scholarly journals An increased pretreatment neutrophil-to-lymphocyte ratio predicts severe novel coronavirus-infected pneumonia

2020 ◽  
Author(s):  
Xiaoyue Wang ◽  
Desheng Jiang ◽  
Huang Huang ◽  
Xiaofeng Chen ◽  
Chunlei Zhou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Early Warning ◽  
Roc Curve ◽  
Neutrophil To Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Independent Risk Factors ◽  
Novel Coronavirus

Abstract Objective The aim of this study was to identify early warning signs for severe novel coronavirus-infected pneumonia (COVID-19).Methods We retrospectively analyzed the clinical data of 90 patients with COVID-19 at the Guanggu District of Hubei Women and Children Medical and Healthcare Center comprising 60 mild cases and 30 severe cases. The demographic data, underlying diseases, clinical manifestations and laboratory blood test results were compared between the two groups. Logistic regression analysis was performed to identify the independent risk factors that predicted severe COVID-19. The receiver-operating characteristic (ROC) curve of independent risk factors was calculated, and the area under the curve (AUC) was used to evaluate the efficiency of the prediction of severe COVID-19.Results The patients with mild and severe COVID-19 showed significant differences in terms of cancer incidence, age, pretreatment neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP) and the serum albumin (ALB) level (P<0.05). The severity of COVID-19 was correlated positively with the comorbidity of cancer, age, NLR, and CRP but was negatively correlated with the ALB level (P<0.05). Multivariate logistic regression analysis showed that the NLR and ALB level were independent risk factors for severe COVID-19 (OR=1.319, 95% CI: 1.043-1.669, P=0.021; OR=0.739, 95% CI: 0.616-0.886, P=0.001), with AUCs of 0.851 and 0.128, respectively. An NLR of 4.939 corresponded to the maximum joint sensitivity and specificity according to the ROC curve (0.700 and 0.917, respectively).Conclusion An increased NLR can serve as an early warning sign of severe COVID-19.

Increased pretreatment C-reactive protein-to-albumin ratio predicts severe coronavirus disease 2019

2020 ◽  
Author(s):  
Xiaoyue Wang ◽  
Yan Xu ◽  
Huang Huang ◽  
Desheng Jiang ◽  
Chunlei Zhou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Early Warning ◽  
Warning Signs ◽  
C Reactive Protein ◽  
Albumin Ratio ◽  
Reactive Protein ◽  
Independent Risk Factors

Abstract Objective The aim of this study was to identify early warning signs for severe coronavirus disease 2019 (COVID-19). Methods We retrospectively analysed the clinical data of 90 patients with COVID-19 from Guanggu District of Hubei Women and Children Medical and Healthcare Center, comprising 60 mild cases and 30 severe cases. The demographic data, underlying diseases, clinical manifestations and laboratory blood test results were compared between the two groups. The cutoff values were determined by receiver operating characteristic curve analysis. Logistic regression analysis was performed to identify the independent risk factors for severe COVID-19. Results The patients with mild and severe COVID-19 had significant differences in terms of cancer incidence, age, pretreatment neutrophil-to-lymphocyte ratio (NLR), and pretreatment C-reactive protein-to-albumin ratio (CAR) ( P =0.000; P =0.008; P=0.000; P =0.000). The severity of COVID-19 was positively correlated with comorbid cancer, age, NLR, and CAR ( P <0.005). Multivariate logistic regression analysis showed that age, the NLR and the CAR were independent risk factors for severe COVID-19 (OR=1.086, P =0.008; OR=1.512, P =0.007; OR=17.652, P =0.001). Conclusion An increased CAR can serve as an early warning sign of severe COVID-19 in conjunction with the NLR and age.

scholarly journals Prognostic value of the neutrophil-to-lymphocyte ratio in acute organophosphorus pesticide poisoning

2021 ◽  
Vol 16 (1) ◽  
pp. 703-710
Author(s):  
Yuhang Mu ◽  
Boqi Hu ◽  
Nan Gao ◽  
Li Pang
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Hospital Mortality ◽  
Logistic Regression Analysis ◽  
Poor Prognosis ◽  
Prognostic Value ◽  
Organophosphorus Pesticide ◽  
Neutrophil To Lymphocyte Ratio ◽  
Pesticide Poisoning ◽  
Lymphocyte Ratio

