Validation of the Modified Alvarado Score in Patients Attending A&E Unit With Suspected Appendicitis – Prospective Clinical Study

BackgroundThe aim of our prospective study was to confirm the validity, diagnostic accuracy of the modified Alvarado score developed in the Department of Surgery, University of Szeged.Methods138 patients were enrolled in our study between 01 January 2019 and 01 January 2020. The patient’s modified Alvarado score was calculated in the Emergency Department before surgical consultation and decision of further therapy. The score was validated based on the final histology finding of the removed appendix. Additionally, potential correlation was examined between the frequency of drain usage, hospital stay, antibiotic use and the severity of the inflammation. ResultsComparing the scores with the histological findings, specificity of the modified Alvarado score was 84.78%, its sensitivity was 97.83% (with cutoff value of 5.5). Spearman's rank correlation (0.796) and ROC analysis (area under the curve 0.968) confirmed that the modified Alvarado score has an excellent predictive value in the diagnosis of acute appendicitis. Based on the result of the Fisher's exact test, cross tabulation and Spearman’s rank correlation correlation was found between the severity of the inflammation determined by the histology finding, the selected antibiotic and the duration of the antibiotic therapy, the average duration of hospitalization and drain insertion. ConclusionsBased on the results of our study, predictive value of the new, modified score system is excellent, using this score system is safe in the differential diagnosis of acute appendicitis as an aid for non-surgical consultants in emergency care. This new score system may decrease the number of unnecessary surgical consultations, decrease waiting time of the patients and some unnecessary examinations can be avoided. Trial RegistrationValidation of the modified Alvarado score in patients presenting in the Emergency Department with right lower abdominal complaints, ethical license number: 248/2018/SZTE, date of registration: 2018.11.04., name of ethics committee: SZTE SZAKK Regionális és Intézményi Humán Orvosbiológiai Kutatásetikai Bizottság- Clinical Research Coordination Office of the University of Szeged

Risk prediction in patients with low-flow, low-gradient aortic stenosis and reduced ejection fraction undergoing TAVI

ObjectivePatients with low-flow, low-gradient aortic stenosis (LFLG AS) and reduced left ventricular ejection fraction (LVEF) are known to suffer from poor prognosis after transcatheter aortic valve implantation (TAVI). This study aimed to develop a simple score system for risk prediction in this vulnerable subset of patients.MethodsAll patients with LFLG AS with reduced EF and sufficient CT data for aortic valve calcification (AVC) quantification, who underwent TAVI at five German centres, were retrospectively included. The Risk prEdiction in patients with Low Ejection Fraction low gradient aortic stenosis undergoing TAVI (RELiEF TAVI) score was developed based on multivariable Cox regression for all-cause mortality.ResultsAmong all included patients (n=718), RELiEF TAVI score variables were defined as independent predictors of mortality: male sex (HR 1.34 (1.06, 1.68), p=0.013), underweight (HR 3.10 (1.50, 6.40), p=0.0022), chronic obstructive pulmonary disease (HR 1.55 (1.21, 1.99), p=0.001), pulmonary hypertension (HR 1.51 (1.17, 1.94), p=0.0015), atrial fibrillation (HR 1.28 (1.03, 1.60), p=0.028), stroke volume index (HR 0.96 (0.95, 0.98), p<0.001), non-transfemoral access (HR 1.36 (1.05, 1.76), p=0.021) and low AVC density (HR 1.44 (1.15, 1.79), p=0.0012). A score system was developed ranging from 0 to 12 points (risk of 1-year mortality: 13%–99%). Kaplan-Meier analysis for low (0–1 points), moderate (2–4 points) and high RELiEF TAVI score (>4 points) demonstrated rates of 18.0%, 29.0% and 46.1% (p<0.001) for all-cause mortality and 23.8%, 35.9% and 53.4% (p<0.001) for the combined endpoint of all-cause mortality or heart failure rehospitalisation after 1 year, respectively.ConclusionsThe RELiEF TAVI score is based on simple clinical, echocardiographic and CT parameters and might serve as a helpful tool for risk prediction in patients with LFLG AS and reduced LVEF scheduled for TAVI.

