scholarly journals Nomogram for Perinatal Prediction of Intrapartum Fever: A Case-control Study

2021 ◽  
Author(s):  
Zhenfei Jiang ◽  
Xiaoyi Hu ◽  
Huabei Zeng ◽  
Xinghe Wang ◽  
Cheng Tan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Vaginal Delivery ◽  
Validation Cohort ◽  
Multivariate Logistic Regression Analysis ◽  
Labor Analgesia ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Clinical Trial Registration ◽  
Training Cohort

Abstract Objective: To explore the risk factors of intrapartum fever and develop a nomogram to predict the incidence of intrapartum fever.Methods: The general demographic characteristics and perinatal factors of 696 parturient who underwent vaginal delivery in the Affiliated Hospital of Xuzhou Medical University from May 2019 to April 2020 were retrospectively analyzed. 487 patients collected from May 2019 to October 2019 were formed into a training cohort. A multivariate logistic regression model was used to identify the independent risk factors associated with intrapartum fever during vaginal delivery, then a nomogram was developed to predict the occurrence. 209 cases collected from January 2020 to April 2020 were formed into a validation cohort to verify the nomogram.Results: Intrapartum fever was found in 72 of 487 parturient (14.78%) in the training cohort, and the incidence of intrapartum fever in the validation cohort was 14.83% (31/209). Multivariate logistic regression analysis showed that primiparas (Odds Ratio [OR]2.433; 95% confidence interval [CI]1.149-5.150), epidural labor analgesia (OR2.890; 95%CI 1.225-6.818), premature rupture of membranes (OR2.366; 95%CI 1.130-4.954), second stage of labor ≥120min (OR4.363; 95%CI 1.419-13.410), amniotic fluid pollution Ⅲ degree (OR10.391; 95%CI 3.299-32.729), fetal weight ≥4000g (OR7.492; 95%CI 2.115-26.542) were significantly related to intrapartum fever. According to clinical experience and previous studies, the duration of epidural labor analgesia also seemed to be a meaningful factor for intrapartum fever, so these 7 variables were incorporated to develop a nomogram, which achieved good area under ROC curve of 0.855 in the training cohort and 0.808 in the validation cohort, and it had a well-fitted calibration curve, which showed an excellent diagnostic performance.Conclusion: We constructed a model to predict the occurrence of fever during childbirth and developed an accessible nomogram. The nomogram can help doctors assess the risk of fever during childbirth, so as to lead to reasonable treatment measures.Clinical Trial Registration: (www.chictr.org.cn ChiCTR2000035593)

scholarly journals Risk factors for peritoneal dialysis–associated peritonitis

2018 ◽  
Vol 16 ◽  
pp. 205873921877224
Author(s):  
Hongyue Wang ◽  
Xiangtuo Wang ◽  
Haichuan Dou ◽  
Chenhao Li ◽  
Mingji Cui ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Peritoneal Dialysis ◽  
Serum Albumin ◽  
Multivariate Logistic Regression Analysis ◽  
Roc Curves ◽  
Multivariate Logistic Regression Model ◽  
Phosphorus Concentration ◽  
Multivariate Logistic Regression ◽  
Gram Positive

The purpose of this study was to summarize the pathogens that cause peritoneal dialysis (PD)-associated peritonitis and to identify risk factors for PD-associated peritonitis. This retrospective study included 115 end-stage renal disease (ESRD) patients receiving PD therapy. Patients were categorized into two groups: peritonitis group (n = 41) and non-peritonitis group (n = 74). Clinical data and laboratory tests were collected from medical records. The multivariate logistic regression model was used to evaluate associations between PD-associated peritonitis and potential risk factors. PD-associated peritonitis occurred 54 times in 41 patients. The most frequently identified pathogen was Gram-positive cocci (57.78%). Multivariate logistic regression analysis showed that serum albumin (β = –0.208, P < 0.001), blood phosphorus concentration (β = –1.732, P = 0.001), gastrointestinal disorders (β = 1.624, P = 0.043), and use of calcitriol (β = –2.239, P = 0.048) were significantly correlated with PD-associated peritonitis. Receiver operating characteristic (ROC) curves showed that the areas under the curve were 0.832 for serum albumin and 0.700 for blood phosphorus concentration with optimal cut-off values of 29.1 g/L for serum albumin and 1.795 mmol/L for blood phosphorus concentration. Gram-positive coccus is the major pathogen responsible for PD-associated peritonitis. Serum albumin <29.1 g/L, blood phosphorus concentration <1.795 mmol/L, and intestinal disorders are risk factors for PD-associated peritonitis, whereas the use of calcitriol can reduce the risk of PD-associated peritonitis.

