scholarly journals The Predictive Role of NLR, d-NLR, MLR, and SIRI in COVID-19 Mortality

Diagnostics ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 122
Author(s):  
Cosmin Citu ◽  
Florin Gorun ◽  
Andrei Motoc ◽  
Ioan Sas ◽  
Oana Maria Gorun ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cox Regression ◽  
Binary Logistic Regression ◽  
Hospital Death ◽  
Optimal Cutoff ◽  
Inflammatory Index ◽  
Cell Counts ◽  
Risk Of Mortality ◽  
Predictive Role

(1) Background: Since its discovery, COVID-19 has caused more than 256 million cases, with a cumulative death toll of more than 5.1 million, worldwide. Early identification of patients at high risk of mortality is of great importance in saving the lives of COVID-19 patients. The study aims to assess the utility of various inflammatory markers in predicting mortality among hospitalized patients with COVID-19. (2) Methods: A retrospective observational study was conducted among 108 patients with laboratory-confirmed COVID-19 hospitalized between 1 May 2021 and 31 October 2021 at Municipal Emergency Clinical Hospital of Timisoara, Romania. Blood cell counts at admission were used to obtain NLR, dNLR, MLR, PLR, SII, and SIRI. The association of inflammatory index and mortality was assessed via Kaplan–Maier curves univariate Cox regression and binominal logistic regression. (3) Results: The median age was 63.31 ± 14.83, the rate of in-hospital death being 15.7%. The optimal cutoff for NLR, dNLR, MLR, and SIRI was 9.1, 9.6, 0.69, and 2.2. AUC for PLR and SII had no statistically significant discriminatory value. The binary logistic regression identified elevated NLR (aOR = 4.14), dNLR (aOR = 14.09), and MLR (aOR = 3.29), as independent factors for poor clinical outcome of COVID-19. (4) Conclusions: NLR, dNLR, MLR have significant predictive value in COVID-19 mortality.

scholarly journals Understanding the role of oxidative stress in the incidence of metabolic syndrome and obstructive sleep apnea

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Behnam Kargar ◽  
Zahra Zamanian ◽  
Majid Bagheri Hosseinabadi ◽  
Vahid Gharibi ◽  
Mohammad Sanyar Moradi ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Metabolic Syndrome ◽  
Obstructive Sleep Apnea ◽  
Logistic Regression ◽  
Sleep Apnea ◽  
International Diabetes Federation ◽  
Binary Logistic Regression ◽  
Stress Index ◽  
Obstructive Sleep

Abstract Background Understanding the causes and risk factors of metabolic syndrome is important for promoting population health. Oxidative stress has been associated with metabolic syndrome, and also obstructive sleep apnea. These are two diseases which have common prognostic characteristics for heart disease. The aim of this study was to examine the role of oxidative stress in the concurrent presence of metabolic syndrome and obstructive sleep apnea in a working population. Methods Participants were 163 artisan bakers in Shahroud, Iran, routinely exposed to significant heat stress and other oxidative stress indicators on a daily basis as part of their work. Using a cross-sectional design, data relevant to determining metabolic syndrome status according to International Diabetes Federation criteria, and the presence of obstructive sleep apnea according to the STOP-Bang score, was collected. Analyses included hierarchical binary logistic regression to yield predictors of the two diseases. Results Hierarchical binary logistic regression showed that oxidative stress – alongside obesity, no regular exercise, and smoking – was an independent predictor of metabolic syndrome, but not obstructive sleep apnea. Participants who were obese were 28 times more likely to have metabolic syndrome (OR 28.59, 95% CI 4.91–63.02) and 44 times more likely to have obstructive sleep apnea (OR 44.48, 95% CI 4.91–403.28). Participants meeting metabolic syndrome criteria had significantly higher levels of malondialdehyde (p <  0.05) than those who did not. No difference in oxidative stress index levels were found according to obstructive sleep apnea status. Conclusions Our findings suggest that oxidative stress contributes to the onset of metabolic syndrome, and that obstructive sleep apnea is involved in oxidative stress. Whilst obesity, exercise, and smoking remain important targets for reducing the incidence of metabolic syndrome and obstructive sleep apnea, policies to control risks of prolonged exposure to oxidative stress are also relevant in occupations where such environmental conditions exist.

