Score Matching Research Articles

A Construction Optimization for Laser SLAM Based on Odometer Constraint Fusion

The traditional laser SLAM (Simultaneous Localization and Mapping) algorithm uses the global relative poses and local ones to form residual blocks. Its constructed map is not smooth enough and the constraint construction is too simplex under some special scenarios. Thus, this paper proposes an odometer constraint fusion method called FOSLAM (Fusion Odometer SLAM) to construct residual blocks between constrains and solve the nonlinear least squares by Ceres. The effectiveness and accuracy of this method have been verified through comparative experiments. Experimental results showed that without increasing the time and space complexity, by involving the odometer constraint into the SLAM optimization process, the convergence of scan matching scores can be improved and the constructed grid map edges are smoother and the jagged phenomenon can be reduced. Under sophisticated scene, FOSLAM is able to acquire more accurate maps and laser odometer trajectory than Cartographer method. Therefore, it is suitable to be used on indoor robot for cleaning and inspection and can be further deployed on autonomous unmanned vehicles involving spatial visualization and neuro-heuristic guidance.

Enhancing Pencak Silat Education through Application-Based Learning Media: A Comparative Study on Teaching Effectiveness and Student Outcomes

This examination is advancement research that expects to configuration learning media that contains appraisals in hand to hand fighting contests, particularly combative techniques and particularly aiding the field of sports science, particularly in the field of refereeing and sports accomplishments in North Sumatra. An application that contains assessments in both legal and illegal pencak silat competitions is the form of the developed media. These assessments are presented in the form of videos and match scoring. Additionally, the application includes a useful assessment of fundamental martial arts and martial arts techniques for use in classes. This thought emerged when specialists wanted to expect to discover that was more viable and proficient, as well as valuable for selecting contender for combative techniques and hand to hand fighting officials. The distribution of training materials for martial arts referees can also benefit from this application, particularly in the field of refereeing. The information displayed in this study is a correlation of the viability of the learning model for every mark of the evaluation of the new learning model (in the wake of utilizing the application) more successful than the old learning model (prior to utilizing the application). The new learning model has an efficiency of 85.71 percent, while the old learning model has an efficiency of 60 percent. The old learning model's average effectiveness of implementation indicators was 50%, while the new model's average effectiveness was 70%. Therefore, it can be concluded that the new learning model is superior to the old learning model (previous to using a drill machine) after using a drill machine.

Two-Year Outcomes of Primary Prophylactic Use of Defibrillators for Ischemic and Non-Ischemic Cardiomyopathy - Propensity Score-Matched Analysis From the Nippon Storm Study.

In 2016, the DANISH study reported negative results regarding the efficacy of implantable cardioverter-defibrillators (ICDs) in patients with non-ischemic cardiomyopathy (NICM) and reduced left ventricular ejection fraction (LVEF). In this study we determined the efficacy of using ICDs for primary prophylaxis in patients with NICM.Methods and Results: We selected 1,274 patients with underlying cardiac disease who were enrolled in the Nippon Storm Study. We analyzed the data of 451 patients with LVEF ≤35% due to NICM or ischemic cardiomyopathy (ICM) who underwent ICD implantation for primary prophylaxis (men, 78%; age, 65±12 years; LVEF, 25±6.4%; cardiac resynchronization therapy, 73%; ICM, 33%). After propensity score matching, we compared the baseline covariates between groups: NICM (132 patients) and ICM (132 patients). The 2-year appropriate ICD therapy risks were 27.7% and 12.2% in the NICM and ICM groups, respectively (hazard ratio, 0.390 [95% confidence interval, 0.218-0.701]; P=0.002). This subanalysis of propensity score-matched patients from the Nippon Storm Study revealed that the risk of appropriate ICD therapy was significantly higher in patients with NICM than in those with ICM.

Development and validation of a prediction model for mortality in critically ill COVID-19 patients.

