Effect of acute alcohol intoxication on mortality, coagulation, and fibrinolysis in trauma patients

Background The effect of alcohol on the outcome and fibrinolysis phenotype in trauma patients remains unclear. Hence, we performed this study to determine whether alcohol is a risk factor for mortality and fibrinolysis shutdown in trauma patients. Materials and methods A total of 686 patients who presented to our trauma center and underwent rotational thromboelastometry were included in the study. The primary outcome was in-hospital mortality. Logistic regression analysis was performed to determine whether alcohol was an independent risk factor for in-hospital mortality and fibrinolysis shutdown. Results The rate of in-hospital mortality was 13.8% and blood alcohol was detected in 27.7% of the patients among our study population. The patients in the alcohol-positive group had higher mortality rate, higher clotting time, and lower maximum lysis, more fibrinolysis shutdown, and hyperfibrinolysis than those in the alcohol-negative group. In logistic regression analysis, blood alcohol was independently associated with in-hospital mortality (odds ratio [OR] 2.578; 95% confidence interval [CI], 1.550–4.288) and fibrinolysis shutdown (OR 1.883 [95% CI, 1.286–2.758]). Within the fibrinolysis shutdown group, blood alcohol was an independent predictor of mortality (OR 2.168 [95% CI, 1.030–4.562]). Conclusions Alcohol is an independent risk factor for mortality and fibrinolysis shutdown in trauma patients. Further, alcohol is an independent risk factor for mortality among patients who experienced fibrinolysis shutdown.

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14-3-3η Protein in Rheumatoid Arthritis: Promising Diagnostic Marker and Independent Risk Factor for Osteoporosis

Laboratory Medicine ◽

10.1093/labmed/lmaa001 ◽

2020 ◽

Vol 51 (5) ◽

pp. 529-539

Author(s):

Tingting Zeng ◽

Liming Tan ◽

Yang Wu ◽

Jianlin Yu

Keyword(s):

Rheumatoid Arthritis ◽

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Logistic Regression Analysis ◽

Independent Risk Factor ◽

Multiple Logistic Regression Analysis ◽

Area Under The Curve ◽

Enzyme Linked Immunosorbent Assay ◽

Disease Monitoring

Abstract Background Early identification and disease monitoring are challenges facing rheumatologists in the management of rheumatoid arthritis (RA). Methods We utilized enzyme-linked immunosorbent assay (ELISA) to determine 14-3-3η and anticyclic citrullinated peptide antibody (anti-CCP) levels, with rheumatoid factor (RF) level detected by rate nephelometry. The diagnostic value of each index was determined via receiver operating characteristic (ROC) curve, and the association between 14-3-3η and osteoporosis was assessed using multiple logistic regression analysis. Results Serum levels of 14-3-3η were 3.26 ng per mL in patients with RA. These levels were helpful in identifying patients with the disease, with the area under the curve (AUC) being 0.879 and 0.853, respectively, from all healthy control individuals and patients with RA. Combining 14-3-3η with RF or anti-CCP increased the diagnostic rate. Logistic regression analysis identified 14-3-3η as an independent risk factor for RA-related osteoporosis (odds ratio [OR], 1.503; 95% confidence interval [CI], 1.116–2.025; P <.01). Conclusions Serum 14-3-3η detection by itself or combined with other serum indices was helpful in differentiating patients with RA. Also, it was a promising biomarker for disease monitoring in RA.

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Pre-existing interstitial lung abnormalities are risk factors for immune checkpoint inhibitor-induced interstitial lung disease in non-NSCLC cancers.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e15171 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e15171-e15171

Author(s):

Kiyofumi Shimoji ◽

Takeshi Masuda ◽

Yu Nakanishi ◽

Kakuhiro Yamaguchi ◽

Shinjiro Sakamoto ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Interstitial Lung Disease ◽

Lung Disease ◽

Logistic Regression Analysis ◽

Independent Risk Factor ◽

Patient Characteristics ◽

Significant Difference

e15171 Background: Immune check point inhibitor (ICI) induced interstitial lung disease (ICI-ILD) is a clinically serious and life-threatening toxicity. Pre-existing ILD has been reported to be a risk factor for ICI-ILD in patients with non-small cell lung cancer (NSCLC). In addition, we have previously reported that interstitial lung abnormality (ILA) is also a risk factor for the ICI-ILD. Therefore, we investigated whether any patient characteristics, including ILA, were risk factors for ICI-ILD in patients with non-NSCLC cancers. Methods: Head and neck cancer, malignant melanoma, oral cavity cancer, renal cell carcinoma or gastric cancer patients who received anti PD-1 antibody (Nivolumab or Pembrolizumab) at Hiroshima University Hospital from December 2015 to May 2019 were enrolled. Information on patient characteristics before anti-PD-1 antibody administration, including chest CT findings and laboratory data, were obtained. Results: Two hundred patients were enrolled, and 20 (10%) developed ICI-ILD. Grade1 was observed in 15 patients, grade2 in 3, and grade3 and 5 in 1. There was no significant difference in the background factors between patients with and without ICI-ILD. On the other hand, the proportion of patients with ILA was significantly higher in the patients with ICI-ILD than those without (P < 0.01). Furthermore, univariate logistic regression analysis revealed ILA was the risk factor for ICI-ILD (p < 0.01), and multivariate logistic regression analysis showed that GGA or reticulation in ILA was an independent risk factor for ICI-ILD (p = 0.016, 0.011). Conclusions: Pre-existing ILA is a risk factor for ICI-ILD, and GGA or reticulation in ILA is an independent risk factor for ICI-ILD in patients with non-NSCLC cancers. Therefore, we should pay more attention to the development of ICI-ILD in patients with ILA, especially GGA or reticulation.

