scholarly journals Development and External Validation of a Nomogram for Early Predicting in-hospital Mortality of Patients with SARS-CoV-2 Pneumonia: A Two-Center, Retrospective Analysis

2020 ◽  
Author(s):  
Miao Luo ◽  
Junlin Lu ◽  
Jing Liu ◽  
Shuli Xia ◽  
Shuang Wei
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Hospital Mortality ◽  
External Validation ◽  
Multivariate Logistic Regression Analysis ◽  
Curve Analysis ◽  
Multivariate Logistic Regression ◽  
Factors Associated ◽  
Death Cases

Abstract Background At present, the death cases with SARS-CoV-2 pneumonia are continuing to increase globally. However, the information on death cases and predictive methods are substantial lacking. We aimed to develop a nomogram, which was validated by both internal and external cohorts, for early predicting mortality in hospitalized patients with SARS-CoV-2 pneumonia.Methods We retrospectively collected data on 1,540 patients confirmed SARS-CoV-2 pneumonia from two hospitals. Multivariate logistic regression analysis was performed to examine factors associated with in-hospital mortality. We investigated the mortality related risk factors and their weights, thereafter designed and validated a predictive nomogram model to facilitate early discrimination of in-hospital death. We assessed the nomogram performance by examining calibration (calibration plots and Hosmer–Lemeshow calibration test) and discrimination (AUROC). We also plotted survival curves and decision curves to evaluate the clinical usefulness of the nomogram.Results In the 1,540 patients from two centers, 248 cases died (16.1%). In the predictive nomogram calculated by a multivariate logistic regression analysis, eight independent risk factors associated mortality included age ≥ 60 years (odd ratio(OR) = 2.840; 95%CI, 1.467–5.495; P = 0.002), respiratory rate ≥ 30 breaths per minute (OR = 3.308; 95%CI, 1.408–7.770; P = 0.006), neutrophil count ≥ 7 × 109/L (OR = 3.084; 95%CI, 1.667–5.707; P < 0.001), lymphocyte count ≤ 0.8 × 109/ L (OR = 4.688; 95%CI, 2.500-8.791; P < 0.001), d-dimer ≥ 1.5 µg/mL(OR = 2.159; 95%CI, 1.169–3.989; P = 0.014), lactate dehydrogenase ≥ 350U/L(OR = 4.385; 95%CI, 2.299–8.362; P < 0.001), procalcitonin ≥ 0.1 ng/mL(OR = 4.972; 95%CI, 2.537–9.746; P < 0.001), and presence of myocardial injury (OR = 2.289; 95%CI, 1.260–4.160; P = 0.007) on admission. Calibration curves showed good fitting of the nomogram model with no statistical significance (P = 0.740) by Hosmer-Lemeshow test. This predictive nomogram had better predictive ability than CURB-65 score in training set (AUROC = 0.956 vs 0.828,P < 0.001). The good predictive performance of the nomogram is suggested by calibration, discrimination, and survival curve analysis, whether in the training, internal or external validation set. The decision curve analysis showed that predicting mortality risk applying this nomogram would be better than having all patients or none patients.Conclusions This nomogram is a reliable prognostic method that can accurately and early predict in-hospital mortality in patients with SARS-CoV-2 pneumonia. It can guide clinicians to improve their abilities to evaluate patient prognosis, enhance patient stratification, make earlier and reasonable decisions.Trail registration: This is a retrospective observational study without a trial registration number.

scholarly journals Factors associated with depression in the patients with diabetes mellitus type 2

2019 ◽  
Vol 76 (11) ◽  
pp. 1178-1183 ◽  
Author(s):  
Admir Sabanovic ◽  
Natasa Maksimovic ◽  
Mirjana Stojanovic-Tasic ◽  
Marijan Bakic ◽  
Anita Grgurevic
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Diabetes Mellitus Type 2 ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Factors Associated