Early prediction of prognosis may help early treatment measures to reduce mortality in critically ill coronavirus disease (COVID-19) patients. The study aimed to develop a mortality prediction model for critically ill COVID-19 patients. This retrospective study analyzed the clinical data of critically ill COVID-19 patients in an intensive care unit between April and June 2022. Propensity matching scores were used to reduce the effect of confounding factors. A predictive model was built using logistic regression analysis and visualized using a nomogram. Calibration and receiver operating characteristic (ROC) curves were used to estimate the accuracy and predictive value of the model. Decision curve analysis (DCA) was used to examine the value of the model for clinical interventions. In total, 137 critically ill COVID-19 patients were enrolled; 84 survived, and 53 died. Univariate and multivariate logistic regression analyses revealed that aspartate aminotransferase (AST), creatinine, and myoglobin levels were independent prognostic factors. We constructed logistic regression prediction models using the seven least absolute shrinkage and selection operator regression-selected variables (hematocrit, red blood cell distribution width-standard deviation, procalcitonin, AST, creatinine, potassium, and myoglobin; Model 1) and three independent factor variables (Model 2). The calibration curves suggested that the actual predictions of the two models were similar to the ideal predictions. The ROC curve indicated that both models had good predictive power, and Model 1 had better predictive power than Model 2. The DCA results suggested that the model intervention was beneficial to patients and patients benefited more from Model 1 than from Model 2. The predictive model constructed using characteristic variables screened using LASSO regression can accurately predict the prognosis of critically ill COVID-19 patients. This model can assist clinicians in implementing early interventions. External validation by prospective large-sample studies is required.

Exploring potential neuroimaging biomarkers for the response to non-steroidal anti-inflammatory drugs in episodic migraine

BackgroundNon-steroidal anti-inflammatory drugs (NSAIDs) are considered first-line medications for acute migraine attacks. However, the response exhibits considerable variability among individuals. Thus, this study aimed to explore a machine learning model based on the percentage of amplitude oscillations (PerAF) and gray matter volume (GMV) to predict the response to NSAIDs in migraine treatment.MethodsPropensity score matching was adopted to match patients having migraine with response and nonresponse to NSAIDs, ensuring consistency in clinical characteristics and migraine-related features. Multimodal magnetic resonance imaging was employed to extract PerAF and GMV, followed by feature selection using the least absolute shrinkage and selection operator regression and recursive feature elimination algorithms. Multiple predictive models were constructed and the final model with the smallest predictive residuals was chosen. The model performance was evaluated using the area under the receiver operating characteristic (ROCAUC) curve, area under the precision-recall curve (PRAUC), balance accuracy (BACC), sensitivity, F1 score, positive predictive value (PPV), and negative predictive value (NPV). External validation was performed using a public database. Then, correlation analysis was performed between the neuroimaging predictors and clinical features in migraine.ResultsOne hundred eighteen patients with migraine (59 responders and 59 non-responders) were enrolled. Six features (PerAF of left insula and left transverse temporal gyrus; and GMV of right superior frontal gyrus, left postcentral gyrus, right postcentral gyrus, and left precuneus) were observed. The random forest model with the lowest predictive residuals was selected and model metrics (ROCAUC, PRAUC, BACC, sensitivity, F1 score, PPV, and NPV) in the training and testing groups were 0.982, 0.983, 0.927, 0.976, 0.930, 0.889, and 0.973; and 0.711, 0.648, 0.639, 0.667,0.649, 0.632, and 0.647, respectively. The model metrics of external validation were 0.631, 0.651, 0.611, 0.808, 0.656, 0.553, and 0.706. Additionally, a significant positive correlation was found between the GMV of the left precuneus and attack time in non-responders.ConclusionsOur findings suggest the potential of multimodal neuroimaging features in predicting the efficacy of NSAIDs in migraine treatment and provide novel insights into the neural mechanisms underlying migraine and its optimized treatment strategy.

The Effect of Hemithyroidectomy in Papillary Thyroid Carcinoma with an Exclusive Involvement of the Recurrent Laryngeal Nerve: A Retrospective Study with a Propensity Score-Matched Analysis.

