Predictors Of Treatment Success Research Articles

Expression and function of α4β7 integrin predict the success of vedolizumab treatment in inflammatory bowel disease

Inflammatory bowel diseases are medically intractable and require constant therapy in many cases. While a growing number of biologicals and small molecules is available for treatment, a substantial portion of patients experiences primary non-response to these compounds and head-to-head evidence for therapy selection is scarce. Thus, approaches to predict treatment success in individual patients are a huge unmet need.We had previously suggested that the expression and function of α4β7 integrin on T cells in the peripheral blood correlate to outcomes of therapy with the anti-α4β7 integrin antibody vedolizumab. Here, we conducted a translational multicenter trial to prospectively evaluate this hypothesis.In a cohort of 89 patients with inflammatory bowel disease undergoing regular therapy with vedolizumab, lower baseline expression of α4β7 was associated with short-term clinical response. Consistently, low α4β7 expression in patients achieving remission predicted sustained remission in week 30. Moreover, high dynamic adhesion of CD4+ T cells to MAdCAM-1 and high reduction of adhesion by vedolizumab in vitro at baseline were associated with clinical remission.These data substantiate the potential of α4β7 integrin function and expression to forecast outcomes of vedolizumab therapy. Further translational efforts are necessary to improve the performance of the assays and to implement the concept in clinical practice.

Long-term success in percutaneous valve commissurotomy – is Wilkins score over 9 a definitive limit?

Abstract Background Percutaneous valve commissurotomy (PMC) is an established treatment in patients with significative mitral stenosis (MS). Although rheumatic MS incidence has decreased in the last century, it remains a prevalent pathology worldwide. The Wilkins score (WS) is a reference in echocardiographic assessment of MS; a score ≤8 is considered a predictor of treatment success and score between 9 and 11 is a “grey zone” (WGZ) in which doubts persists regarding PMC success. Purpose To evaluate the early and long-term results of PMC in patients with rheumatic MS and to compare long-term events between patients with WS ≤8 and patients in WGZ. Methods We retrospectively analysed all patients between 1991 and 2008 with significative rheumatic MS undergoing PMC. Data were collected at baseline and during long-term follow-up. M ACE was defined as a composite of all-cause mortality, mitral valve re-intervention or cardiovascular hospitalization. Results In our cohort, 124 patients were included. Most were female (87%), mean age at the time of repair was 46±11 year-old and mean follow-up was 20±6 years. Before the procedure, 81% had WS ≤8 and 19% were in WGZ. Both groups had similar baseline characteristics, namely age at first intervention, NYHA class and follow-up time. All patients had preserved biventricular systolic function, 83% presented PH, mean transvalvular gradient (TVG) and mitral valve area (MVA) were 12.8 mmHg and 1.0 cm2, respectively. Most of the procedures were successful (91%) and without complications (94%). Mean MVA improvement was similar in both groups [0.9 cm2 in WS ≤8 and 0.8 cm2 in WGZ, t(102)=0.173, p=0.863]; there was also no significative difference in TVG and PASP reduction after PMC. During long-term follow-up, re-intervention and mortality occurred in 40% and 23% in WS ≤8 and in 50% and 29% in WGZ, respectively, and none of these differences was statistically significant (p=0.389 and p=0.544, respectively). Concerning time-to-event analysis, approximately 80% of patients kept uneventful and >90% alive after 10 years in both groups and no significant difference in M ACE events and all-cause mortality between WS ≤8 and WGZ was observed (Log Rank, p=0,419 and p=0.950, respectively). Conclusion PMC was safe and effective in clinically significant rheumatic MS in both WS ≤8 and WS 9–11, with similar MVA improvement. After 10 years, approximately 80% of patients were MACE-free and >90% alive in both groups. There was no difference in all-cause mortality and in a composite of all-cause death, mitral valve re-intervention or cardiovascular hospitalization concerning WS groups. Funding Acknowledgement Type of funding sources: None.

Clinical Effectiveness and Pharmacokinetics of Dalbavancin in Treatment-Experienced Patients with Skin, Osteoarticular, or Vascular Infections.