Background/Aim. The assessment of association of depression and diabetes mellitus type 2 using the Patient Health Questionaire (PHQ-9) has not been done in Montenegro. The aim of this study was to assess the prevalence of depression in the patients with type 2 diabetes mellitus, and to identify the risk factors associated with the presence of depression. Methods. A cross-sectional study was conducted at the General Hospital in Bijelo Polje, from July to September, 2015. It included 70 patients over 35 years of age with the diagnosis of diabetes for at least six months. For the assessment of depression presence and intensity PHQ?9 was used. All variables associated with the presence of depression at a significance level of p < 0.05 were included into the final method of the multivariate logistic regression analysis. Results. Comorbidities were statistically significant more frequent among patients with depression (?2 = 5.40; p = 0.020). Duration of diabetes over five years was significantly associated with depression (?2 = 12.48; p < 0.001). Depression occurred more frequently among physically inactive subjects (?2 = 10.74; p = 0.005). The presence of diabetic polyneuropathy (?2 = 6.04; p = 0.014) and cataract (?2 = 5.351; p = 0.021) were also significantly associated with depression. A multivariate logistic regression analysis showed that the duration of diabetes over five years and presence of cataract were independently associated with depression. Conclusion. The risk factors for depression among the subjects with diabetes were disease duration more than five years and the presence of cataract. Since depression is a serious disease and can be a risk factor for many chronic diseases, the best way of prevention is its early detection and treatment.

Diagnostic accuracy of time to first positivity of blood cultures for predicting severe clinical outcomes in children with pneumonia-related bacteremia

2020 ◽  
Vol 68 (7) ◽  
pp. 1241-1249
Author(s):  
Yin Zhang ◽  
Jilei Lin ◽  
Qingxia Shi ◽  
Chulin Li ◽  
Jingyue Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Hospital Mortality ◽  
Clinical Outcomes ◽  
Early Recognition ◽  
Multivariate Logistic Regression Analysis ◽  
Blood Cultures ◽  
Lasso Regression ◽  
Multivariate Logistic Regression

Early recognition of severe clinical outcomes in children with pneumonia-related bacteremia is vitally important because of the high mortality. This study aims to explore risk factors for severe clinical outcomes in children with pneumonia-related bacteremia and evaluate the value of time to first positive blood cultures (TTFP) in predicting prognosis. Children with pneumonia-related bacteremia in Children’s Hospital of Chongqing Medical University were included (January 2013–May 2019), respectively. TTFP and clinical parameters were collected and analyzed. The area under the curve (AUC)-receiver operating characteristic was used to evaluate the discrimination ability of TTFP. Multivariate logistic regression tests were performed to evaluate the association between TTFP and severe clinical outcomes. A total of 242 children with pneumonia-related bacteremia were included. The least absolute shrinkage and selection operator (LASSO) regression analysis identified TTFP, serum albumin (ALB) and lactic dehydrogenase (LDH) as predictors of in-hospital mortality. Multivariate logistic regression analysis showed that shorter TTFP (OR 0.94; 95% CI 0.89 to 0.97; p<0.01), lower ALB level (OR 0.93; 95% CI 0.89 to 0.98; p<0.01) and higher LDH level (OR 1.001; 95% CI 1.000 to 1.001; p<0.01) were risk factors for in-hospital mortality in children with pneumonia-related bacteremia. AUC of TTFP for predicting in-hospital mortality was 0.748 (95% CI 0.668 to 0.829). Shorter TTFP (≤16 hours) was associated with in-hospital mortality and septic shock. TTFP plays an important role in predicting severe clinical outcomes in children with pneumonia-related bacteremia.

scholarly journals Risk factors for tissue expander infection in scar reconstruction: a retrospective cohort study of 2374 consecutive cases

2020 ◽  
Vol 8 ◽  
Author(s):  
Chen Dong ◽  
Minhui Zhu ◽  
Luguang Huang ◽  
Wei Liu ◽  
Hengxin Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Treatment Failure ◽  
Logistic Regression Analysis ◽  
Disease Duration ◽  
Multivariate Logistic Regression Analysis ◽  
Tissue Expansion ◽  
Multivariate Logistic Regression ◽  
Hematoma Evacuation