Involvement of the recurrent laryngeal nerve (RLN) in papillary thyroid carcinoma (PTC) is an important prognostic factor and is associated with a higher risk of recurrence. This study aimed to retrospectively analyze the outcomes of patients treated with hemithyroidectomy (HT) in PTC patients with an exclusive RLN invasion who could not tolerate staged surgery, did not wish to undergo another operation, or had other reasons. A retrospective review was conducted on 163 patients with PTC and exclusive RLN involvement at our institution between 2013 and 2019. Patients were divided into a total thyroidectomy (TT) group and HT group. The clinicopathologic factors and prognostic outcomes were compared between the two groups. A propensity score-matched analysis was carried out to reduce selection bias, with the following covariates: gender, age, tumor size, multifocality, central lymph node metastasis (CLNM), and RLN resection. The Kaplan-Meier method was used for a comparison of recurrence outcomes. In the baseline data of the 163 PTC patients, tumor size (p < 0.001), multifocality (p = 0.011), CLNM (p < 0.001), and RLN resection (p < 0.008) in the TT and HT groups differed significantly, whereas age and gender did not differ between the two groups. The TT group reported significantly higher temporary and permanent hypoparathyroidism than the HT group (p < 0.001 and p = 0.042, respectively). With 72-month median follow-up, 11 (6.7%) patients developed recurrence. After propensity score matching, 24 patients with HT and 43 patients with TT were included. Recurrence-free survival (RFS) in the matched samples showed no difference between the TT and HT groups (p = 0.092). Our results indicate that HT may be a feasible treatment for PTC patients with exclusive RLN involvement in specific circumstances without significantly increasing the risk of recurrence. Performing a thorough preoperative examination is crucial to exclude multifocal tumors and lymph node metastasis before undergoing HT.

Purely Off-Clamp Sutureless Robotic Partial Nephrectomy for Novice Robotic Surgeons: A Multi-Institutional Propensity Score-Matched Analysis.

Objectives: To compare perioperative outcomes of patients treated with sutureless off-clamp robotic partial nephrectomy (sl-oc RAPN) by either a novice or an expert robotic surgeon at two different institutions. Methods: Data concerning two continuous series of patients with cT1-2N0M0 renal tumors treated with sl-oc RAPN either by a novice or an expert surgeon were extracted from prospectively populated institutional databases over the last 4 years. Perioperative outcomes as well as the baseline characteristics of patients and tumors were compared by using χ2 and Mann-Whitney tests for categorical and continuous variables, respectively. A 1:1 propensity match score analysis (PMSa) generated two homogeneous cohorts. Logistic regression analysis was performed to assess predictors of trifecta outcomes, defined as negative surgical margins, no Clavien-Dindo ≧ 3 grade complications, and no ≧ 30% postoperative eGFR reduction. Results: Overall, 328 patients were treated by an expert surgeon, while 40 were treated by a novice surgeon. After PMSa analysis, two cohorts of 23 patients each were generated, homogeneous for all baseline variables (p ≥ 0.07). Hospital stay was the only significantly different outcome observed between the two groups (5 days vs. 2 days; p < 0.001). No statistically significant differences were recorded when comparing trifecta outcomes (expert: 100% vs. novice: 87%; p = 0.07). In the logistic regression analysis, no statistically significant predictors of trifecta outcomes were recorded. Conclusions: sl-oc RAPN is a feasible and safe nephron sparing technique, even when performed by a novice robotic surgeon.

Selection for transcatheter versus surgical aortic valve replacement and mid-term survival: results of the AUTHEARTVISIT study.