Abstract This study investigates the ability of blood neutrophil-to-lymphocyte ratio (NLR) to predict acute organophosphorus pesticide poisoning (AOPP). Clinical data of 385 patients with AOPP were obtained within 24 h of admission, and NLR values were calculated based on neutrophil and lymphocyte counts. The patients were divided into two groups – good and poor – based on prognosis. Poor prognosis included in-hospital death and severe poisoning. The factors affecting prognosis were analyzed by logistic regression analysis, and the prognostic value of NLR was evaluated using the area under the receiver operating characteristic curve (AUC). Univariate logistic regression analysis showed that NLR levels, serum cholinesterase, and creatinine levels were good predictors of AOPP. Multivariate logistic regression analysis showed that high NLR was an independent risk factor for severe poisoning (adjusted odds ratio [AOR], 1.13; 95% CI, 1.10–1.17; p < 0.05) and in-hospital mortality (AOR, 1.07; 95% CI, 1.03–1.11; p < 0.05). NLR values >13 and >17 had a moderate ability to predict severe poisoning and in-hospital mortality, respectively (AUC of 0.782 [95% CI, 0.74–0.824] and 0.714 [95% CI, 0.626–0.803], respectively). Our results show that high NLR at admission is an independent indicator of poor prognosis in AOPP and can be used to optimize treatment and manage patients.

Risk Factors for Silent Cerebral Infarcts in a Pediatric Sickle Cell Anemia (SCA) Cohort

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 2487-2487 ◽  
Author(s):  
Francoise Bernaudin ◽  
Suzanne Verlhac ◽  
Annie Kamdem ◽  
Cécile Arnaud ◽  
Lena Coïc ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Risk Factor ◽  
Logistic Regression Analysis ◽  
G6pd Deficiency ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
History Of ◽  
Independent Risk Factors

Abstract Background Silent infarcts are associated with impaired cognitive functioning and have been shown to be predictors of stroke (Miller ST J Pediatr 2001). Until now, reported risk factors for silent infarcts were low pain event rate, history of seizures, high leukocyte count and Sen bS haplotype (Kinney TR Pediatrics 1999). Here, we seek to define the prevalence and risk factors of silent infarcts in the Créteil SCA pediatric cohort comprising patients assessed at least yearly by transcranial doppler (TCD) since 1992, and by MRI/MRA. Methods This study retrospectively analyzed data from the Créteil cohort stroke-free SS/Sb0 children (280; 134 F, 146 M), according to institutional review board. Time-averaged mean of maximum velocities higher than 200 cm/sec were considered as abnormal, resulting in initiation of a transfusion program (TP). A switch to hydroxyurea was proposed to patients with normalized velocities (&lt; 170 cm/sec) and normal MRA on TP, although TP was re-initiated in case of abnormal velocities recurrence. Patients with “conditional” velocities (170–199 cm/sec) were assessed by TCD 4 times yearly. Alpha genes and beta-globin haplotypes were determined. Baseline biological parameters (G6PD activity; WBC, PMN, Reticulocytes, Platelets counts; Hemoglobin, Hematocrit, HbF, LDH levels; MCV; SpO2) were obtained a minimum of 3 months away from a transfusion, one month from a painful episode, after 12 months of age, before the first TCD, and always before therapy intensification. Results. Patients were followed for a total of 2139 patient-years. Alpha-Thal was present in 114/254 patients (45%) and 27/241 (11.2%) had G6PD deficiency. Beta genotype, available in 240 patients, was BaBa in 102 (42.5%), BeBe in 54 (22.5%), SeSe in 19 (7.9%) and “other” in 65 (27.1%); TCD was abnormal in 52 of 280 patients (18.6%). MRA showed stenoses in 30 of 226 evaluated patients (13.3%) while MRI demonstrated presence of silent infarcts in 81/280 patients (28.9%). Abnormal TCD (p&lt;0.001), G6PD deficiency (p=0.008), high LDH (p=0.03), and low Hb (p=0.026) were significant risk factors for stenoses by univariate analysis while multivariate analysis retained only abnormal TCD as a significant risk factor for stenoses ([OR= 10.6, 95% CI (4.6–24.4)]; p&lt;0.001). Univariate logistic regression analysis showed that the risk of silent infarcts was not related to alpha-Thal, beta genotype, abnormal TCD, WBC, PMN, platelets, reticulocyte counts, MCV, LDH level, HbF %, pain or ACS rates but was significantly associated with stenoses detected by MRA (p&lt;0.001), gender (male; p=0.04), G6PD deficiency (p=0.05), low Hb (p=0.016) and Hct (p=0.012). Multivariate logistic regression analysis showed that gender ([OR= 2.1, 95% CI (1.03–4.27)]; p=0.042), low Hb ([OR= 1.4, 95% CI (1.0–1.1)]; p=0.05) and stenoses ([OR= 4.8, 95% CI (1.88–12.28)]; p=0.001) were all significant independent risk factors for silent infarcts. The presence of stenoses was the only significant risk factor for silent infarcts in patients with a history of abnormal TCD ([OR= 5.9, 95% CI (1.6–21.7)]; p=0.008). Conclusion We recently showed that G6PD deficiency, absence of alpha-Thal, and hemolysis are independent significant risk factors for abnormal TCD in stroke-free SCA patients (Bernaudin et al, Blood, 2008, in press). Here, we report that an abnormal TCD is the most significant risk factor for stenoses and, expanding previous studies, we demonstrate that stenoses, low Hb and gender are significant independent risk factors for silent infarcts.