Abstract Background Tissue expansion is used for scar reconstruction owing to its excellent clinical outcomes; however, the complications that emerge from tissue expansion hinder repair. Infection is considered a major complication of tissue expansion. This study aimed to analyze the perioperative risk factors for expander infection. Methods A large, retrospective, single-institution observational study was carried out over a 10-year period. The study enrolled consecutive patients who had undergone tissue expansion for scar reconstruction. Demographics, etiological data, expander-related characteristics and postoperative infection were assessed. Univariate and multivariate logistic regression analysis were performed to identify risk factors for expander infection. In addition, we conducted a sensitivity analysis for treatment failure caused by infection as an outcome. Results A total of 2374 expanders and 148 cases of expander infection were assessed. Treatment failure caused by infection occurred in 14 expanders. Multivariate logistic regression analysis identified that disease duration of ≤1 year (odds ratio (OR), 2.07; p &lt; 0.001), larger volume of expander (200–400 ml vs &lt;200 ml; OR, 1.74; p = 0.032; &gt;400 ml vs &lt;200 ml; OR, 1.76; p = 0.049), limb location (OR, 2.22; p = 0.023) and hematoma evacuation (OR, 2.17; p = 0.049) were associated with a high likelihood of expander infection. Disease duration of ≤1 year (OR, 3.88; p = 0.015) and hematoma evacuation (OR, 10.35; p = 0.001) were so related to high risk of treatment failure. Conclusions The rate of expander infection in patients undergoing scar reconstruction was 6.2%. Disease duration of &lt;1 year, expander volume of &gt;200 ml, limb location and postoperative hematoma evacuation were independent risk factors for expander infection.

scholarly journals Predictive risk factors for worse outcomes in COVID-19 patients with different clinical features at baseline

2021 ◽  
Author(s):  
Elisabetta Schiaroli ◽  
Anna Gidari ◽  
Giovanni Brachelente ◽  
Sabrina Bastianelli ◽  
Alfredo Villa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Critical Illness ◽  
Serum Ferritin ◽  
Logistic Regression Analysis ◽  
Severe Disease ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Neutrophil Lymphocyte Ratio

IntroductionCOVID-19 is characterized by a wide range of clinical expression and by possible progression to critical illness and death. Therefore it is essential to identify risk factors predicting progression towards serious and fatal diseases. The aim of our study was to identify laboratory predictive markers of clinical progression in patients with moderate/severe disease and in those with acute respiratory distress syndrome (ARDS).Material and methodsUsing electronic medical records for all demographic, clinical and laboratory data, a retrospective study on all consecutive patients with COVID-19 admitted to the Infectious Disease Clinic of Perugia was performed. The PaO2/FiO2 ratio (P/F) assessment cut‑off of 200 mm Hg was used at baseline to categorize the patients into two clinical groups. The progression towards invasive ventilation and/or death was used to identify critical outcome. Statistical analysis was performed. Multivariate logistic regression analysis was adopted to identify risk factors of critical illness and mortality.ResultsIn multivariate logistic regression analysis neutrophil/lymphocyte ratio (NLR) was the only significant predictive factor of progression to a critical outcome (p = 0.03) and of in-hospital mortality (p = 0.03). In ARDS patients no factors were associated with critical progression. Serum ferritin > 1006 ng/ml was the only predictive value of critical outcome in COVID-19 subjects with moderate/severe disease (p = 0.02).ConclusionsNeutrophil/lymphocyte ratio and serum ferritin are the only biomarkers that can help to stratify the risk of severity and mortality in patients with COVID-19.

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

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
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.