scholarly journals Prevalence and risk factors of depression and anxiety for inpatients with lung cancer in China: A hospital-based cross-sectional study

2022 ◽  
Author(s):  
Xueqian Wang ◽  
Xuejiao Ma ◽  
Mo Yang ◽  
Yan Wang ◽  
Yi Xie ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lung Cancer ◽  
Logistic Regression ◽  
Risk Factor ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression Model ◽  
Depression And Anxiety ◽  
Multivariate Logistic Regression ◽  
Cross Sectional

Abstract Background Lung cancer was often accompanied by depression and anxiety. Nowadays, most investigations for depression and anxiety were concentrated in western medical hospitals, while few related studies have been carried out in the tradition Chinese medicine (TCM) ward. It was necessary to understand the prevalence and risk factors of depression and anxiety in the inpatients with lung cancer in TCM hospital. Methods This study adopted cross-sectional research method, which enrolled a total of 222 inpatients with lung cancer in TCM hospital. PHQ-9 and GAD-7 scales were used to assess depression and anxiety for the inpatients, respectively. Demographic and clinical data were also collected. Statistical methods of the univariate analysis and the multivariate logistic regression model were used. Results The prevalence of depression and anxiety in the inpatients with lung cancer were 58.1% and 34.2%, respectively. Multivariate logistic regression analysis prompted that the common risk factor of depression and anxiety was the symptom of insomnia. Constipation and gender were the two anther risk factors of depression. Conclusion Depression and anxiety were common for the inpatients with lung cancer in TCM hospital. Gender, insomnia and constipation were risk factors for depression, and insomnia was risk factor for anxiety. Therefore, medical workers should pay close attention to the emotional changes of these high-risk patients and intervene the symptoms as early as possible.

scholarly journals The severity and risk factors for mortality in immunocompromised adult patients hospitalized with influenza-related pneumonia

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Liang Chen ◽  
Xiudi Han ◽  
YanLi Li ◽  
Chunxiao Zhang ◽  
Xiqian Xing
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Multivariate Logistic Regression Analysis ◽  
Neuraminidase Inhibitor ◽  
Teaching Hospitals ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Optimal Cutoff

Abstract Objective To explore disease severity and risk factors for 30-day mortality of adult immunocompromised (IC) patients hospitalized with influenza-related pneumonia (Flu-p). Method A total of 122 IC and 1191 immunocompetent patients hospitalized with Flu-p from January 2012 to December 2018 were recruited retrospectively from five teaching hospitals in China. Results After controlling for confounders, multivariate logistic regression analysis showed that immunosuppression was associated with increased risks for invasive ventilation [odds ratio: (OR) 2.475, 95% confidence interval (CI): 1.511–4.053, p < 0.001], admittance to the intensive care unit (OR: 3.247, 95% CI 2.064–5.106, p < 0.001), and 30-day mortality (OR: 3.206, 95% CI 1.926–5.335, p < 0.001) in patients with Flu-p. Another multivariate logistic regression model revealed that baseline lymphocyte counts (OR: 0.993, 95% CI 0.990–0.996, p < 0.001), coinfection (OR: 5.450, 95% CI 1.638–18.167, p = 0.006), early neuraminidase inhibitor therapy (OR 0.401, 95% CI 0.127–0.878, p = 0.001), and systemic corticosteroid use at admission (OR: 6.414, 95% CI 1.348–30.512, p = 0.020) were independently related to 30-day mortality in IC patients with Flu-p. Based on analysis of the receiver operating characteristic curve (ROC), the optimal cutoff for lymphocyte counts was 0.6 × 109/L [area under the ROC (AUROC) = 0.824, 95% CI 0.744—0.887], sensitivity: 97.8%, specificity: 73.7%]. Conclusions IC conditions are associated with more severe outcomes in patients with Flu-p. The predictors for mortality that we identified may be valuable for the management of Flu-p among IC patients.