Limited data are available from randomized trials comparing outcomes between transcatheter aortic valve replacement (TAVR) and surgery in patients with different risks and with follow-up of at least 4 years or longer. In this large, population-based cohort study, long-term mortality and morbidity were investigated in patients undergoing aortic valve replacement (AVR) for severe aortic stenosis using a surgically implanted bioprosthesis (surgical/biological aortic valve replacement; sB-AVR) or TAVR. Individual data from the Austrian Insurance Funds from 2010 through 2020 were analysed. The primary outcome was all-cause mortality, assessed in the overall and propensity score-matched populations. Secondary outcomes included reoperation and cardiovascular events. From January 2010 through December 2020, a total of 18882 patients underwent sB-AVR (n = 11749; 62.2%) or TAVR (n = 7133; 37.8%); median follow-up was 5.8 (95% CI 5.7-5.9) years (maximum 12.3 years). The risk of all-cause mortality was higher with TAVR compared with sB-AVR: hazard ratio 1.552, 95% confidence interval (CI) 1.469-1.640, P < 0.001; propensity score-matched hazard ratio 1.510, 1.403-1.625, P < 0.001. Estimated median survival was 8.8 years (95% CI 8.6-9.1) with sB-AVR versus 5 years (4.9-5.2) with TAVR. Estimated 5-year survival probability was 0.664 (0.664-0.686) with sB-AVR versus 0.409 (0.378-0.444) with TAVR overall, and 0.690 (0.674-0.707) and 0.560 (0.540-0.582), respectively, with propensity score matching. Separate subgroup analyses for patients aged 65-75 years and >75 years indicated a significant survival benefit in patients selected for sB-AVR in both groups. Other predictors of mortality were age, sex, previous heart failure, diabetes and chronic kidney disease. In this retrospective national population-based study, selection for TAVR was significantly associated with higher all-cause mortality compared with sB-AVR in patients ≥65 years with severe, symptomatic aortic stenosis in the >2-year follow-up.

Evaluating the Efficacy and Safety of Aspirin for Primary Cardiovascular Prevention in Asian Patients with Type 2 Diabetes: A Population-Based and Propensity Score-Matched Study.

The risk of developing cardiovascular disease is significantly higher for individuals with diabetes compared to those without. Aspirin has been widely used for primary prevention in diabetic patients. However, evidence is limited in the Asian population. We aimed to compare the effectiveness and safety of aspirin versus placebo for primary cardiovascular prevention in the Asian population with type 2 diabetes. In this study, we performed propensity score matching with non-aspirin users from January 2006 to December 2015 (n = 37,095 in each group after matching, PSM). We analyzed the incidence risk of all-cause mortality, composite cardiovascular events, and hospitalized major bleeding. The propensity score-matched (PSM) cohort of patients who received aspirin within one year of diabetes diagnosis was compared with the non-aspirin diabetic (DM) cohort. Baseline characteristics were balanced between the two groups. The median follow-up duration was 78 months. Aspirin users exhibited a slightly but significantly lower rate of all-cause mortality (HR: 0.92; 95% CI: 0.87 to 0.96). However, they also had a significantly higher composite cardiovascular risk (HR: 1.34; 95% CI: 1.28-1.40), including non-fatal acute myocardial infarction (HR: 1.33; 95% CI: 1.18 to 1.50), non-fatal ischemic stroke (HR: 1.38; 95% CI: 1.30 to 1.45), heart failure (HR: 1.18; 95% CI: 1.09 to 1.27), and coronary revascularization (HR: 1.94; 95% CI: 1.73 to 2.17). Aspirin users also faced a significantly higher risk of hospitalized major bleeding (HR: 1.08; 95% CI: 1.03 to 1.14). The presence of one or more additional risk factors did not influence the effectiveness and safety outcomes of aspirin, according to stratified analysis. In conclusion, in this real-world Asian diabetic population, aspirin was associated with a significantly lower mortality risk but also with higher risks of cardiovascular events and hospitalized bleeding. Aspirin may not play a role in the primary prevention of cardiovascular disease in such patients, regardless of additional risk factors.

Outcomes after laparoscopic or open liver resection for nonalcoholic fatty liver disease-associated hepatocellular carcinoma: a propensity score-matching study.