Risk factor analysis of progressive spinal deformity after resection of intramedullary spinal cord tumors in patients who underwent laminoplasty: a report of 105 consecutive cases

2019 ◽  
Vol 30 (5) ◽  
pp. 655-663 ◽  
Author(s):  
Wei Shi ◽  
Shan Wang ◽  
Huifang Zhang ◽  
Guoqin Wang ◽  
Yi Guo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Spinal Cord ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Spinal Deformity ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Spinal Cord Tumors ◽  
Intramedullary Spinal Cord

OBJECTIVELaminoplasty has been used in recent years as an alternative approach to laminectomy for preventing spinal deformity after resection of intramedullary spinal cord tumors (IMSCTs). However, controversies exist with regard to its real role in maintaining postoperative spinal alignment. The purpose of this study was to examine the incidence of progressive spinal deformity in patients who underwent laminoplasty for resection of IMSCT and identify risk factors for progressive spinal deformity.METHODSData from IMSCT patients who had undergone laminoplasty at Beijing Tsinghua Changgung Hospital between January 2014 and December 2016 were retrospectively reviewed. Univariate tests and multivariate logistic regression analysis were used to assess the statistical relationship between postoperative spinal deformity and radiographic, clinical, and surgical variables.RESULTSOne hundred five patients (mean age 37.0 ± 14.5 years) met the criteria for inclusion in the study. Gross-total resection (> 95%) was obtained in 79 cases (75.2%). Twenty-seven (25.7%) of the 105 patients were found to have spinal deformity preoperatively, and 10 (9.5%) new cases of postoperative progressive deformity were detected. The mean duration of follow-up was 27.6 months (SD 14.5 months, median 26.3 months, range 6.2–40.7 months). At last follow-up, the median functional scores of the patients who did develop progressive spinal deformity were worse than those of the patients who did not (modified McCormick Scale: 3 vs 2, and p = 0.04). In the univariate analysis, age (p = 0.01), preoperative spinal deformity (p < 0.01), extent of tumor involvement (p < 0.01), extent of abnormal tumor signal (p = 0.02), and extent of laminoplasty (p < 0.01) were identified as factors associated with postoperative progressive spinal deformity. However, in subsequent multivariate logistic regression analysis, only age ≤ 25 years and preoperative spinal deformity emerged as independent risk factors (p < 0.05), increasing the odds of postoperative progressive deformity by 4.1- and 12.4-fold, respectively (p < 0.05).CONCLUSIONSProgressive spinal deformity was identified in 25.7% patients who had undergone laminoplasty for IMSCT resection and was related to decreased functional status. Younger age (≤ 25 years) and preoperative spinal deformity increased the risk of postoperative progressive spinal deformity. The risk of postoperative deformity warrants serious reconsideration of providing concurrent fusion during IMSCT resection or close follow-up after laminoplasty.

scholarly journals Seroprevalence and Risk Factors ofChlamydia abortusInfection in Tibetan Sheep in Gansu Province, Northwest China

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Si-Yuan Qin ◽  
Ming-Yang Yin ◽  
Wei Cong ◽  
Dong-Hui Zhou ◽  
Xiao-Xuan Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Northwest China ◽  
Gansu Province ◽  
Factors Associated ◽  
Tibetan Sheep ◽  
Different Seasons

Chlamydia abortus, an important pathogen in a variety of animals, is associated with abortion in sheep. In the present study, 1732 blood samples, collected from Tibetan sheep between June 2013 and April 2014, were examined by the indirect hemagglutination (IHA) test, aiming to evaluate the seroprevalence and risk factors ofC. abortusinfection in Tibetan sheep. 323 of 1732 (18.65%) samples were seropositive forC. abortusantibodies at the cut-off of 1 : 16. A multivariate logistic regression analysis was used to evaluate the risk factors associated with seroprevalence, which could provide foundation to prevent and controlC. abortusinfection in Tibetan sheep. Gender of Tibetan sheep was left out of the final model because it is not significant in the logistic regression analysis (P>0.05). Region, season, and age were considered as major risk factors associated withC. abortusinfection in Tibetan sheep. Our study revealed a widespread and high prevalence ofC. abortusinfection in Tibetan sheep in Gansu province, northwest China, with higher exposure risk in different seasons and ages and distinct geographical distribution.

scholarly journals Ectopic eruption of the maxillary second molar: Predictive factors

