Predictive performance of emergency department-specific variables on COVID-19 pneumonia

Introduction: The majority of patients with COVID-19 infection do not progress to pneumonia. We report emergency department (ED)-specific variables and evaluate their predictive performance on diagnosis of pneumonia, intensive care unit (ICU) admission and death. Methods: This was a retrospective, single-centre cohort study of confirmed COVID-19 patients admitted to a Singapore tertiary hospital. Primary outcome was diagnosis of COVID-19 pneumonia. Secondary outcomes were ICU admission and/or death. Multivariate logistic regression was used to analyse the predictive performance of ED-specific variables. Accuracy of continuous variables was measured by area under receiver operating characteristic (ROC) curve. Results: 294 patients were included. Patients with pneumonia were older (52.0 years, p < 0.001) and had higher C-reactive protein (CRP; 33.8 mg/L, p < 0.001). Patients with indeterminate chest radiograph (CRX) findings were at risk of pneumonia vs. patients with normal CRX (37.5% vs. 4.3%, p < 0.001). Patients admitted to ICU were older (60.0 years, p < 0.001) and had higher CRP (40.0 mg/L, p < 0.001). Diagnosis of COVID-19 pneumonia was associated with ICU admission and death (30.0% vs 0.39%, p < 0.001). Multivariate logistic regression analysis showed that age (aOR 1.07, p = 0.049), CRP (aOR 1.05, p = 0.006) and CRX findings (aOR 50.00, p < 0.001) had increased odds of pneumonia. ROC curve analysis showed that CRP of 23.3 mg/L was the optimal cut-off for predicting pneumonia. Conclusion: Older age, higher CRP and CRX findings are associated with COVID-19 pneumonia, ICU admission and death. Prospective studies should be undertaken to validate these findings.

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Endocan, a Risk Factor for Developing Acute Respiratory Distress Syndrome among Severe Pneumonia Patients

Canadian Respiratory Journal ◽

10.1155/2019/2476845 ◽

2019 ◽

Vol 2019 ◽

pp. 1-6 ◽

Cited By ~ 4

Author(s):

Jun Ying ◽

Danfei Zhou ◽

Tongjie Gu ◽

Jianda Huang

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Acute Respiratory Distress Syndrome ◽

Distress Syndrome ◽

Multivariate Logistic Regression Analysis ◽

Severe Pneumonia ◽

Curve Analysis ◽

Multivariate Logistic Regression ◽

Roc Curve Analysis

Background. Severe pneumonia (SP) has been widely accepted as a major cause for acute respiratory distress syndrome (ARDS), and the development of ARDS is significantly associated with increased mortality. This study aimed to identify potential predictors for ARDS development in patients with SP. Methods. Eligible SP patients at admission from January 2013 to June 2017 were prospectively enrolled, and ARDS development within hospital stay was identified. Risk factors for ARDS development in SP patients were analyzed by univariate and multivariate logistic regression analysis. The receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC) was performed for the predictive value of endocan for ARDS development. Results. A total of 145 SP patients were eventually enrolled into the final analysis, of which 37 developed ARDS during the hospital stay. Our final multivariate logistic regression analysis suggested plasma endocan expression as the only independent risk factor for ARDS development in SP patients (OR: 1.57, 95% CI: 1.14–2.25, P=0.021). ROC curve analysis of plasma endocan resulted in an AUC of 0.754, 95% CI of 0.642–0.866, a cutoff value of 11.6 ng/mL, a sensitivity of 78.7%, and a specificity of 70.3%, respectively (P<0.01). Conclusions. Endocan expression at ICU admission is a reliable predictive factor in predicting ARDS in patients with SP.