Dalbavancin (DBV) is a lipoglycopeptide approved for the treatment of Gram-positive infections of the skin and skin-associated structures (ABSSSIs). Currently, its off-label use at different dosages for other infections deserves attention. This work aimed to study the clinical effectiveness and tolerability of DBV in outpatients with ABSSSIs, osteoarticular (OA), or other infections, treated with either one or two 1500 mg doses of dalbavancin, for different scheduled periods. A liquid chromatography–tandem mass spectrometry method was used to measure total DBV concentrations. PK/PD parameters and the clinical and microbiological features of this cohort were evaluated in order to investigate the best predictors of treatment success in real-life settings. Of the 76 screened patients, 41 completed the PK study. Long-term PK was comparable to previous studies and showed significant differences between genders and dosing schedules. Few adverse events were observed, and treatment success was achieved in the vast majority of patients. Failure was associated with lower PK parameters, particularly Cmax. Concluding, we were able to describe DBV PK and predictors of treatment success in selected infections in this cohort, finding DBV Cmax as a possible candidate for therapeutic drug-monitoring purposes, as well as highlighting the dual-dose one-week-apart treatment as the optimal choice for OA infections.

Daily variations and levels of human chorionic gonadotropin before methotrexate treatment as predictors of treatment success.

The aim of this study is to investigate the role of human chorionic gonadotropin (hCG) daily variations and levels prior to methotrexate treatment as predictors for treatment outcome. This retrospective study included patients who had a sonographically confirmed ectopic pregnancy at the International Peace Maternity and Child Health Hospital between November 2015 and June 2020. The associations of hCG levels and daily variations with the treatment success were evaluated by multivariable logistic regression and receiver operator characteristic (ROC) curve. Establish a nomogram that predicts how methotrexate (MTX) therapy will turn out. The performance of the model was assessed utilizing concordance index, receiver operating characteristic curves, and calibration plots. The median serum hCG levels before treatment and hCG daily variation in the failure group were higher than those in the success group (487.8 vs. 270.7 IU/L, -1.86% vs. 7.29%, both p < 0.01). According to the ROC curve analysis, the cutoff values of serum hCG level before treatment and daily variations were 617.35 IU/L and 1.76%/day. By multivariable logistic regression analysis, serum hCG levels before treatment (odds ratio [OR]: 1.001, 95% confidence interval [CI]: 1.000 ~ 1.001) and hCG daily variations were independently associated with the treatment success (OR: 1.033, 95% CI: 1.015 ~ 1.052). The nomogram was effective at predicting the outcome of MTX treatment with a receiver operating characteristic area under the curve of 0.717 (p < 0.001). The nomogram's calibration curve was almost parallel to the ideal diagonal line. We successfully created a nomogram based on serum hCG levels before treatment and hCG daily changes to anticipate the result of MTX therapy, which could assist medical professionals in selecting therapeutic schedule for patients with tubal pregnancies.

How well do ESWL nomograms predict treatment success in pediatric patients?

To study was to identify the variables that influence the outcomes of pediatric SWL patients in our clinic and to compare our findings to previously published nomograms. All children who underwent SWL at a single center between 2005 and 2020 were included in this retrospective study. Depending upon the age and mental state of the children, SWL procedures were performed with or without anesthesia. Data from the hospital information system were obtained on patient characteristics, metabolic evaluation, imaging, SWL details, and post-procedure results, and their correlation with the Onal and Dogan nomograms was evaluated. The present study included 112 pediatric patients in total. The average age was 8.22 ± 4.9 (83.3 ± 58.1 months, 4 months-16 years), and the median stone size was 9.5 ± 3.2 mm (4-20 mm). Even though there was quite a significant positive correlation between age and the number of shots and the intensity of shots (intensity and number of shots increased with increasing age), there was no statistical difference in the number of sessions and stone-free rates. The number of shots and sessions was significantly lower in patients with hydronephrosis (N = 70) than in those without (N = 42) (p < 0.001). When the stone-free rates of patients without and with hydronephrosis were compared, it was discovered that they were 69.05% and 92.86%, respectively, which was statistically significant (p < 0.01). It is believed that the nomograms developed for SWL in pediatric patients should be reviewed, and larger, prospective studies should be conducted.