2017 ◽  
Vol 87 (4) ◽  
pp. 583-589 ◽  
Author(s):  
Soonshin Hwang ◽  
Yoon Jeong Choi ◽  
Ji Yeon Lee ◽  
Chooryung Chung ◽  
Kyung-Ho Kim
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Multivariate Logistic Regression Analysis ◽  
Key Factors ◽  
Multivariate Logistic Regression ◽  
Factors Associated ◽  
Ectopic Eruption ◽  
Maxillary Tuberosity

ABSTRACT Objective: The purpose of this study was to investigate the diagnostic aspects, contributing conditions, and predictive key factors associated with ectopic eruption of maxillary second molars. Material and Methods: This retrospective study evaluated the study models, lateral cephalographs, and panoramic radiographs of 40 adult subjects (20 men, 20 women) with bilateral ectopic eruption and 40 subjects (20 men, 20 women) with normal eruption of the maxillary second molars. Studied variables were analyzed statistically by independent t-tests, univariate and multivariate logistic regression analysis, followed by receiver-operating characteristic analysis. Results: Tooth widths of bilateral lateral incisors, canines, and premolars were wider in the ectopic group, which resulted in greater arch lengths. The ANB angle and maxillary tuberosity distance (PTV-M1, PTV-M2) were smaller in the ectopic group. The long axes of the maxillary molars showed significant distal inclination in the ectopic group. The multivariate logistic regression analysis showed that three key factors—arch length, ANB angle, and PTV-M1 distance—were significantly associated with ectopic eruption of the second molars. The area under the curve (AUC) was the largest for the combination of the three key factors with an AUC greater than 0.75. PTV-M1 alone was the single factor that showed the strongest association with ectopic eruption (AUC = 0.7363). Conclusions: An increase in arch length, decrease in ANB angle, and decrease in maxillary tuberosity distance to the distal aspect of the maxillary first molar (PTV-M1) were the most predictive factors associated with ectopic eruption of maxillary second molars.

scholarly journals Decreased eGFR Is Associated With Ischemic Stroke in Patients With Dilated Cardiomyopathy

2019 ◽  
Vol 25 ◽  
pp. 107602961986690 ◽  
Author(s):  
Yuqing Deng ◽  
Zhiqing Chen ◽  
Lili Hu ◽  
Zhenyan Xu ◽  
Jinzhu Hu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Dilated Cardiomyopathy ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Analysis Model ◽  
Multivariate Logistic Regression ◽  
Increased Risk

Dilated cardiomyopathy (DCM) is increasingly indicated as a cause of cardioembolic syndrome, in particular, cardioembolic ischemia stroke. However, the potential risk factors for stroke among DCM patients remain under investigated. DCM patients hospitalized from June 2011 to June 2016 were included. The cases were defined as the group of DCM patients with stroke compared with those without stroke. Clinical characteristic data were collected and compared between the two groups including demographic data, complicated diseases, echocardiography index, and laboratory parameters and estimated glomerular filtration rate (eGFR). A multivariate logistic regression analysis model adjusted by sex and age was used to explore the related risk factors for stroke in DCM patients. A total of 779 hospitalized patients with DCM were included. Of these, 55 (7.1%) had experienced a stroke. Significantly lower eGFR levels (68.03 ± 26.22 vs 79.88 ± 24.25 mL/min/1.73 m2, P = .001) and larger left atrial diameters (45.32 ± 7.79 vs 43.25 ± 7.11 mm, P = .04) were found in the group of patients having DCM with stroke compared to those without stroke. When the eGFR was categorized as eGFR >60, 30<eGFR≤ 60 and eGFR ≤ 30, there were more patients with 30<eGFR≤ 60 (30.9% vs 17.7%) and eGFR≤ 30 (9.1% vs 3.3%) in the ischemic stroke group ( P = 0.003). A multivariate logistic regression analysis model adjusted by sex and age showed that 30 <eGFR≤60 (odds ratio [OR]: 2.07, 95% confidence interval [CI]: [1.05-4.07], P = .035) and eGFR≤30 (OR: 4.04, 95% CI: [1.41-11.62], P = .009) were statistically associated with ischemic stroke in patients with DCM. It is concluded that decreased eGFR is significantly associated with an increased risk of ischemic stroke in patients with DCM.

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