scholarly journals The severity and risk factors for mortality in immunocompromised adult patients hospitalized with influenza-related pneumonia

2021 ◽  
Author(s):  
Liang Chen ◽  
Xiudi Han ◽  
YanLi Li ◽  
Chunxiao Zhang ◽  
Xiqian Xing
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Multivariate Logistic Regression Analysis ◽  
Neuraminidase Inhibitor ◽  
Teaching Hospitals ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression

Abstract Objective To explore disease severity and risk factors for 30-day mortality of adult immunocompromised (IC) patients hospitalized with influenza-related pneumonia (Flu-p).Method A total of 122 IC and 1,191 immunocompetent patients hospitalized with Flu-p from January 2012 to December 2018 were recruited retrospectively from five teaching hospitals in China. Results After controlling for confounders, multivariate logistic regression analysis showed that immunosuppression was associated with increased risks for invasive ventilation [odds ratio: (OR) 2.475, 95% confidence interval (CI): 1.511-4.053, p < 0.001], admittance to the intensive care unit (OR: 3.247, 95% CI: 2.064-5.106, p < 0.001), and 30-day mortality (OR: 3.206, 95% CI: 1.926-5.335, p < 0.001) in patients with Flu-p. Another multivariate logistic regression model revealed that baseline lymphocyte counts (OR: 0.993, 95% CI: 0.990-0.996, p < 0.001), coinfection (OR: 5.450, 95% C:I 1.638-18.167, p = 0.006), early neuraminidase inhibitor therapy (OR 0.401, 95% CI 0.127-0.878, p = 0.001), and systemic corticosteroid use at admission (OR: 6.414, 95% C:I 1.348-30.512, p = 0.020) were independently related to 30-day mortality in IC patients with Flu-p. Based on receiver operating characteristic curve (ROC) analysis, the optimal cutoff for lymphocyte counts was 0.6×109/L [area under the ROC (AUROC) = 0.824, 95% CI: 0.744 - 0.887], sensitivity: 97.8%, specificity: 73.7%].Conclusions IC conditions are associated with more severe outcomes in patients with Flu-p. The predictors for mortality that we identified may be valuable for the management of Flu-p among IC patients.

scholarly journals Nomogram for perinatal prediction of intrapartum fever: a retrospective case–control study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhenfei Jiang ◽  
Xiaoyi Hu ◽  
Huabei Zeng ◽  
Xinghe Wang ◽  
Cheng Tan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Pregnant Women ◽  
Validation Cohort ◽  
Vaginal Birth ◽  
Labour Analgesia ◽  
Trial Registration ◽  
Multivariate Logistic Regression ◽  
Training Cohort ◽  
Link Type