scholarly journals Association of Biomarkers Related to Preoperative Inflammatory and Coagulation with Postoperative In-Hospital Deaths in Patients with Type A Acute Aortic Dissection

2021 ◽  
Author(s):  
Ming Li ◽  
Haifeng Sun ◽  
Suochun Xu ◽  
Yang Yan ◽  
Haichen Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Value ◽  
Multivariate Logistic Regression Analysis ◽  
Type A ◽  
Hospital Deaths ◽  
Independent Risk Factors ◽  
D Dimer

Abstract Background: The aim of this study was to analyze the predictive value of biomarkers related to preoperative inflammatory and coagulation in the prognosis of patients with type A acute aortic dissection (AAD). Methods: A total of 206 patients with type A AAD who had received surgical treatment were enrolled. Patients were divided into two groups according to whether they died during hospitalization. Peripheral blood samples were collected before anesthesia induction. Preoperative levels of D-dimer, fibrinogen (FIB), platelet (PLT), white blood cells (WBC) and neutrophil (NEU) between the two groups were compared. Univariate and multivariate logistic regression analysis were utilized to identify the independent risk factors for postoperative in-hospital deaths of patients with type A AAD. Receiver operating characteristic (ROC) curve were used to analyze the predictive value of D-dimer, FIB, PLT, WBC, NEU and CRP in the prognosis of the patients. Results: Univariate logistic regression analysis showed that the P values of the five parameters including D-dimer, FIB, PLT, WBC and NEU were all less than 0.1, which may be risk factors for postoperative in-hospital deaths of patients with type A AAD. Further multivariate logistic regression analysis indicated that higher preoperative D-dimer and WBC levels were independent risk factors for in-hospital deaths of patients with type A AAD. ROC curve analysis indicated that FIB+PLT combination is provided with the highest predictive value for in-hospital deaths.Conclusion: Both preoperative D-dimer and WBC in patients with type A AAD may be used as independent risk factors for the prognosis of such patients. Combined use of FIB and PLT may improve the accuracy and accessibility of clinical prognostic assessment.

scholarly journals The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhichuang Lian ◽  
Yafang Li ◽  
Wenyi Wang ◽  
Wei Ding ◽  
Zongxin Niu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Prediction Model ◽  
Logistic Regression Analysis ◽  
Roc Curve ◽  
Curve Analysis ◽  
Severe Illness ◽  
Roc Curve Analysis ◽  
Underlying Diseases

