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Background: The aim of this study was to identify the risk factors associated with prolonged length of stay (LOS) in patients undergoing primary total hip arthroplasty (THA) managed with an enhanced recovery after surgery (ERAS) program and develop a prediction model for improving the perioperative management of THA. Methods: In this single-center retrospective study, patients who underwent primary THA in accordance with ERAS from May 2018 to December 2019 were enrolled in this study. The primary outcome was prolonged LOS (> 48 h) beyond the first postoperative day. We collected the clinical patient's clinical characteristics, surgery-related parameters, and laboratory tests. A logistic regression analysis explored the independent risk factors for prolonged LOS. According to published literature and clinical experience, a series of variables were selected to develop a nomogram prediction model to predict the risk of prolonged LOS following primary THA with an ERAS program. Evaluation indicators of the prediction model, including the concordance index (C-index), the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis, were reported to assess the performance of the prediction model. The bootstrap method was conducted to validate the performance of the designed nomogram. Results: A total of 392 patients were included in the study, of whom 189 (48.21%) had prolonged LOS. The logistics regression analysis demonstrated that age, sex, hip deformities, intraoperative blood loss, operation time, postoperative Day 1 (POD) hemoglobin (Hb), POD albumin (ALB), and POD interleukin-6 (IL-6) were independent risk factors for prolonged LOS. The C-index was 0.863 (95% CI 0.808 to 0.918) and 0.845 in the bootstrapping validation, respectively. According to the results of the calibration, ROC curve, and decision curve analyses, we found that the nomogram showed satisfactory performance for prolonged LOS in this study. Conclusions: We explored the risk factors for prolonged LOS following primary THA with an ERAS program and developed a prediction model. The designed nomogram was expected to be a precise and personalized tool for predicting the risk and prognosis for prolonged LOS following primary THA with an ERAS program. [ABSTRACT FROM AUTHOR]

Background: This study aimed to develop and validate an individualized nomogram to predict the risk of positive hidden blood loss (HBL) in patients with single-level thoracolumbar burst fracture (TBF) during the perioperative period. Methods: We conducted a retrospective investigation including 150 consecutive patients with TBL, and the corresponding patient data was extracted from March 2013 to March 2019. The independent risk factors for positive HBL were screened using univariate and multivariate logistic regression analyses. According to published literature and clinical experience, a series of variables were selected to develop a nomogram prediction model for positive HBL. The area under the receiver operating characteristic curves (AUC), C-index, calibration plot, and decision curve analysis (DCA) were used to evaluate the performance of the prediction model. Bootstrapping validation was performed to evaluate the performance of the model. Results: Among the 150 consecutive patients, 62 patients were positive for HBL (38.0%). The multivariate logistic regression analysis showed that the six risk factors of age, length of surgical incision, duration of operation, percentage of vertebral height restoration (P1%), preoperative total cholesterol, and preoperative fibrinogen were independent risk factors of positive HBL. The C-index was 0.831 (95% CI 0.740–0.889) and 0.845 in bootstrapping validation, respectively. The calibration curve showed that the predicted probability of the model was consistent with the actual probability. Decision curve analysis (DCA) showed that the nomogram had clinical utility. Conclusion: Overall, we explored the relationship between the positive HBL requirement and predictors. The individualized prediction model for patients with single-level TBF can accurately assess the risk of positive HBL and facilitate clinical decision making. However, external validation will be needed in the future. [ABSTRACT FROM AUTHOR]

Background: This study aimed to develop and validate a nomogram for predicting acute kidney injury (AKI) during the Intensive Care Unit (ICU) stay of patients with diabetic ketoacidosis (DKA). Methods: A total of 760 patients diagnosed with DKA from the Medical Information Mart for Intensive Care III (MIMIC-III) database were included and randomly divided into a training set (70%, n = 532) and a validation set (30%, n = 228). Clinical characteristics of the data set were utilized to establish a nomogram for the prediction of AKI during ICU stay. The least absolute shrinkage and selection operator (LASSO) regression was utilized to identified candidate predictors. Meanwhile, a multivariate logistic regression analysis was performed based on variables derived from LASSO regression, in which variables with P < 0.1 were included in the final model. Then, a nomogram was constructed applying these significant risk predictors based on a multivariate logistic regression model. The discriminatory ability of the model was determined by illustrating a receiver operating curve (ROC) and calculating the area under the curve (AUC). Moreover, the calibration plot and Hosmer-Lemeshow goodness-of-fit test (HL test) were conducted to evaluate the performance of our newly bullied nomogram. Decision curve analysis (DCA) was performed to evaluate the clinical net benefit. Results: A multivariable model that included type 2 diabetes mellitus (T2DM), microangiopathy, history of congestive heart failure (CHF), history of hypertension, diastolic blood pressure (DBP), urine output, Glasgow coma scale (GCS), and respiratory rate (RR) was represented as the nomogram. The predictive model demonstrated satisfied discrimination with an AUC of 0.747 (95% CI, 0.706–0.789) in the training dataset, and 0.712 (95% CI, 0.642–0.782) in the validation set. The nomogram showed well-calibrated according to the calibration plot and HL test (P > 0.05). DCA showed that our model was clinically useful. Conclusion: The nomogram predicted model for predicting AKI in patients with DKA was constructed. This predicted model can help clinical physicians to identify the patients with high risk earlier and prevent the occurrence of AKI and intervene timely to improve prognosis. [ABSTRACT FROM AUTHOR]