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Title: Preoperative albumin-to-fibrinogen ratio predicts postoperative pulmonary complications in patients after minimally invasive esophagectomy

10.21203/rs.3.rs-604731/v1 ◽

2021 ◽

Author(s):

Zhang Peng ◽

Zhao Song

Keyword(s):

Risk Factors ◽

Esophageal Cancer ◽

Logistic Regression ◽

Roc Curve ◽

Training Group ◽

Pulmonary Complications ◽

Curve Analysis ◽

Postoperative Pulmonary Complications ◽

Multivariate Logistic Regression ◽

Roc Curve Analysis

Abstract Background Postoperative pulmonary complications (PPCs) are the most common postoperative complications in patients with esophageal cancer. Prediction of PPCs by establishing a preoperative physiological function parameter model can help patients make adequate preoperative preparation, reduce treatment costs, and improve prognosis and quality of life. The purpose of this study was to investigate the relationship between albumin-to-fibrinogen ratio (AFR), prognostic nutritional index (PNI), albumin-to-globulin ratio (AGR), neutrophils-to-lymphocyte ratio (NLR), platelet-to-lymphocyte (PLR), and monocyte-to -lymphocyte ratio (MLR) and other preoperative laboratory tests and PPCs in patients after esophagectomy. Methods Retrospective analysis was performed on total 712 consecutive patients who underwent esophagectomy in the Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University from July 2018 to December 2020. Patients were divided into training (535 patients) and validation (177) groups for comparison of baseline data, perioperative indicators, and laboratory examination data. Receiver operating characteristic (ROC) curve analysis was used to evaluate the efficacy, sensitivity and specificity of AFR, and Youden’s index was used to calculate the cut-off values of AFR. Univariate and multivariate logistic regression analyses were used to assess the risk factors for PPCs in training group. Results 112 (20.9%) in training group and 36 (20.3%) in validation group developed PPCs. The AUC value predicted by AFR using ROC curve analysis was 0.817, sensitivity 76.2% and specificity 78.7% in training group while AUC 0.803, sensitivity 69.4% and specificity 85.8%. Multivariate logistic regression analysis showed that smoking index, American Society of Anesthesiologists (ASA), AFR, and recurrent laryngeal nerve palsy were independent risk factors for PPCs. Conclusion Preoperative AFR can effectively predict the occurrence of PPCs in patients with esophageal cancer

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Serum Irisin Predicts Mortality Risk in Acute Heart Failure Patients

Cellular Physiology and Biochemistry ◽

10.1159/000477867 ◽

2017 ◽

Vol 42 (2) ◽

pp. 615-622 ◽

Cited By ~ 12

Author(s):

Shutong Shen ◽

Rongrong Gao ◽

Yihua Bei ◽

Jin Li ◽

Haifeng Zhang ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Multivariate Logistic Regression Analysis ◽

Curve Analysis ◽

Multivariate Logistic Regression ◽

Roc Curve Analysis ◽

Kaplan Meier ◽

All Cause Mortality

Background/Aims: Irisin is a peptide hormone cleaved from a plasma membrane protein fibronectin type III domain containing protein 5 (FNDC5). Emerging studies have indicated association between serum irisin and many major chronic diseases including cardiovascular diseases. However, the role of serum irisin as a predictor for mortality risk in acute heart failure (AHF) patients is not clear. Methods: AHF patients were enrolled and serum was collected at the admission and all patients were followed up for 1 year. Enzyme-linked immunosorbent assay was used to measure serum irisin levels. To explore predictors for AHF mortality, the univariate and multivariate logistic regression analysis, and receiver-operator characteristic (ROC) curve analysis were used. To determine the role of serum irisin levels in predicting survival, Kaplan-Meier survival analysis was used. Results: In this study, 161 AHF patients were enrolled and serum irisin level was found to be significantly higher in patients deceased in 1-year follow-up. The univariate logistic regression analysis identified 18 variables associated with all-cause mortality in AHF patients, while the multivariate logistic regression analysis identified 2 variables namely blood urea nitrogen and serum irisin. ROC curve analysis indicated that blood urea nitrogen and the most commonly used biomarker, NT-pro-BNP, displayed poor prognostic value for AHF (AUCs ≤ 0.700) compared to serum irisin (AUC = 0.753). Kaplan-Meier survival analysis demonstrated that AHF patients with higher serum irisin had significantly higher mortality (P<0.001). Conclusion: Collectively, our study identified serum irisin as a predictive biomarker for 1-year all-cause mortality in AHF patients though large multicenter studies are highly needed.