Modified Coronally Positioned Flap for Isolated Gingival Recession, Evaluated with Root Coverage Esthetic Score System

Background: Various modifications of the coronally displaced flap have been proposed in the literature with the attempt of treating gingival recession. This study is undertaken to evaluate the predictability of the modified coronally positioned flap in isolated gingival recession not only in terms of root coverage but also with the esthetic outcome. Materials and Methods: Fifteen isolated gingival recessions with at least 1mm of keratinized tissue apical to the defect were treated with a modified coronally advanced flap. All recessions fall into Miller class I. The clinical re-evaluation was performed 3 months and 1year after the surgery. Statistical analysis was performed using statistical application software (SPSS16.0). Multivariate ANOVA was used for analysis. Results: At the 1-year examination, the average root coverage was 94.6% of the pre-operative recession depth. There was a mean clinical attachment gain of 3.3±0.1 mm at 1 year follow-up.The average increase of keratinized tissue between the baseline and the 1-year follow-up amounted to 1.53±0.13 mm. Root coverage esthetic score (RES) was recorded at the end of follow-up period. 13/15 cases showed RES score of 9 and 2/15 cases showed RES score of 6. Conclusion: The modified coronally advanced surgical technique is effective in the treatment of isolated gingival recession in the upper jaw.

Development And Validation of a Risk Scoring System to Predict Pneumothorax in CT-Guided Percutaneous Transthoracic Needle Biopsy

Objective: To develop and validate a risk scoring system using variables easily obtained for the prediction of pneumothorax in CT-guided percutaneous transthoracic needle biopsy (PTNB).Methods: The derivation cohort was comprised of 1001 patients who underwent CT-guided PTNB. Multivariate logistic regression was used to identify risk factors for pneumothorax, which were treated as the foundation to develop the risk scoring system. To validate the system, a validation cohort group of 230 patients was enrolled.Results: Age, puncture times, puncture depth, smoking index, number of specimens, bleeding from the needle path, and lobular lesion were identified as risk factors in the derivation cohort. A risk scoring system (Hosmer-Lemeshow goodness-of-fit test p =0.33) was developed. The area under the receiver operating characteristic curve (AUROC) was 0.601 by using the risk score system. This risk score system demonstrated a better diagnostic effect with increasing age. In the group of patients older than 80 years, the AUROC was 0.76, showing good predictive power. This risk scoring system was confirmed in the validation cohort with an AUROC of 0.736.Conclusion: This scoring system has a good predictive effect in both derivation and validation cohort.

A novel machine learning derived RNA-binding protein gene–based score system predicts prognosis of hepatocellular carcinoma patients

Background Although the expression of RNA-binding protein (RBP) genes in hepatocellular carcinoma (HCC) varies and is associated with tumor progression, there has been no overview study with multiple cohorts and large samples. The HCC-associated RBP genes need to be more accurately identified, and their clinical application value needs to be further explored. Methods First, we used the robust rank aggregation (RRA) algorithm to extract HCC-associated RBP genes from nine HCC microarray datasets and verified them in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and International Cancer Genome Consortium (ICGC) Japanese liver cancer (ICGC-LIRI-JP) cohort. In addition, the copy number variation (CNV), single-nucleotide variant (SNV), and promoter-region methylation data of HCC-associated RBP genes were analyzed. Using the random forest algorithm, we constructed an RBP gene–based prognostic score system (RBP-score). We then evaluated the ability of RBP-score to predict the prognosis of patients. The relationships between RBP-score and other clinical characteristics of patients were analyzed. Results The RRA algorithm identified 30 RBP mRNAs with consistent expression patterns across the nine HCC microarray datasets. These 30 RBP genes were defined as HCC-associated RBP genes. Their mRNA expression patterns were further verified in the TCGA-LIHC and ICGC-LIRI-JP cohorts. Among these 30 RBP genes, some showed significant copy number gain or loss, while others showed differences in the methylation levels of their promoter regions. Some RBP genes were risk factors or protective factors for the prognosis of patients. We extracted 10 key HCC-associated RBP genes using the random forest algorithm and constructed an RBP-score system. RBP-score effectively predicted the overall survival (OS) and disease-free survival (DFS) of HCC patients and was associated with the tumor, node, metastasis (TNM) stage, α-fetoprotein (AFP), and metastasis risk. The clinical value of RBP-score was validated in datasets from different platforms. Cox analysis suggested that a high RBP-score was an independent risk factor for poor prognosis in HCC patients. We also successfully established a combined RBP-score+TNM LASSO-Cox model that more accurately predicted the prognosis. Conclusion The RBP-score system constructed based on HCC-associated RBP genes is a simple and highly effective prognostic evaluation tool. It is suitable for different subgroups of HCC patients and has cross-platform characteristics. Combining RBP-score with the TNM staging system or other clinical parameters can lead to an even greater clinical benefit. In addition, the identified HCC-associated RBP genes may serve as novel targets for HCC treatment.