Abstract Objective To explore the risk factors for intrapartum fever and to develop a nomogram to predict the incidence of intrapartum fever. Methods The general demographic characteristics and perinatal factors of 696 parturients who underwent vaginal birth at the Affiliated Hospital of Xuzhou Medical University from May 2019 to April 2020 were retrospectively analysed. Data was collected from May 2019 to October 2019 on 487 pregnant women who formed a training cohort. A multivariate logistic regression model was used to identify the independent risk factors associated with intrapartum fever during vaginal birth, and a nomogram was developed to predict the occurrence. To verify the nomogram, data was collected from January 2020 to April in 2020 from 209 pregnant women who formed a validation cohort. Results The incidence of intrapartum fever in the training cohort was found in 72 of the 487 parturients (14.8%), and the incidence of intrapartum fever in the validation cohort was 31 of the 209 parturients (14.8%). Multivariate logistic regression analysis showed that the following factors were significantly related to intrapartum fever: primiparas (odds ratio [OR] 2.43; 95% confidence interval [CI] 1.15–5.15), epidural labour analgesia (OR 2.89; 95% CI 1.23–6.82), premature rupture of membranes (OR 2.37; 95% CI 1.13–4.95), second stage of labour ≥ 120 min (OR 4.36; 95% CI 1.42–13.41), amniotic fluid pollution degree III (OR 10.39; 95% CI 3.30–32.73), and foetal weight ≥ 4000 g (OR 7.49; 95% CI 2.12–26.54). Based on clinical experience and previous studies, the duration of epidural labour analgesia also appeared to be a meaningful factor for intrapartum fever; therefore, these seven variables were used to develop a nomogram to predict intrapartum fever in parturients. The nomogram achieved a good area under the ROC curve of 0.86 and 0.81 in the training and in the validation cohorts, respectively. Additionally, the nomogram had a well-fitted calibration curve, which also showed excellent diagnostic performance. Conclusion We constructed a model to predict the occurrence of fever during childbirth and developed an accessible nomogram to help doctors assess the risk of fever during childbirth. Such assessment may be helpful in implementing reasonable treatment measures. Trial registration Clinical Trial Registration: (www.chictr.org.cnChiCTR2000035593)

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 A novel procalcitonin-based score for detecting sepsis among critically ill patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245748
Author(s):  
Tung-Lin Tsui ◽  
Ya-Ting Huang ◽  
Wei-Chih Kan ◽  
Mao-Sheng Huang ◽  
Min-Yu Lai ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Validation Cohort ◽  
Multivariate Logistic Regression Analysis ◽  
Sepsis Group ◽  
C Reactive Protein ◽  
Multivariate Logistic Regression ◽  
Reactive Protein

Background Procalcitonin (PCT) has been widely investigated as an infection biomarker. The study aimed to prove that serum PCT, combining with other relevant variables, has an even better sepsis-detecting ability in critically ill patients. Methods We conducted a retrospective cohort study in a regional teaching hospital enrolling eligible patients admitted to intensive care units (ICU) between July 1, 2016, and December 31, 2016, and followed them until March 31, 2017. The primary outcome measurement was the occurrence of sepsis. We used multivariate logistic regression analysis to determine the independent factors for sepsis and constructed a novel PCT-based score containing these factors. The area under the receiver operating characteristics curve (AUROC) was applied to evaluate sepsis-detecting abilities. Finally, we validated the score using a validation cohort. Results A total of 258 critically ill patients (70.9±16.3 years; 55.4% man) were enrolled in the derivation cohort and further subgrouped into the sepsis group (n = 115) and the non-sepsis group (n = 143). By using the multivariate logistic regression analysis, we disclosed five independent factors for detecting sepsis, namely, “serum PCT level,” “albumin level” and “neutrophil-lymphocyte ratio” at ICU admission, along with “diabetes mellitus,” and “with vasopressor.” We subsequently constructed a PCT-based score containing the five weighted factors. The PCT-based score performed well in detecting sepsis with the cut-points of 8 points (AUROC 0.80; 95% confidence interval (CI) 0.74–0.85; sensitivity 0.70; specificity 0.76), which was better than PCT alone, C-reactive protein and infection probability score. The findings were confirmed using an independent validation cohort (n = 72, 69.2±16.7 years, 62.5% men) (cut-point: 8 points; AUROC, 0.79; 95% CI 0.69–0.90; sensitivity 0.64; specificity 0.87). Conclusions We proposed a novel PCT-based score that performs better in detecting sepsis than serum PCT levels alone, C-reactive protein, and infection probability score.

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 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.

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