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Preoperative prediction of papillary thyroid microcarcinoma via multiparameter ultrasound

Acta Radiologica ◽

10.1177/0284185117692167 ◽

2017 ◽

Vol 58 (11) ◽

pp. 1303-1311 ◽

Cited By ~ 8

Author(s):

Hui Juan Ma ◽

Jing Chun Yang ◽

Zhen Peng Leng ◽

Ying Chang ◽

Hua Kang ◽

...

Keyword(s):

Logistic Regression ◽

Roc Curve ◽

Imaging Modality ◽

Multivariate Logistic Regression Analysis ◽

Strain Ratio ◽

Papillary Thyroid Microcarcinoma ◽

Papillary Thyroid ◽

Roc Curve Analysis ◽

Thyroid Microcarcinoma ◽

Heterogeneous Enhancement

Background Accurate diagnosis of papillary thyroid microcarcinoma (PTMC) is important for further management. Ultrasound (US) is the most frequently used imaging modality for PTMC. Purpose To evaluate the diagnostic value of conventional US, contrast-enhanced ultrasound (CEUS) and real-time elastography (RTE) for patients with PTMC. Material and Methods In total, 135 patients with subcentimeter thyroid nodules who underwent conventional US, CEUS, and RTE before surgery were enrolled. A multivariate logistic regression analysis was performed to assess the independent predictors of PTMC. The diagnostic performances of conventional US, CEUS, and RTE were evaluated with a receiver operating characteristic (ROC) curve analysis. Results A taller-than-wide shape was identified as the strongest predictor of PTMC (odds ratio [OR], 25.21), followed by heterogeneous enhancement (OR, 24.03), marked hypoechogenicity (OR, 21.71), poorly defined margin (OR, 5.51), strain ratio (OR, 2.59), and age (OR, 0.92; all P values < 0.05). Heterogeneous enhancement on CEUS showed the highest positive predictive value (PPV; 88.0%) and an accuracy of 83.7%. A logistic regression model was created to predict PTMC using conventional US, CEUS, and RTE. The area under the ROC curve was 0.97, with a sensitivity of 88.6% and a specificity of 94.6%. Conclusion Conventional US combined with CEUS and RTE can improve the diagnostic accuracy of PTMC.

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Development and external validation of a novel nomogram for screening Chinese Lynch syndrome: based on a multicenter, population study

Therapeutic Advances in Medical Oncology ◽

10.1177/17588359211023290 ◽

2021 ◽

Vol 13 ◽

pp. 175883592110232

Author(s):

Mengyuan Yang ◽

Dan Li ◽

Wu Jiang ◽

Lizhen Zhu ◽

Haixing Ju ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Lynch Syndrome ◽

Mismatch Repair ◽

Roc Curve ◽

External Validation ◽

Multivariate Logistic Regression Analysis ◽

Multivariate Logistic Regression ◽

Screening Model ◽

Pathogenic Variants

Background: This multicenter study aimed to reveal the genetic spectrum of colorectal cancer (CRC) with deficient mismatch repair (dMMR) and build a screening model for Lynch syndrome (LS). Methods: Through the immunohistochemical (IHC) screening of mismatch repair protein results in postoperative CRC patients, 311 dMMR cases, whose germline and somatic variants were detected using the ColonCore panel, were collected. Univariate and multivariate logistic regression analysis was performed on the clinical characteristics of these dMMR individuals, and a clinical nomogram, incorporating statistically significant factors identified using multivariate logistic regression analysis, was constructed to predict the probability of LS. The model was validated externally by an independent cohort. Results: In total, 311 CRC patients with IHC dMMR included 95 identified MMR germline variant (LS) cases and 216 cases without pathogenic or likely pathogenic variants in MMR genes (non-Lynch-associated dMMR). Of the 95 individuals, approximately 51.6%, 28.4%, 14.7%, and 5.3% cases carried germline MLH1, MSH2, MSH6, and PMS2 pathogenic or likely pathogenic variants, respectively. A novel nomogram was then built to predict the probability of LS for CRC patients with dMMR intuitively. The receiver operating characteristic (ROC) curve informed that this nomogram-based screening model could identify LS with a higher specificity and sensitivity with an area under curve (AUC) of 0.87 than current screening criteria based on family history. In the external validation cohort, the AUC of the ROC curve reached 0.804, inferring the screening model’s universal applicability. We recommend that dMMR-CRC patients with a probability of LS greater than 0.435 should receive a further germline sequencing. Conclusion: This novel screening model based on the clinical characteristic differences between LS and non-Lynch-associated dMMR may assist clinicians to preliminarily screen LS and refer susceptible patients to experienced specialists.