Laparoscopic liver resection (LLR) is rapidly gaining popularity; however, its efficacy for nonalcoholic fatty liver disease (NAFLD)-associated hepatocellular carcinoma (HCC) (NAFLD-HCC) has been not evaluated. The purpose of this study was to compare short- and long-term outcomes between LLR and open liver resection (OLR) among patients with NAFLD-HCC. We used a single-institution database to analyze data for patients who underwent LLR or OLR for NAFLD-HCC from January 2007 to December 2022. We performed propensity score-matching analyses to compare overall postoperative complications, major morbidities, duration of surgery, blood loss, transfusion, length of stay, recurrence, and survival between the two groups. Among 210 eligible patients, 46 pairs were created by propensity score matching. Complication rates were 28% for OLR and 11% for LLR (p = 0.036). There were no significant differences in major morbidities (15% vs. 8.7%, p = 0.522) or duration of surgery (199 min vs. 189 min, p = 0.785). LLR was associated with a lower incidence of blood transfusion (22% vs. 4.4%, p = 0.013), less blood loss (415 vs. 54 mL, p < 0.001), and shorter postoperative hospital stay (9 vs. 6 days, p < 0.001). Differences in recurrence-free survival and overall survival between the two groups were not statistically significant (p = 0.222 and 0.301, respectively). LLR was superior to OLR for NAFLD-HCC in terms of overall postoperative complications, blood loss, blood transfusion, and postoperative length of stay. Moreover, recurrence-free survival and overall survival were comparable between LLR and OLR. Although there is a need for careful LLR candidate selection according to tumor size and location, LLR can be regarded as a preferred treatment for NAFLD-HCC over OLR.

Transcriptome-based response predictor to identify potential responders among patients with negative standard markers for response to immune checkpoint blockers.

2666 Background: Immune checkpoint blockers (ICB) are revolutionizing cancer treatment, and are being approved for an increasingly wide range of cancer types. The most common biomarkers currently in use to select patients for ICB are PD-L1 expression on tumor cells, as measured by IHC, and tumor mutational burden (TMB) and microsatellite instability (MSI), both measured by NGS. However, some patients that are negative for these markers still respond to ICB. This calls for complementary biomarkers to better identify responders to ICB, especially in patients that are negative to current biomarkers. Here, we focus on predicting response to anti-PD1 in patients with negative PD-L1, TMB or MSI. Methods: We employ ENLIGHT, our transcriptome-based precision oncology platform, which identifies and utilizes clinically relevant genetic interactions to predict a patient’s response to a wide range of targeted drugs, including ICB. ENLIGHT generates an individual ICB response score calculated from a 10-gene expression signature - the ENLIGHT Matching Score (EMS). Patients with EMS above a predetermined threshold are considered matched by ENLIGHT to anti-PD-1 treatments. We have previously shown, based on more than 1000 cases analyzed retrospectively, that this signature can identify responders to anti-PD-1 with high accuracy. Here, we use ENLIGHT to perform a retrospective analysis of 125 cases from three different datasets, who had low PD-L1 presentation (&lt;1%), low TMB (&lt; 10) or microsatellite stable tumors (MSS), and were treated with anti-PD-1, to specifically assess ENLIGHT’s performance in this biomarker-negative sub-population. Results: Patients who responded to anti-PD-1 treatments had significantly higher EMS in all three datasets. Correspondingly, ENLIGHT is highly predictive of response to anti-PD-1 in patients with negative ICB markers in the three datasets (ROC AUCs of 0.80, 0.84, 0.77, respectively, for low PDL1, low TMB and MSS). It is important to note that ENLIGHT was not trained on any of these datasets, and is applied as-is using previously published parameters. Overall, we find that patients who are ENLIGHT-Matched to anti-PD1 in this biomarker-negative cohort are almost 3 times more likely to respond than patients who are not (31% vs. 11%, p=5e-13). Conclusions: ENLIGHT is a powerful tool for predicting response to anti-PD-1 treatment in patients with negative standard biomarkers for ICB, a currently unmet need with considerable clinical importance.

Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification

Rescoring of peptide spectrum matches originating from database search engines enabled by peptide property predictors is exceeding the performance of peptide identification from traditional database search engines. In contrast to the peptide spectrum match scores calculated by traditional database search engines, rescoring peptide spectrum matches generates scores based on comparing observed and predicted peptide properties, such as fragment ion intensities and retention times. These newly generated scores enable a more efficient discrimination between correct and incorrect peptide spectrum matches. This approach was shown to lead to substantial improvements in the number of confidently identified peptides, facilitating the analysis of challenging datasets in various fields such as immunopeptidomics, metaproteomics, proteogenomics, and single-cell proteomics. In this review, we summarize the key elements leading up to the recent introduction of multiple data-driven rescoring pipelines. We provide an overview of relevant post-processing rescoring tools, introduce prominent data-driven rescoring pipelines for various applications, and highlight limitations, opportunities, and future perspectives of this approach and its impact on mass spectrometry-based proteomics.

Color Matching of Single-Shade Composite Resin by Various Pulp Capping Materials in Anterior Teeth

This study aimed to compare color matching between single-shade composite resin-restored teeth with various pulp capping materials and the dentin surrounding the restoration through instrumental analysis and visual evaluation of the color difference. Fifty maxillary right central incisor acrylic resin teeth were prepared with standardized Class III cavities on the proximal surfaces. These teeth were divided into five groups: restored with single-shade composite resin only; Ultra-Blend™ plus followed by single-shade composite resin; TheraCal PT™ followed by single-shade composite resin; Endocem&lt;sup&gt;®&lt;/sup&gt; MTA premixed followed by single-shade composite resin; and Well-root PT™ followed by single-shade composite resin. The color difference (ΔE&lt;sub&gt;ab&lt;/sub&gt;&lt;sup&gt;*&lt;/sup&gt;) between the restored area and the center of the resin teeth was measured using a spectrophotometer. No significant color difference was observed in groups restored with only single-shade composite resin, Ultra-Blend™ plus, and TheraCal PT™. The visual evaluation revealed that Ultra-Blend™ plus exhibited the best color matching score, whereas the Endocem® MTA premixed and Well-root PT™ groups showed significantly lower color matching scores than the single-shade composite resin-only group. When opting for single-shade composite resin usage for anterior tooth restorations with the aim of reducing chair time, pulp capping materials UltraBlend™ plus and TheraCal PT™ provide esthetically pleasing results.

Perioperative Outcomes of Robotic Radical Prostatectomy with Hugo™ RAS versus daVinci Surgical Platform: Propensity Score-Matched Comparative Analysis.

Background/Objectives: There is an urgent need for comparative analyses of the intraoperative, oncological, and functional outcomes of different surgical robotic platforms. We aimed to compare the outcomes of RARP performed at a tertiary referral robotic centre with the novel HugoTM RAS system with those performed with a daVinci surgical system, which is considered the reference standard. Methods: We analysed the data of 400 patients undergoing RARP ± pelvic lymph node dissection between 2021 and 2023, using propensity score (PS) matching to correct for treatment selection bias. All procedures were performed by three surgeons with HugoTM RAS or daVinci. Results: The PS-matched cohort included 198 patients with 99 matched pairs, balanced for all covariates. Positive surgical margins (PSMs) were found in 22.2% and 25.3% (p = 0.616) of patients, respectively, in the HugoTM RAS and daVinci groups. No significant differences were found for other important perioperative outcomes, including median (1st-3rd q) operative time (170 (147.5-195.5) vs. 166 (154-202.5) min; p = 0.540), median (1st-3rd q) estimated blood loss (EBL) (100 (100-150) vs. 100 (100-150) ml; p = 0.834), Clavien-Dindo (CD) ≥ 2 complications (3% vs. 4%; p = 0.498), and social continence at 3 months (73.7% vs. 74.7%; p = 0.353). In multiple analyses, no associations were found between surgical outcomes (PSM, length of PSM, operative time, EBL, length of catheterization, length of hospital stay, social continence at three months after surgery, and CD ≥ 2 complications) and the robotic platform. Conclusions: Our findings demonstrate that HugoTM RAS enables surgeons to safely and effectively transfer the level of proficiency they reached during their previous experience with the daVinci systems.