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Association of Japan Coma Scale score on hospital arrival with in-hospital mortality among trauma patients

BMC Emergency Medicine ◽

10.1186/s12873-019-0282-x ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 2

Author(s):

Tetsuya Yumoto ◽

Hiromichi Naito ◽

Takashi Yorifuji ◽

Toshiyuki Aokage ◽

Noritomo Fujisaki ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Hospital Mortality ◽

Logistic Regression Analysis ◽

Multiple Logistic Regression Analysis ◽

Trauma Patients ◽

Multiple Logistic Regression ◽

Point Scale ◽

Hospital Arrival ◽

Coma Scale

Abstract Background The Japan Coma Scale (JCS) score has been widely used to assess patients’ consciousness level in Japan. JCS scores are divided into four main categories: alert (0) and one-, two-, and three-digit codes based on an eye response test, each of which has three subcategories. The purpose of this study was to investigate the utility of the JCS score on hospital arrival in predicting outcomes among adult trauma patients. Methods Using the Japan Trauma Data Bank, we conducted a nationwide registry-based retrospective cohort study. Patients 16 years old or older directly transported from the trauma scene between January 2004 and December 2017 were included. Our primary outcome was in-hospital mortality. We examined outcome prediction accuracy based on area under the receiver operating characteristic curve (AUROC) and multiple logistic regression analysis with multiple imputation. Results A total of 222,540 subjects were included; their in-hospital mortality rate was 7.1% (n = 15,860). The 10-point scale JCS and the total sum of Glasgow Coma Scale (GCS) scores demonstrated similar performance, in which the AUROC (95% CIs) showed 0.874 (0.871–0.878) and 0.878 (0.874–0.881), respectively. Multiple logistic regression analysis revealed that the higher the JCS score, the higher the predictability of in-hospital death. When we focused on the simple four-point scale JCS score, the adjusted odds ratio (95% confidence intervals [CIs]) were 2.31 (2.12–2.45), 4.81 (4.42–5.24), and 27.88 (25.74–30.20) in the groups with one-digit, two-digit, and three-digit scores, respectively, with JCS of 0 as a reference category. Conclusions JCS score on hospital arrival after trauma would be useful for predicting in-hospital mortality, similar to the GCS score.

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Lipoprotein(a) and coronary artery disease in Chinese postmenopausal female patients: a large cross-sectional cohort study

Postgraduate Medical Journal ◽

10.1136/postgradmedj-2019-136591 ◽

2019 ◽

Vol 95 (1128) ◽

pp. 534-540 ◽

Cited By ~ 1

Author(s):

Shuo-Lin Liu ◽

Na-Qiong Wu ◽

Yuan-Lin Guo ◽

Cheng-Gang Zhu ◽

Ying Gao ◽

...

Keyword(s):

Coronary Artery Disease ◽

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Coronary Artery ◽

Logistic Regression Analysis ◽

Independent Risk Factor ◽

Lipoprotein A ◽

Female Patients ◽

Artery Disease

BackgroundIt has been reported that lipoprotein(a) (Lp(a)) is associated with the risk of cardiovascular disease. The present study aimed to examine the association of Lp(a) levels with the presence and severity of coronary artery disease (CAD) in female patients.MethodsA total of 3712 female patients who received coronary angiography were consecutively enrolled. The levels of Lp(a) were measured and compared among patients with or without CAD, myocardial infarction and menopause. Spearman correlation analysis and logistic regression analysis were used to examine the association of Lp(a) with the presence of CAD and the severity of coronary atherosclerosis assessed by Gensini score (GS).ResultsThe average of Lp(a) levels was elevated as age increased in female subjects. Notably, women after menopause had higher Lp(a) levels compared with that before menopause (16.8 mg/dL (IQR 7.54–41.12 mg/dL) vs 14.7 mg/dL (IQR 6.72–30.82 mg/dL), p=0.002). Furthermore, multiple logistic regression analysis identified that Lp(a)>30 mg/dL was an independent risk factor of CAD in the postmenopausal females (OR: 1.33, 95% CI: 1.08 to 1.63, p=0.007). Finally, Lp(a) had a positive correlation with GS (r=0.11, p<0.001), and Lp(a)>30 mg/dL was an independent risk factor for high GS (OR: 1.43, 95% CI: 1.14 to 1.79, p=0.02) in the postmenopausal females.ConclusionCirculating Lp(a) levels were independently associated with the presence and severity of CAD in the postmenopausal females, suggesting that Lp(a) may be useful for prevention and risk-stratification of CAD in female individuals.