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Preoperative Albumin-to-Fibrinogen Ratio Predicts Postoperative Pneumonia in Patients with Esophageal Squamous Cell Carcinoma: A Retrospective Study

10.21203/rs.3.rs-127793/v1 ◽

2020 ◽

Author(s):

Peng Zhang ◽

Song Zhao

Keyword(s):

Risk Factors ◽

Esophageal Cancer ◽

Logistic Regression ◽

Roc Curve ◽

Laboratory Tests ◽

Curve Analysis ◽

Postoperative Pneumonia ◽

Function Parameter ◽

Multivariate Logistic Regression ◽

Roc Curve Analysis

Abstract Background: Postoperative pneumonia is the most common postoperative complication in patients with esophageal cancer. Prediction of postoperative pneumonia by establishing a preoperative physiological function parameter model can help patients make adequate preoperative preparation, reduce treatment costs, and improve prognosis and quality of life. The purpose of this study was to investigate the relationship between albumin, fibrinogen, albumin-to-fibrinogen ratio(AFR) , and other preoperative laboratory tests and postoperative pneumonia in patients with esophageal cancer after esophagectomy.Methods: Retrospective analysis was performed on 177 consecutive patients who underwent esophagectomy in the Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University from December 2018 to December 2019.Postoperative pneumonia was defined according to the revised Uniform Pneumonia Score(rUPS).Patients were divided into pneumonia and non-pneumonia groups for comparison of baseline data, perioperative indicators, and laboratory examination data.(Receiver operating characteristic)ROC curve analysis was used to evaluate the efficacy, sensitivity and specificity of AFR, and Youden’s index was used to calculate the cut-off values of AFR and other laboratory tests data. Univariate and multivariate logistic regression analyses were used to assess the risk factors for postoperative pneumoniaResults: Of the 177 patients, 32 (18%) developed postoperative pneumonia. The AUC value predicted by AFR using ROC curve analysis was 0.767, 65.6% sensitivity and 83.4% specificity. Multivariate logistic regression analysis showed that albumin (P=0.013), creatinine (P=0.01), and AFR (P=0.016) were independent risk factors for postoperative pneumonia.Conclusion: Preoperative AFR can effectively predict the occurrence of postoperative pneumonia in patients with esophageal cancer

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The association between hypoglycemia and glycemic variability in elderly patients with type 2 diabetes: cross-sectional study

10.21203/rs.3.rs-128672/v1 ◽

2020 ◽

Author(s):

Takahisa Handa ◽

Akinobu Nakamura ◽

Aika Miya ◽

Hiroshi Nomoto ◽

Hiraku Kameda ◽

...