This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients’ admissions. The clinical data of 1046 COVID-19 patients admitted to a designated hospital in a certain city from July to September 2020 were retrospectively analyzed, the clinical characteristics of the patients were collected, and a multivariate unconditional logistic regression analysis was used to determine the risk factors for severe illnesses in COVID-19 patients during hospitalization. Based on the analysis results, a prediction model for severe conditions and the ROC curve were constructed, and the predictive value of the model was assessed. Logistic regression analysis showed that age (OR = 3.257, 95% CI 10.466–18.584), complications with chronic obstructive pulmonary disease (OR = 7.337, 95% CI 0.227–87.021), cough (OR = 5517, 95% CI 0.258–65.024), and venous thrombosis (OR = 7322, 95% CI 0.278–95.020) were risk factors for COVID-19 patients developing severe conditions during hospitalization. When complications were not taken into consideration, COVID-19 patients’ ages, number of diseases, and underlying diseases were risk factors influencing the development of severe illnesses. The ROC curve analysis results showed that the AUC that predicted the severity of COVID-19 patients at admission was 0.943, the optimal threshold was −3.24, and the specificity was 0.824, while the sensitivity was 0.827. The changes in the condition of severe COVID-19 patients are related to many factors such as age, clinical symptoms, and underlying diseases. This study has a certain value in predicting COVID-19 patients that develop from mild to severe conditions, and this prediction model is a useful tool in the quick prediction of the changes in patients’ conditions and providing early intervention for those with risk factors.

scholarly journals Diabetes and Younger Age Are Vital and Independent Risk Factors for Acute Pancreatitis in Patients with Severe Hypertriglyceridemia

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
Qiang Li ◽  
Chaoqun Hou ◽  
Yunpeng Peng ◽  
Xiaole Zhu ◽  
Chenyuan Shi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Pancreatitis ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Severe Hypertriglyceridemia ◽  
Younger Age ◽  
History Of ◽  
Independent Risk Factors

Background. The incidence of hypertriglyceridemia-induced acute pancreatitis (HIAP) is increasing worldwide, and now it is the third leading cause of acute pancreatitis in the United States. But, there are only 5% of patients with severe hypertriglyceridemia (>1000 mg/dl) which might generate acute pancreatitis. In order to explore which part of the patients is easy to develop into pancreatitis, a case-control study was performed by us to consider which patient population tend to develop acute pancreatitis in patients with severe hypertriglyceridemia. To perform a retrospective case-control study, we identified severe hypertriglyceridemia patients without AP (HNAP) and with HIAP with a fasting triglyceride level of >1000 mg/dl from The First Affiliated Hospital of Nanjing Medical University during January 1, 2014, to December 31, 2016. Baseline patient characteristics, comorbidities, and risk factors were recorded and evaluated by the univariate and multivariate logistic regression analysis for HIAP and HNAP patients. A total of 124 patients with severe hypertriglyceridemia were included in this study; of which, 62 patients were in the HIAP group and 62 were in the HNAP group. Univariate logistic regression analysis showed that there was no gender difference in both groups; however, there were more younger patients in the HIAP group than in the HNAP group (P value < 0.001), and the HIAP group had low level of high-density lipoprotein compared to the HNAP group (P<0.05). Meanwhile, the presence of pancreatitis was associated with higher level of glycemia and a history of diabetes (P<0.05). Multivariate logistic regression analysis indicated that a history of diabetes and younger age were independent risk factors for acute pancreatitis in patients with severe hypertriglyceridemia. Uncontrolled diabetes and younger age are potential risk factors in patients with severe hypertriglyceridemia to develop acute pancreatitis.

Gender-specific association between neutrophil-to-lymphocyte ratio and arterial stiffness in an apparently healthy population undergoing a health examination

Vascular ◽  
2019 ◽  
Vol 27 (6) ◽  
pp. 668-676
Author(s):  
Yihu Yi ◽  
Lingyun Zhou ◽  
Shanru Zuo ◽  
Wenjun Yin ◽  
Daiyang Li ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Arterial Stiffness ◽  
Logistic Regression Analysis ◽  
Partial Correlation ◽  
Neutrophil To Lymphocyte Ratio ◽  
Healthy Population ◽  
Lymphocyte Ratio ◽  
Apparently Healthy