scholarly journals Cardiac biomarkers as prognosticators among SARS-CoV-19 patients in a tertiary hospital in Philippines

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
R Ong ◽  
C Chacon ◽  
S Javier
Keyword(s):  
Creatine Kinase ◽  
Logistic Regression ◽  
Hospital Mortality ◽  
Roc Curve ◽  
Predictive Value ◽  
Troponin I ◽  
Binary Logistic Regression ◽  
High Sensitivity ◽  
Cardiac Biomarkers ◽  
Optimal Cutoff

Abstract Background There is overwhelming volume of confirmed cases of COVID-19, despite this numerous knowledge gaps remain in the diagnosis, management, and prognostication of this novel coronavirus infection, making prevention and control a challenge. Methods This retrospective cohort study included patients with real-time reverse transcriptase polymerase chain reaction (rRT-PCR)-confirmed COVID-19. Binary logistic regression was used to determine the association between the cardiac biomarkers and in-hospital mortality. ROC, AUC, and cutoff analyses were used to determine optimal cutoff values for the cardiac biomarkers. Results A total of 90 subjects with a complete panel of cardiac biomarkers out of the 224 rRT-PCR confirmed cases were included. The median age was 57 years (IQR, 47–67 years), majority were males. Sixty-six (77.6%) subjects survived while 19 (22.4%) expired. The most common presenting symptom was fever (75.6%), and the most common comorbidity was hypertension (67.8%). Spearman rho correlation analysis showed moderate positive association of high sensitivity troponin I (hsTnI) with in-hospital mortality (R, 0.434, p = &lt;0.001). Multivariate binary logistic regression analysis showed that creatine kinase and hsTnI were independently associated with in-hospital mortality (OR, 4.103 [95% CI, 1.241–13.563], p=0.021; and OR, 7.899 [95% CI, 2.430–25.675], p=0.001, respectively). ROC curve analysis showed that hsTnI was a good predictor for in-hospital mortality (AUC, 0.829 [95% CI, 0.735–0.923], p = &lt;0.001) and that creatine kinase was a poor predictor (AUC, 0.677 [95% CI, 0.531–0.823], p=0.018). Optimal cutoff point derived from the ROC curve for hsTnI was 0.010 ng/ml (J, 0.574) with a sensitivity of 84% (TPR, 0.842 [95% CI, 0.604–0.966]), specificity of 73% (TNR, 0.732 [95% CI, 0.614–0.386]), and an adjusted negative predictive value of 99% (Known prevalence*adjusted NPV, 0.989), a positive likelihood ratio of 20% (LR+, 3.147 [95% CI, 2.044–4.844]) and a negative likelihood ratio of 30% (LR−, 0.216 [95% CI, 0.076–0.615]). Conclusion High sensitivity troponin I level was a good tool with a very high negative predictive value in significantly predicting in-hospital mortality among rRT-PCR positive COVID-19 patients. FUNDunding Acknowledgement Type of funding sources: None. ROC Curve

Copa America: a resource-based theory of football talent

2019 ◽  
Vol 25 (3/4) ◽  
pp. 176-191
Author(s):  
Peter Omondi-Ochieng
Keyword(s):  
Logistic Regression ◽  
Design Methodology ◽  
Binary Logistic Regression ◽  
Content Type ◽  
Independent Variables ◽  
Football Team ◽  
Practical Implications ◽  
Resource Based Theory

Purpose Guided by the resource-based theory, the purpose of this study was to predict the role of football talent in the Federation Internationale de Football Association (FIFA) rankings of the men’s national football teams in the Copa America zone. Design/methodology/approach The study used archival data of Copa American national football teams. The dependent variable was FIFA rankings, and the independent variables were football talent (measured by the stocks of amateur footballers, professional footballers and football officials). Statistical analysis was performed using Kendall tau statistic and binary logistic regression. Findings The binary logistic regression results indicated that FIFA rankings were statistically and significantly associated with the stock of football officials and professional footballers – but not amateur footballers. The predictive model explained 80 per cent of the variance. Research limitations/implications The study focused exclusively on the stock of football talent in each nation, and not alternative determinants of national football team competitiveness as economic power and quality of professional football leagues, among others. Practical implications The stocks of professional footballers and football officials are valuable sources of competitive advantage (CA) in national football team rankings. Originality/value The study highlighted the uniqueness and distinctiveness of a nation possessing large stocks of professional footballers which can boost the CA and rankings of Copa American national football teams.