Keyword(s):

Type 2 Diabetes ◽

Logistic Regression ◽

Regression Analysis ◽

Elderly Patients ◽

Logistic Regression Analysis ◽

Roc Curve ◽

Multivariate Logistic Regression Analysis ◽

Glycemic Variability ◽

Multivariate Logistic Regression

Abstract BackgroundThis study aimed to explore predictive factors of time below target glucose range (TBR) ≥ 1% among patients’ characteristics and glycemic variability (GV) indices using continuous glucose monitoring data in elderly patients with type 2 diabetes.MethodsWe conducted a prospective observational study on 179 (71 female) Japanese outpatients with type 2 diabetes aged ≥ 65 years. The characteristics of the participants with TBR ≥ 1% were evaluated by multivariate logistic regression analysis. Receiver-operating characteristic (ROC) curve analyses of GV indices, comprising coefficient of variation (CV), standard deviation, and mean amplitude of glycemic excursions, were performed to identify the optimal index for the identification of patients with TBR ≥ 1%.ResultsIn the multivariate logistic regression analysis, none of the clinical characteristics, including HbA1c and C-peptide index, were independent markers for TBR ≥ 1%, while all three GV indices showed significant associations with TBR ≥ 1%. Among the three GV indices, CV showed the best performance based on the area under the curve in the ROC curve analyses.ConclusionsAmong elderly patients with type 2 diabetes, CV reflected TBR ≥ 1% most appropriately among the GV indices examined.Trial registration: UMIN-CTR: UMIN000029993. Registered 16 November 2017

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Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios Are Correlated with Complicated Diverticulitis and Hinchey Classification: A Simple Tool to Assess Disease Severity in the Emergency Department

Emergency Medicine International ◽

10.1155/2019/6321060 ◽

2019 ◽

Vol 2019 ◽

pp. 1-6 ◽

Cited By ~ 1

Author(s):

Amir Mari ◽

Tawfik Khoury ◽

Ahmad Lubany ◽

Mohammad Safadi ◽

Moaad Farraj ◽

...

Keyword(s):

Emergency Department ◽

Logistic Regression ◽

Regression Analysis ◽

Univariate Analysis ◽

Multivariate Logistic Regression Analysis ◽

Complicated Diverticulitis ◽

Multivariate Logistic Regression ◽

Hinchey Classification ◽

Group A ◽

Group B

Background and Aim. Rapid identification of patients with complications related to acute diverticulitis who require urgent intervention in the emergency department (ED) is essential. The aim of our study was to determine the role of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in predicting severity of diverticulitis as assessed by Hinchey classification. Patients and Methods. We performed a single retrospective study in EMMS Nazareth Hospital from 4/2014 to 4/2018. Patients were categorized into two groups: group A with mild to moderate complicated diverticulitis (Hinchey 1-2) and group B with severe complicated diverticulitis (Hinchey 3-4). Results. Two hundred twenty-five patients were included. Two hundred seven patients were in group A, and 18 patients were in group B. On univariate analysis, age, NLR, and PLR correlated with advanced Hinchey classification and disease severity (stages 3-4) (OR 1.038, 95% CI 1.001–1.076, P=0.0416; OR 1.192, 95% CI 1.093–1.300, P<0.0001; and OR 1.011, 95% CI 1.005–1.017, P=0.0005, respectively). On multivariate logistic regression analysis, the NLR and PLR remain significantly correlated with Hinchey 3-4 (OR 1.174, 95% CI 1.071–1.286, P=0.0006, and OR 1.008, 95% CI 1.001–1.015, P=0.0209, respectively). The area under the curve (AUC) for the NLR and PLR on univariate analysis was 0.7526 and 0.6748, respectively, and 0.7760 and 0.7391 on multivariate logistic regression analysis, respectively, and receiver-operating characteristic (ROC) curves were drawn. Conclusion. The NLR and PLR independently associated with diverticulitis severity and positively correlated with advanced Hinchey classification. This simple available laboratory tool can be implemented into clinical practice to optimize patient management.