Objective Neutrophil-to-lymphocyte ratio (NLR) value has emerged as a cardiovascular prognostic marker. Although several recent studies suggested NLR was associated with arterial stiffness, it was still controversial. The aim of this study was to investigate the correlation between NLR and arterial stiffness by measuring of brachial-ankle pulse wave velocity (baPWV) in an apparently healthy population. Methods This retrospective study enrolled 5612 participants during the health examinations from 1 October 2007 to 30 September 2011. Arterial stiffness was measured by baPWV. NLR was calculated as the ratio of the absolute neutrophil count to the absolute lymphocyte count in peripheral blood. According to the quartiles of NLR, the patients were categorized into four groups in males and females, respectively. Associations between NLR and baPWV were evaluated using partial correlation and multivariate logistic regression analysis. Results Both female and male subjects with increased arterial stiffness (baPWV ≥ 1400 cm/s) were likely to be older (females: P < 0.001, males: P < 0.001) and have higher systolic blood pressure (females: P < 0.001, males: P < 0.001), diastolic blood pressure (females: P < 0.001, males: P < 0.001), fasting plasma glucose (females: P < 0.001, males: P < 0.001), serum total cholesterol (females: P < 0.001, males: P = 0.028), triglyceride (females: P < 0.001, males: P = 0.031), urea nitrogen (females: P < 0.001, males: P < 0.001) than those without increased arterial stiffness. In addition, compared to those without increased arterial stiffness, body mass index ( P < 0.001), waist circumference ( P < 0.001), low-density lipoproteins cholesterol ( P < 0.001), creatinine ( P < 0.001), uric acid ( P < 0.001) and lymphocytes ( P = 0.001) were higher in females with increased arterial stiffness. However, males with increased arterial stiffness had higher NLR value (2.0 ± 0.7 vs. 2.1 ± 0.9, P < 0.001) and neutrophils (4.3 ± 1.4 vs. 4.5 ± 1.5, P < 0.001) than those without increased arterial stiffness, while the difference was not found in females. ANCOVA showed that males with quartile 3 and quartile 4 of NLR had greater levels of baPWV. NLR was correlated to baPWV in males by partial correlation analysis (r = 0.110, P < 0.001), but not in females. In multiple logistic regression analysis, the quartile 4 of NLR was positively associated with increased arterial stiffness in males (OR = 1.43, 95% confidence intervals [CI]=1.12–1.82, P = 0.004), but there was no obvious correlation in females. Conclusions Our findings suggest that there is a gender difference in the relationship between arterial stiffness and NLR. After adjusting for other confounders, the risk of increased arterial stiffness in apparently healthy adult males (rather than females) is independently associated with the highest quartile of NLR.

scholarly journals P05.69 Independent risk factors for pre- and postoperative seizures in meningioma patients identified by logistic regression analysis

2018 ◽  
Vol 20 (suppl_3) ◽  
pp. iii319-iii319
Author(s):  
L Goertz ◽  
C Hamisch ◽  
N Erdner ◽  
H Muders ◽  
R Goldbrunner ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Independent Risk Factors

scholarly journals Prognostic Value of Neutrophil-to-Lymphocyte Ratio in Patients With Sepsis

2021 ◽  
Author(s):  
Xinyu Liao ◽  
Fuxing Li ◽  
Fuke Wang ◽  
Guoliang Wang ◽  
Yaxing Zheng ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Sofa Score ◽  
Prognostic Value ◽  
Laboratory Data ◽  
Neutrophil To Lymphocyte Ratio ◽  
Univariate Logistic Regression Analysis ◽  
Lymphocyte Ratio ◽  
Reactive Protein

Abstract Objective: We attempt to evaluate the role of neutrophil-to-lymphocyte ratio (NLR) in predicting 28-day mortality in patients with sepsis to investigate its prognostic value.Method: Relevant clinical and laboratory data of 91 healthy controls, 87 non-septic patients admitted to intensive care unit (ICU) and 127 septic patients on admission were collected, and septic patients were divided into survival (n=79) and death groups (n=48) according to their prognoses. NLR levels among different groups were compared and analyzed for associations with C-reactive protein (CRP), procalcitonin (PCT) and SOFA score. Univariate logistic regression analysis was used to assess the prognostic value of the NLR in patients with sepsis. Result: The NLR level was significantly higher in the septic patients compared to the case controls and healthy individuals (P < 0.05), and was much higher in septic patients who died (P < 0.05). ROC analysis indicated that the NLR had the best prognostic value for sepsis, with an AUC of 0.77 (95% CI: 0.69-0.84). Univariate logistic regression analysis suggested that NLR >8.25 was an independent risk factor for sepsis (odds ratio [OR] 6.39, P = 0.001). Correlation analysis suggested that the NLR was positively correlated with CRP, PCT and SOFA score.Conclusion: Peripheral serum NLR appeares to have a predictive value for 28-day mortality in patients with sepsis.

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