Acoustic cardiography is a completely new technology, it has great advantages in the rapid diagnosis of cardiovascular diseases. The purpose of this study was to investigate the clinical value of the fourth heart sound (S4), cardiac systolic dysfunction index (SDI), and the cardiac cycle time-corrected electromechanical activation time (EMATc) in the prediction of post-percutaneous coronary intervention (PCI) early ventricular remodeling (EVR) in patients with acute myocardial infarction (AMI). We recruited 161 patients with AMI of 72-h post-PCI, including 44 EVR patients with left ventricular ejection fraction (LVEF) < 50% and 117 Non-EVR patients (normal left ventricular systolic function group, LVEF ≥ 50%). EMATc, S4, and SDI were independent risk factors for post-PCI early ventricular remodeling in patients with AMI [S4 (OR 2.860, 95% CI 1.297–6.306, p = 0.009), SDI (OR 4.068, 95% CI 1.800–9.194, p = 0.001), and EMATc (OR 1.928, 95% CI 1.420–2.619, p < 0.001)]. The area under the receiver operating characteristic curve for EMATc was 0.89, with an optimal cutoff point of 12.2, EMATc had a sensitivity of 80% and a specificity of 83%. By contrast, an optimal cutoff point of 100 pg/ml, Serum brain natriuretic peptide had a sensitivity of 46% and a specificity of 83%. Our findings suggest the predictive value of EMATc for the occurrence of EVR in these patients was also identified; EMATc may be a simple, quick, and effective way to diagnose EVR after AMI. [ABSTRACT FROM AUTHOR]

Background: This study aimed to predict C5 palsy (C5P) after posterior laminectomy and fusion (PLF) with cervical myelopathy (CM) from routinely available variables using a support vector machine (SVM) method. Methods: We conducted a retrospective investigation based on 184 consecutive patients with CM after PLF, and data were collected from March 2013 to December 2019. Clinical and imaging variables were obtained and imported into univariable and multivariable logistic regression analyses to identify risk factors for C5P. According to published reports and clinical experience, a series of variables was selected to develop an SVM machine learning model to predict C5P. The accuracy (ACC), area under the receiver operating characteristic curve (AUC), and confusion matrices were used to evaluate the performance of the prediction model. Results: Among the 184 consecutive patients, C5P occurred in 26 patients (14.13%). Multivariate analyses demonstrated the following 4 independent factors associated with C5P: abnormal electromyogram (odds ratio [OR] = 7.861), JOA recovery rate (OR = 1.412), modified Pavlov ratio (OR = 0.009), and presence of C4–C5 foraminal stenosis (OR = 15.492). The SVM model achieved an area under the receiver operating characteristic curve (AUC) of 0.923 and an ACC of 0.918. Additionally, the confusion matrix showed the classification results of the discriminant analysis. Conclusions: The designed SVM model presented satisfactory performance in predicting C5P from routinely available variables. However, future external validation is needed. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the methylation status of E2BSs in the HPV 16 long control region (LCR) in clinical cervical samples. Methylation status of the four E2BSs in 43 clinical cervical samples with HPV 16 infection was quantitatively detected using pyrosequencing. Meanwhile, Quantivirus® HPV E6/E7 RNA 3.0 assay (bDNA) was used to detect E6/E7 mRNA levels in the corresponding specimens. Our results showed that methylation status of E2BS1, 2 and 4 sites in high-grade squamous intraepithelial lesions (HSIL) and cervical cancer were significantly higher than that of asymptomatic HPV 16 infection and low-grade squamous intraepithelial lesions (LSIL) (all P <.05). Furthermore, methylation status of HPV 16 E2BS1 and 2 was positively correlated with E6/E7 mRNA levels (r s = 0.529 and 0.512 respectively, P <.01). Receiver operating characteristic curve analysis was used to compare the diagnostic performance of E2BSs methylation. When the Youden index was the maximum value, the methylation level of E2BS1 and E2BS2 all demonstrated optimum diagnostic sensitivity of 77.8%, and specificity of 80% and 92%, respectively. The methylation status of E2BS1 and 2 may have utility as diagnostic markers for the severity of cervical lesions in the future. • This study presents new data on the methylation status at four E2BSs of HPV-16 LCR. • The methylation status of E2BSs may affect transcriptional regulation of E2 on E6/E7. • HPV DNA methylation and the severity of cervical lesions appear to be correlated. • Methylation status of E2BSs may be used as diagnostic biomarker for cervical cancer. [ABSTRACT FROM AUTHOR]

Objective: To compare E6/E7 mRNA and HPV DNA assays for evaluating women with atypical cells of undetermined significance (ASCUS).Methods: The present prospective study enrolled patients with ASCUS undergoing HPV testing at Third Affiliated Hospital of Zhengzhou University, China, between September 1, 2013, and January 31, 2016. Patients with positive HPV DNA test results underwent screening by E6/E7 mRNA assay, and the accuracy of HPV DNA and E6/E7 mRNA testing were compared, with histology used for definitive diagnoses.Results: In total, 591 patients with ASCUS underwent HPV DNA screening, with 455 and 136 having positive and negative results, respectively; 252 patients with positive results and 66 with negative results underwent biopsy and histology testing and were included in the study. The sensitivity of the E6/E7 mRNA assay was similar to that of HPV DNA testing (88.2%, 95% confidence interval [CI] 77.6-94.4 vs 90.7%, 95%CI 81.2-95.9; P=0.636) for the detection of cervical intraepithelial neoplasia grade 2+, and the specificity was higher (36.4%, 95%CI 29.6-43.9 vs 24.3%, 95%CI 19.1-30.3; P=0.006). The area under the receiver operating characteristic curve was greater for E6/E7 mRNA testing compared with HPV DNA testing (0.658 vs 0.588).Conclusion: The higher specificity of the E6/E7 mRNA assay means it could be a promising technique in the management of women with ASCUS. [ABSTRACT FROM AUTHOR]