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Prognostic factors, symptoms, and consequences of electrolyte imbalances in patients who suffered from cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.31_suppl.74 ◽

2017 ◽

Vol 35 (31_suppl) ◽

pp. 74-74

Author(s):

Pawel Bryniarski

Keyword(s):

Emergency Department ◽

Logistic Regression ◽

Regression Analysis ◽

Cancer Patients ◽

Logistic Regression Analysis ◽

Multivariate Logistic Regression Analysis ◽

Terminal Cancer ◽

Multivariate Logistic Regression ◽

Risk Of Death ◽

Ps Scale

74 Background: Dyselectrolytemia is a common problem in patients with terminal cancer. It worsens the quality of life and increases the amount of complications. The aim of our study was to determine factors connected with dyselectrolytemia in patients with terminal cancer. Methods: 310 terminal cancer patients admitted to Palliative Care Unit were retrospectively analyzed. Detailed physical examination, medical history and laboratory parameters were taken upon admission. Univariate and multivariate logistic regression analysis were used to determine possible predictors, symptoms and consequences of dyselectrolytemia. Results: On admission 67,74% of patients had dyselectrolytemia. They were more frequently admitted to hospital from Emergency Department (OR=Odds Ratio=2,879, p=probability value=0,00004), had higher PS scale note (OR=1,627, p=0,0001), were more often cachectic (OR=1,915, p=0,0083), had more often constipation (OR=1,728,p=0,0275), were more often dehydrated (OR=2,609 ,p=0,0007), had lower albumin level (OR=0,909, p=0,00001). They had 275% higher risk of death (OR=2,758, p=0,0001). Multivariate logistic regression analysis after adjustment for possible confounders reviled that admission to hospital from Emergency Department (OR=2,652, p=0,01), higher PS scale note (OR=1,445, p=0,001), opioids administration (OR=2,747, p=0,003), dehydration (OR=1,966 , p=0,038) and higher risk of death (OR=2,432, p=0,002) remained independently associated with dyselectrolytemia. Conclusions: Higher PS scale note, occurrence of dehydration, admission to hospital from Emergency Department and opioids administration are factors associated with dyselectrolytemia. Patients with electrolytes imbalances had 275% higher risk of death. Project "Extension of life and improvement of its quality and reduction of cancer patients' mortality due to proper control of water and electrolyte management and elimination of risk factors for dehydration and dyselectrolytemia." Co-financed by the European Social Fund under the project of the Ministry of Science and Higher Education of Poland entitled "Best of the best! 2.0 ".

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Serum Interleukin-33 is a Predictor of Depression in Patients with Acute Ischemic Stroke

Current Neurovascular Research ◽

10.2174/1567202617999210101223635 ◽

2021 ◽

Vol 17 ◽

Author(s):

Zhenlei Chen ◽

Rongrong Zhang ◽

Yanping Wu ◽

Qing Fu ◽

Xinyue Qin

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Ischemic Stroke ◽

Roc Curve ◽

Independent Predictor ◽

Multivariate Logistic Regression Analysis ◽

Multivariate Logistic Regression ◽

Prognosis Factor ◽

Interleukin 33

Objective: The study aimed to investigate the relationship between serum interleukin-33 (IL-33) concentrations and poststroke depression (PSD) in patients with acute ischemic stroke (AIS). Methods: Serum IL-33 concentrations were determined using an enzyme-linked immunosorbent assay. Patients were assigned to the PSD group after a six-month follow-up if their score on the 17- item Hamilton Rating Scale for Depression was ≥7 or to the non-PSD group if their score was <7. IL-33 was used to predict the risk of PSD using multivariate logistic regression analysis, while a receiver operating characteristic (ROC) curve was used to analyze the accuracy of PSD prediction. In addition, the modified Rankin scale (mRS) was used for follow-up scoring six months after disease onset. Results: A total of 151 AIS patients and 40 healthy controls were included in this study. ROC curve results showed that the area under the curve was 0.684 (95% confidence interval: 0.594-0.774,Ρ=0.001) for IL-33 as a predictor of PSD. When the IL-33 concentration was ≤71.85 ng/L, prediction sensitivity and specificity were 77.5% and 57.3%, respectively. Multivariate logistic regression analysis showed that IL-33 concentration of ≤71.85 ng/L was an independent predictor of PSD (95% CI: 1.129-7.515, P=0.027). The follow-up mRS data showed that serum IL-33 is a protective prognosis factor in patients with AIS (95% CI: 0.954-0.997, P=0.024). Conclusions: Serum IL-33 is an independent predictor of PSD and a protective prognosis factor in patients with AIS.

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