scholarly journals Lymphocyte subsets as a predictor of severity and prognosis in COVID-19 patients

2021 ◽  
Vol 35 ◽  
pp. 205873842110485
Author(s):  
Peng Zhang ◽  
Wei Du ◽  
Ting Yang ◽  
Lei Zhao ◽  
Richeng Xiong ◽  
...  
Keyword(s):  
T Cells ◽  
Blood Cell ◽  
Lymphocyte Subsets ◽  
Cox Regression ◽  
Hematological Parameters ◽  
Characteristic Curve ◽  
Hospital Death ◽  
Cox Regression Analysis ◽  
Cell Counts ◽  
Blood Cell Counts

Background Coronavirus disease 2019 (COVID-19) had become a worldwide health threat. Early prediction of the severity of COVID-19 patients was important for reducing death rate and controlling this disease. Methods and materials A total of 301 patients confirmed with COVID-19 in Wuhan from 8 February to 10 April 2020 were included. Clinical data were collected and analyzed. Diagnostic and prognostic utility of blood cell counts and lymphocyte subsets in COVID-19 patients were investigated. The receiver operator characteristic curve (ROC) was used in discriminating the mild and severe/critical cases. Results There were difference in blood cell counts and lymphocyte subsets among mild, severe and critical patients, which were also influenced by comorbidities and duration of disease. The area under the ROC of lymphocyte, CD3+ T cells, CD4+ T cells, and CD8+ T cells were 0.718, 0.721, 0.718, and 0.670, which were higher than that of other hematological parameters. The optimal threshold was 1205, 691, 402, and 177 per μl, respectively. Patients with higher counts of lymphocyte, CD3+ T cells, CD4+ T cells, or CD8+ T cells were correlated with shorter length of stay in hospital ( p < 0.05). Multivariable Cox regression analysis showed disease severity, CD3+ T cells counts and time when the nucleic acid turned negative were independent risk factors for in-hospital death of COVID-19 patients ( p < 0.05). Conclusion Blood cell counts and lymphocyte subsets correlated with severity of COVID-19.

scholarly journals Predictive Value of Matrix Metalloprotease 9 On Surgical Outcomes After Pericardiectomy

2021 ◽  
Author(s):  
Likui Fang ◽  
Wenfeng Yu ◽  
Guocan Yu ◽  
Bo Ye ◽  
Gang Chen
Keyword(s):  
Gene Expression ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Postoperative Complications ◽  
Binary Logistic Regression ◽  
Postoperative Outcomes ◽  
Binary Logistic Regression Analysis ◽  
Optimal Cutoff ◽  
Cutoff Value ◽  
High Level

Abstract Background The effects of matrix metalloproteases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) expressions on the patients with constrictive pericarditis undergoing pericardiectomy remain unclear. This study explored the associations of MMPs and TIMPs expressions with postoperative outcomes in these patients. Methods Pericardial specimens were obtained during pericardiectomy from the patients with constrictive pericarditis. The levels of MMP1, MMP2, MMP9 and TIMP1 in pericardium were analyzed by quantitative real-time polymerase chain reaction. The enrolled patients were divided into two groups according to the optimal cutoff value of gene expression predicting postoperative complications. Postoperative outcomes were compared between the two groups. Binary logistic regression analysis was performed to determine the degree of contribution of gene expression on postoperative outcomes. Results A total of 22 patients and their pericardial specimens were included. The level of MMP9 was significantly associated with postoperative complications and the optimal cutoff value predicting postoperative complications was 3.67. The patients with low level of MMP9 (< 3.67) had lower incidence of postoperative complications (P = 0.002), shorter postoperative intensive care unit (P = 0.040) and hospital stay (P = 0.043) in comparison to those with high level of MMP9 (≥ 3.67). Binary logistic regression analysis showed that high level of MMP9 increased risk of postoperative complications (OR, 27.096, 95%CI 1.166-629.886, P = 0.040). Conclusions High level of MMP9 in the pericardium was associated with poor postoperative outcomes and was the independent risk factor of postoperative complications. The level of MMP9 could be used as a potential marker for prediction of surgical outcomes.