Albumin levels and cerebral collateral circulation in patients with acute ischemic stroke due to intracranial arteriosclerotic: A propensity score-matched analysis.

Cerebral collateral circulation (CC) is associated with the recurrence and severity of acute ischemic stroke (AIS), and early identification of poor CC is helpful for the prevention of AIS. In this study we evaluated the association between serum albumin levels and CC in AIS using logistic regression. Propensity score (PS) matching was used to eliminate the effect of confounders, and restricted cubic splines (RCS) were employed to explore potential nonlinear associations between albumin and CC. In unadjusted logistic regression analysis, lower albumin (OR = 0.85, 95% CI = 0.79-0.92) was associated with poor CC, and after adjusting for covariates, the odds of lower albumin for poor CC compared to good CC were 0.86 (95% CI = 0.79-0.94). In the PS cohort, the association of albumin with CC was consistent with those of the original cohort. RCS results showed a linear relationship between albumin and CC (P values of .006 and .08 for overall and nonlinear associations, respectively). The results of this study suggest that lower serum albumin is independently associated with an increased risk of poor CC, which may serve as an effective predictive indicator for poor CC in patients with severe intracranial atherosclerotic stenosis.

Effect of implantable cardioverter defibrillator intracardiac electrogram morphology changes on hospitalization and life quality

Abstract Background Implantable Cardioverter Defibrillators (ICD) are standard therapy for patients at risk of life-threatening ventricular tachyarrhythmias. ICDs use morphology discrimination to compare ventricular electrogram during tachycardia with reference template during baseline rhythm. Baseline morphology match score (MMS) changes may predict arrhythmic events, but usefulness as a parameter for heart failure (HF) is still unknown. Methods The prospective single-center study included consecutive 88 patients undergoing device control at cardiology department from July 2022 to May 2023. Inclusion criteria were patients implanted with ICD or CRT for at least 3 months; the exclusion criteria were defined as communication barriers (n=1), depleted device battery during checks (n=1), total AV block (n=3), and auto-template activation (n=4). The data were analysed for changes in the baseline (MMS) relationship with demographic, clinical characteristics, quality of life (QOL), and hospitalisation with HF. Results We analyzed 79 patients with a mean age 64,9 13,6 and an average MMS of 98 1,8 morphology. During follow-up there were 12 (15%) patients hospitalized due to HF. ROC curve analysis showed that a MMS ≤ 97% had 73% sensitivity and 59% specificity for hospitalization (p: 0,033 Area 0.695). No significant differences were observed in demographics between the two groups. Although there was no significant difference in EF and BNP levels, patients with MMS &amp;lt;97% had lower QOL scores and more hospitalizations for heart failure (HF). Conclusion EGM baseline MMS changes in ICD were associated with hospitalization for HF and QOL, apart from arrhythmia detection indications. It may be a follow-up parameter for HF, in addition to the current device algorithms.Graphical AbstractTable 1

#2427 A multi-targeted treatment approach to induce early remission in high-risk primary membranous nephropathy