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Branches of the brachiocephalic was an independent risk factor for hemorrhagic pulmonary sheath (HPS) patients with acute Stanford A aortic dissection

10.21203/rs.2.14309/v2 ◽

2020 ◽

Author(s):

Qiuxia Xie ◽

Haoling Qin ◽

Ling Lin ◽

Jian Guan ◽

Xuhui Zhou

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Aortic Dissection ◽

Logistic Regression Analysis ◽

Independent Risk Factor ◽

Conditional Logistic Regression ◽

Case Group ◽

Conditional Logistic Regression Analysis

Abstract Background: AAD refers to the blood flow into the middle membrane through the intimal rupture of the aorta. Hemorrhagic pulmonary sheath (HPS) is a common complication of Stanford-A AAD. The risk factors of HPS are remaining unclear Methods: In this study, we have probed the potential risk factors of HPS patients with acute Stanford A aortic dissection. 18 HPS patients with acute Stanford A aortic dissection were selected as the case group. The age difference ± 5 years and the same sex are set as the matching principles. 36 patients with acute Stanford-A type AD who did not detect HPS in the same period were matched according to the ratio of 1:2. Demographic data, treatment methods, AD-related disease history, clinical symptoms and Charlson comorbidity index (CCI) values of each patient were collected. Meanwhile, the values of the maximum diameter of ascending aorta (mm), aortic dissection range, and the main branch of the aorta, pleural effusion/blood, and pericardial effusion/blood were measured by two experienced cardiovascular radiological physicians. Univariate and multivariate conditional logistic regression analysis was used in this study. Results: CCI value and the branches of the brachiocephalic in the case group were significantly higher than those in the control group (p<0.05). Univariate conditional logistic regression analysis showed CCI and branches of the brachiocephalic were associated with HPS. Multivariate conditional logistic regression analysis suggested that branches of the brachiocephalic were an independent risk factor for HPS (OR=7.02, 95%CI=1.28-38.62, p=0.025). Conclusions: Branches of the brachiocephalic were an independent risk factor for HPS.

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

10.21203/rs.3.rs-32889/v1 ◽

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.

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Association between the Japan Coma Scale scores at the scene of injury and in-hospital outcomes in trauma patients: an analysis from the nationwide trauma database in Japan

BMJ Open ◽

10.1136/bmjopen-2019-029706 ◽

2019 ◽

Vol 9 (7) ◽

pp. e029706 ◽

Cited By ~ 3

Author(s):

Yohei Okada ◽

Takeyuki Kiguchi ◽

Ryoji Iiduka ◽

Wataru Ishii ◽

Taku Iwami ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Cohort Study ◽

Hospital Mortality ◽

Logistic Regression Analysis ◽

Prehospital Care ◽

Multivariate Logistic Regression Analysis ◽

Trauma Patients ◽

Multivariate Logistic Regression ◽

Coma Scale

ObjectiveJapan Coma Scale (JCS) is a grading system used to evaluate disturbed consciousness in prehospital care settings. We aimed to identify the association between the JCS levels at the scene with in-hospital mortality, as well as the discrimination ability for the outcomes.DesignA retrospective cohort study based on the nationwide trauma database in Japan.SettingMulticentre cohort study using data from the Japan Trauma Data Bank, which is a nationwide, prospective, observational trauma registry derived from 235 hospitals.ParticipantsAdult trauma victims transferred directly from the scene of injury to the hospital from January 2004 to December 2017 were eligible for inclusion.Primary and secondary outcomesPrimary outcome was the association between the JCS levels at the scene with in-hospital mortality. We conducted a multivariate logistic regression analysis to calculate the adjusted ORs of JCS levels with 95% CIs for in-hospital mortality. We also calculated the c-statistics for in-hospital mortality.Results164 723 patients were included in the analysis. In a multivariate logistic regression analysis, the corresponding adjusted ORs of JCS levels 2 and 3 referred to level 1 for in-hospital mortality were 4.1 (95% CI 3.8 to 4.4) and 26.0 (95% CI 24.8 to 27.2). The c-statistics of the JCS level for in-hospital mortality was 0.845 (95% CI 0.842 to 0.849).ConclusionsData from large multicentre prospective registry revealed strong associations of the JCS level at the scene of injury with in-hospital mortality as well as the good discriminatory performance for this outcome.

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Branches of the brachiocephalic was an independent risk factor for hemorrhagic pulmonary sheath (HPS) patients with acute Stanford A aortic dissection

10.21203/rs.2.14309/v3 ◽

2020 ◽

Author(s):

Qiuxia Xie ◽

Haoling Qin ◽

Ling Lin ◽

Jian Guan ◽

Xuhui Zhou

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Aortic Dissection ◽

Logistic Regression Analysis ◽

Independent Risk Factor ◽

Conditional Logistic Regression ◽

Case Group ◽

Conditional Logistic Regression Analysis

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

Open Life Sciences ◽

10.1515/biol-2021-0069 ◽

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.

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