scholarly journals Krebs von den Lungen 6 levels in COVID-19 ICU Patients are Associated with Mortality

2021 ◽  
Author(s):  
Giuliana Scarpati ◽  
Daniela Baldassarre ◽  
Graziella Lacava ◽  
Filomena Oliva ◽  
Gabriele Pascale ◽  
...  
Keyword(s):  
Cox Regression ◽  
Icu Patients ◽  
Cox Regression Analysis ◽  
Alveolar Epithelial ◽  
Type Ii Pneumocytes ◽  
Group A ◽  
Predictive Role ◽  
Fraction Of Inspired Oxygen ◽  
Group B

Rationale Krebs von den Lungen 6 (KL-6) is a high molecular weight mucin-like glycoprotein produced by type II pneumocytes and bronchial epithelial cells. Elevated circulating levels of KL-6 may denote disorder of the alveolar epithelial lining. Objective Aim of this study was to verify if KL-6 values may help to risk stratify and triage severe COVID-19 patients. Methods We performed a retrospective prognostic study on 110 COVID-19 ICU patients, evaluating the predictive role of KL-6 for mortality. Measurements and Main Results The study sample was divided in two groups related according to the median KL-6 value [Group A (KL-6 lower than the log-transformed median (6.73)) and Group B (KL-6 higher than the log-transformed median)]. In both linear and logistic multivariate analyses, ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (P/F) was significantly and inversely related to KL-6. Death rate was higher in group B than in group A (80.3 versus 45.9%) (p<0.001), Accordingly, the Cox regression analysis showed a significant prognostic role of KL-6 on mortality in the whole sample as well as in the subgroup with SOFA lower than its median value. Conclusions At ICU admission, KL-6 serum level was significantly lower in the survivors group. Our findings shown that, in severe COVID19 patients, elevated KL-6 was strongly associated with mortality in ICU.

P5459Comparison of the predictive role of changes in left ventricular mass and arterial stiffness for coronary artery disease in essential hypertension: Data from a 8-year-follow-up study

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
I Leontsinis ◽  
C Tsioufis ◽  
K Dimitriadis ◽  
A Kasiakogias ◽  
I Liatakis ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Arterial Stiffness ◽  
Cox Regression ◽  
Left Ventricular ◽  
Hazard Ratio ◽  
Hypertensive Patients ◽  
Predictive Role ◽  
Artery Disease