Abstract Background and Aims A considerable proportion of primary membranous nephropathy (PMN) patients do not achieve early clinical remission with current immunosuppression regimens. The goal of the study was to evaluate efficacy and safety of the multi-targeted treatment regimen including rituximab, cyclophosphamide, and corticosteroids (all administered at low cumulative doses) (RCP) in PMN with antibodies to the phospholipase A2 receptor (anti-PLA2R). Method The study enrolled 30 high- or very-high risk PMN patients with persistent nephrotic syndrome (NS) and elevated anti-PLA2R in a prospective single-arm study of RCP treatment. The experimental protocol consisted of a single intravenous infusion of RTX (375 mg/m2) and methylprednisolone (500 mg), followed by oral prednisolone (1 mg/kg) tapered rapidly at 10 mg per week and discontinued at week 49. An additional RTX infusion at the same dose was given during weeks 8-12, 20-24, and 32-36 if complete remission was not achieved and peripheral CD19+ cell exceeded 5 cells/μl. Four intravenous infusions of CYC were administered at a dose of 7.5 mg/kg every other week, in weeks 1, 3, 5, and 7. The effectiveness of RCP was compared to that of historic controls who received either rituximab-based therapy (RTX, n = 15) or cyclosporine+corticosteroids (CSA, n = 42). The primary outcomes measured were complete clinical remission (CR), overall remission (OR, which combines complete and partial remission) at month 12 after treatment initiation, and the time to clinical remission. Cox regression models were used to analyse the effect of RCP therapy on the probability of remission. Furthermore, we conducted comparative time-to-remission analyses in the RCP group and controls after propensity score (PS) matching. Results The RCP group exhibited higher OR and CR rates at 12 months (97% and 60%) compared to the RTX group (60% and 7%, P≤0.009) and the CSA group (50% and 24%, P≤0.003) (Fig. 1A,B). The median time to OR was shorter in the RCP group (2.8 (1.6–3.9) months) than in the RTX group (7.1 (3.4–17.5) months, P = 0.008) and the CSA group (7.3 (6.0–13.6) months, P &amp;lt; 0.001) (Fig. 1A). In the adjusted Cox regression, the hazard ratios for OR and CR attainment for RCP compared to other treatments were 5.2 (95% CI: 2.8–9.6) and 4.8 (95% CI: 2.2–10.3), respectively. These results were confirmed by comparative analyses of propensity score-matched groups. Only one serious adverse event (SAE) occurred in the RCP group during the 56 patient-year follow-up. Conclusion RCP therapy is considered effective and safe for inducing early remission in high-risk PMN patients.

Unveiling the Deep Connection Between Athlete Momentum and Match Scoring through Statistics Analysis

The concept of momentum in ball sports is characterized by significant changes in-game performance and mental states, which play a key role in determining the outcome of a match. This study takes the 2023 Wimbledon men's final as an example and constructs a model for assessing athletes' performance during tennis matches based on binary logistic regression. It also constructs a tennis match momentum assessment algorithm to explore the relationship between the momentum change among match players and the performance change (score difference) of both players. It was found that the momentum change of match players was closely related to the score difference. This study is not only conducive to improving the athletes' competitive level but also has a profound impact on the scientific and professional development of tennis.

Unlocking Tennis Dynamics: A Hidden Markov Model Approach to Match Scoring

Unlocking Tennis Dynamics: A Hidden Markov Model Approach to Match Scoring

On the security risk of pre-image attack on cancelable biometrics

Over the years, a number of biometric template protection schemes, often based on the notion of “cancelable biometrics”, have been proposed. An ideal cancelable biometric algorithm complies with four criteria: irreversibility, revocability, unlinkability, and performance preservation. Cancelable biometrics employs an irreversible but distance preserving transformation to convert the original biometric templates into protected templates. Matching in the transform domain can be accomplished due to the property of distance preservation. However, distance preservation also entails security issues, a point often overlooked in existing research. In this paper, we have conducted a comprehensive security analysis of distance preservation in cancelable biometrics for the first time. The analysis is based on a pre-image attack, which is launched to break the security of cancelable biometrics under Kerckhoffs’s assumption. Furthermore, we propose a general security analysis framework under the single and cross-transformation attacks, which also employs an information leakage estimation strategy based on mutual information as a complement. The experimental results performed on real face, iris, and fingerprint data demonstrate that the risks originating from the matching scores computed from the distance/similarity of two cancelable templates greatly compromise the security of cancelable biometric schemes, including the classic Biohashing, Index-of-max hashing, Non-linear multi-dimensional spectral hashing, Indexing-First-One hashing, Bloom Filter and Two-factor Protected Minutia Cylinder-Code. The security versus accuracy trade-off is discussed and recommendations for designing a biometric system secure against pre-image attacks are also proposed. The source code is available at github.com/biometricsecurity/CBrisks.