Results TCMF-score is significantly associated with DFS in univariate Cox proportional hazard regression analysis. After adjusting for clinical variables by multivariate Cox regression analysis, the TCMF-score remains an independent prognostic indicator. Remarkably, the TCMF model performs better than the clinical (CLI) model in the three cohorts and is particularly outstanding in the ER-positive and lower-risk subgroups. By contrast, the TACS model is more suitable for the ER-negative and higher-risk subgroups. When the TACS and TCMF are combined, they could complement each other and perform well in all patients. As expected, the full model (CLI+TCMF+TACS) achieves the best performance (AUC 0.905, [0.873–0.938]; 0.896, [0.860–0.931]; 0.882, [0.840–0.925] in the three cohorts). Conclusion These results demonstrate that the TCMF-score is an independent prognostic factor for breast cancer, and the increased prognostic performance (TCMF+TACS-score) may help us develop more appropriate treatment protocols.

scholarly journals Factors That Affect Time to Switch From Warfarin to a Direct Oral Anticoagulant After Change in the Reimbursement Criteria in Patients With Atrial Fibrillation

2019 ◽  
Vol 25 (1) ◽  
pp. 57-64
Author(s):  
Susin Park ◽  
Nam Kyung Je
Keyword(s):  
Atrial Fibrillation ◽  
Regression Analysis ◽  
Oral Anticoagulant ◽  
Proportional Hazard ◽  
Direct Oral Anticoagulant ◽  
Hazard Regression ◽  
Cox Proportional Hazard ◽  
History Of ◽  
Cox Proportional Hazard Regression ◽  
Prior Stroke

Background: Anticoagulation therapy is recommended for stroke prevention in high-risk patients with atrial fibrillation (AF). This study aimed to estimate the time to switch from warfarin to a direct oral anticoagulant (DOAC) and identify the factors associated with it. Methods: By using claims data, we studied 7111 warfarin-using patients with nonvalvular AF who were aged ≥65 years. The Kaplan-Meier analysis was performed to estimate the time to switch from warfarin to a DOAC, and Cox proportional hazard regression analysis was used to estimate the influencing factors. Results: Approximately one-third of the patients (2403, 33.8%) switched from warfarin to a DOAC during the study period. Female sex, aged between 75 and 79 years, having a Medical Aid or Patriots and Veterans Insurance, hypertension, and history of prior stroke, and transient ischemic attack or thromboembolism (prior stroke/TIA/TE) were associated with a significantly shorter time to switch. The odds of switching to a DOAC were increased by approximately 1.2-fold in the women and 1.4-fold in the patients with prior stroke/TIA/TE. Conclusions: Approximately one-third of the warfarin-using patients switched from warfarin to a DOAC within 6 months after the change in the DOAC reimbursement criteria. In the Cox proportional hazard regression analysis, the factors that affected anticoagulant switching from warfarin to a DOAC were female sex and history of prior stroke/TIA/TE.

scholarly journals Decreased All-Cause and Liver-Related Mortality Risk in HIV/Hepatitis B Virus Coinfection Coinciding With the Introduction of Tenofovir-Containing Combination Antiretroviral Therapy

2020 ◽  
Vol 7 (7) ◽  
Author(s):  
Berend J van Welzen ◽  
Colette Smit ◽  
Anders Boyd ◽  
Faydra I Lieveld ◽  
Tania Mudrikova ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Hepatitis B Virus ◽  
Proportional Hazard ◽  
Combination Antiretroviral Therapy ◽  
Cox Proportional Hazard ◽  
B Virus ◽  
Specific Mortality ◽  
Cox Proportional Hazard Regression ◽  
Related Mortality

Abstract Background The development of efficacious combination antiretroviral therapy (cART) has led to a dramatic decrease in mortality in HIV-positive patients. Specific data on the impact in HIV/hepatitis B virus (HBV)–coinfected patients are lacking. In this study, all-cause and cause-specific mortality risks stratified per era of diagnosis are investigated. Methods Data were analyzed from HIV/HBV-coinfected patients enrolled in the ATHENA cohort between January 1, 1998, and December 31, 2017. Risk for (cause-specific) mortality was calculated using Cox proportional hazard regression analysis, comparing patients diagnosed before 2003 with those diagnosed ≥2003. Risk factors for all-cause and liver-related mortality were also assessed using Cox proportional hazard regression analysis. Results A total of 1301 HIV/HBV-coinfected patients were included (14 882 person-years of follow-up). One-hundred ninety-eight patients (15%) died during follow-up. The adjusted hazard ratio (aHR) for all-cause mortality in patients diagnosed in or after 2003 was 0.50 (95% CI, 0.35–0.72) relative to patients diagnosed before 2003. Similar risk reduction was observed for liver-related (aHR, 0.29; 95% CI, 0.11–0.75) and AIDS-related mortality (aHR, 0.44; 95% CI, 0.22–0.87). Use of a tenofovir-containing regimen was independently associated with a reduced risk of all-cause and liver-related mortality. Prior exposure to didanosine/stavudine was strongly associated with liver-related mortality. Ten percent of the population used only lamivudine as treatment for HBV. Conclusions All-cause, liver-related, and AIDS-related mortality risk in HIV/HBV-coinfected patients has markedly decreased over the years, coinciding with the introduction of tenofovir. Tenofovir-containing regimens, in absence of major contraindications, should be strongly encouraged in this population.

scholarly journals ANALISIS KETAHANAN HIDUP PENDERITA DENGUE HEMORRHAGIC FEVER (DEMAM BERDARAH) DENGAN REGRESI COX KEGAGALAN PROPORSIONAL (Studi Kasus : Rumah Sakit Islam Nahdlatul Ulama Demak)

2021 ◽  
Vol 10 (3) ◽  
pp. 367-376
Author(s):  
Putri Qodar Ummayah ◽  
Sudarno Sudarno ◽  
Budi Warsito
Keyword(s):  
Survival Analysis ◽  
Dengue Fever ◽  
Dengue Hemorrhagic Fever ◽  
Recovery Time ◽  
Hemorrhagic Fever ◽  
Proportional Hazard ◽  
Hazard Regression ◽  
Cox Proportional Hazard ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Dengue hemorrhagic fever is an acute febrile disease caused by the dengue virus, which enters the human bloodstream through the bite of a mosquito of the genus Aedes Aegypti or Aedes Albopictus. Based on World Health Organization (WHO) records, it is estimated that 500,000 dengue hemorrhagic fever patients require hospital treatment every year and most of the sufferers are children. To analyze the relationship between recovery time in dengue fever patients and the factors that influence it using regression analysis, the dependent variable is the failure time and the function of the response variable tends to fail constant so to find out the relationship using Cox proportional hazard regression. Cox proportional hazard regression is a regression model that is often used in survival analysis. Survival analysis is a method used to describe data analysis in terms of time from the time of origin defined until a certain event occurs. In this study, the recovery time of dengue fever patients as a function of failure is proportional. The observations used by the researchers for each patient were not the same. The population of this study were all patients with dengue fever. The data used was obtained from the medical record section for data on the length of hospitalization of patients regarding the recovery of patients with dengue fever. The conclusion of the research shows that the factors that affect the recovery time of dengue fever patients are hematocrit, platelets, immunoglobulin G, and immunoglobulin M. 

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