Abstract Background/Introduction Although arterial stiffening is related to atherosclerosis progression, its prognostic role in hypertension is not fully elucidated, while augmented left ventricular mass index (LVMI) is linked to adverse outcome. Purpose The aim of the present study was to compare the predictive role of changes in arterial stiffness and LVMI for the incidence of coronary artery disease (CAD) in a cohort of essential hypertensive patients. Methods We followed up 1082 essential hypertensives (mean age 55.9 years, 562 males, office blood pressure (BP)=145/91 mmHg) free of cardiovascular disease for a mean period of 8 years. All subjects had at least one annual visit and at baseline and last visit underwent complete echocardiographic study for estimation of LVMI and measurements of arterial stiffness on the basis of carotid to femoral pulse wave velocity (PWV), by means of a computerized method. The distribution of PWV was split by the median (8.2 m/sec) and accordingly subjects were classified into those with high (n=546) and low values (n=536). Moreover, LV hypertrophy (LVH) was defined as LVMI ≥125 g/m2 in males and LVMI ≥110 g/m2 in females, while CAD was defined as the history of myocardial infarction or significant coronary artery stenosis revealed by angiography or coronary revascularization procedure. Results The incidence of CAD over the follow-up period was 3.5%. Hypertensives who developed CAD (n=38) compared to those without CAD at follow-up (n=1044) had at baseline higher waist circumference (101.7±10.1 vs 96.2±11.6 cm, p=0.004), LVMI (123.9±22.1 vs 105.8±21.3 g/m2, p=0.026), prevalence of LVH (46% vs 25%, p=0.018) and prevalence of high PWV levels (67% vs 40%, p=0.021). No difference was observed between hypertensives with CAD and those without CAD with respect to baseline office BP, serum creatinine and lipid levels (p=NS for all). By univariate Cox regression analysis, it was revealed that changes in PWV levels between baseline and last visit predicted CAD (hazard ratio=1.243, p=0.014). However, in multivariate Cox regression model baseline glomerular filtration rate (hazard ratio=1.029, p=0.015) and changes in LVMI (hazard ratio=1.036, p<0.0001) but not alterations of PWV turned out to be independent predictors of CAD. Conclusions In essential hypertensive patients changes in LVMI predict future development of CAD, whereas PWV alterations exhibit no independent prognostic value. These findings support that LVMI constitutes a superior prognosticator of events than PWV and its estimation is essential in order to improve overall risk stratification in hypertension.

scholarly journals Gender differences in the predictive role of self-rated health on short-term risk of mortality among older adults

2016 ◽  
Vol 4 ◽  
pp. 205031211666697 ◽  
Author(s):  
Shervin Assari
Keyword(s):  
Older Adults ◽  
Mortality Risk ◽  
Older Men ◽  
Short Term ◽  
Men And Women ◽  
Self Rated Health ◽  
Risk Of Mortality ◽  
Predictive Role ◽  
Pooled Sample

Objectives: Despite the well-established association between self-rated health and mortality, research findings have been inconsistent regarding how men and women differ on this link. Using a national sample in the United States, this study compared American male and female older adults for the predictive role of baseline self-rated health on the short-term risk of mortality. Methods: This longitudinal study followed 1500 older adults (573 men (38.2%) and 927 women (61.8%)) aged 66 years or older for 3 years from 2001 to 2004. The main predictor of interest was self-rated health, which was measured using a single item in 2001. The outcome was the risk of all-cause mortality during the 3-year follow-up period. Demographic factors (race and age), socio-economic factors (education and marital status), and health behaviors (smoking and drinking) were covariates. Gender was the focal moderator. We ran logistic regression models in the pooled sample and also stratified by gender, with self-rated health treated as either nominal variables, poor compared to other levels (i.e. fair, good, or excellent) or excellent compared to other levels (i.e. good, fair, or poor), or an ordinal variable. Results: In the pooled sample, baseline self-rated health predicted mortality risk, regardless of how the variable was treated. We found a significant interaction between gender and poor self-rated health, indicating a stronger effect of poor self-rated health on mortality risk for men compared to women. Gender did not interact with excellent self-rated health on mortality. Conclusion: Perceived poor self-rated health better reflects risk of mortality over a short period of time for older men compared to older women. Clinicians may need to take poor self-rated health of older men very seriously. Future research should test whether the differential predictive validity of self-rated health based on gender is due to a different meaning of poor self-rated health for older men and women and whether poor self-rated health reflects different health statuses based on gender.

scholarly journals The Role of Sales Promotion in inducing Impulse Purchases

2014 ◽  
Vol 3 (1) ◽  
pp. 362-372 ◽  
Author(s):  
Rim Ben Amara ◽  
Abir Sahraoui Kchaou
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Structural Equations ◽  
Sales Promotion ◽  
Impulse Buying ◽  
Research Support ◽  
Impulse Purchases ◽  
The Impact

This paper focuses on promotional impulse buying. It aims at examining the impact of hedonic and utilitarian benefits of promotion on an impulse buying experience. The hypotheses were tested with a sample of 300 consumers doing their shopping in a hypermarket. Data were analyzed using binary logistic regression and structural equations. The results obtained allow us to confirm most of our hypotheses. The different outcomes of this research support the formulation of a number of theoretical, methodological and managerial recommendations. 

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