Radiomics and Deep Learning for Disease Detection in Musculoskeletal Radiology: An Overview of Novel MRI- and CT-Based Approaches.

Radiomics and machine learning-based methods offer exciting opportunities for improving diagnostic performance and efficiency in musculoskeletal radiology for various tasks, including acute injuries, chronic conditions, spinal abnormalities, and neoplasms. While early radiomics-based methods were often limited to a smaller number of higher-order image feature extractions, applying machine learning-based analytic models, multifactorial correlations, and classifiers now permits big data processing and testing thousands of features to identify relevant markers. A growing number of novel deep learning-based methods describe magnetic resonance imaging- and computed tomography-based algorithms for diagnosing anterior cruciate ligament tears, meniscus tears, articular cartilage defects, rotator cuff tears, fractures, metastatic skeletal disease, and soft tissue tumors. Initial radiomics and deep learning techniques have focused on binary detection tasks, such as determining the presence or absence of a single abnormality and differentiation of benign versus malignant. Newer-generation algorithms aim to include practically relevant multiclass characterization of detected abnormalities, such as typing and malignancy grading of neoplasms. So-called delta-radiomics assess tumor features before and after treatment, with temporal changes of radiomics features serving as surrogate markers for tumor responses to treatment. New approaches also predict treatment success rates, surgical resection completeness, and recurrence risk. Practice-relevant goals for the next generation of algorithms include diagnostic whole-organ and advanced classification capabilities. Important research objectives to fill current knowledge gaps include well-designed research studies to understand how diagnostic performances and suggested efficiency gains of isolated research settings translate into routine daily clinical practice. This article summarizes current radiomics- and machine learning-based magnetic resonance imaging and computed tomography approaches for musculoskeletal disease detection and offers a perspective on future goals and objectives.

Development and Validation of a Deep Learning Model for Predicting Treatment Response in Patients With Newly Diagnosed Epilepsy

Selection of antiseizure medications (ASMs) for epilepsy remains largely a trial-and-error approach. Under this approach, many patients have to endure sequential trials of ineffective treatments until the "right drugs" are prescribed. To develop and validate a deep learning model using readily available clinical information to predict treatment success with the first ASM for individual patients. This cohort study developed and validated a prognostic model. Patients were treated between 1982 and 2020. All patients were followed up for a minimum of 1 year or until failure of the first ASM. A total of 2404 adults with epilepsy newly treated at specialist clinics in Scotland, Malaysia, Australia, and China between 1982 and 2020 were considered for inclusion, of whom 606 (25.2%) were excluded from the final cohort because of missing information in 1 or more variables. One of 7 antiseizure medications. With the use of the transformer model architecture on 16 clinical factors and ASM information, this cohort study first pooled all cohorts for model training and testing. The model was trained again using the largest cohort and externally validated on the other 4 cohorts. The area under the receiver operating characteristic curve (AUROC), weighted balanced accuracy, sensitivity, and specificity of the model were all assessed for predicting treatment success based on the optimal probability cutoff. Treatment success was defined as complete seizure freedom for the first year of treatment while taking the first ASM. Performance of the transformer model was compared with other machine learning models. The final pooled cohort included 1798 adults (54.5% female; median age, 34 years [IQR, 24-50 years]). The transformer model that was trained using the pooled cohort had an AUROC of 0.65 (95% CI, 0.63-0.67) and a weighted balanced accuracy of 0.62 (95% CI, 0.60-0.64) on the test set. The model that was trained using the largest cohort only had AUROCs ranging from 0.52 to 0.60 and a weighted balanced accuracy ranging from 0.51 to 0.62 in the external validation cohorts. Number of pretreatment seizures, presence of psychiatric disorders, electroencephalography, and brain imaging findings were the most important clinical variables for predicted outcomes in both models. The transformer model that was developed using the pooled cohort outperformed 2 of the 5 other models tested in terms of AUROC. In this cohort study, a deep learning model showed the feasibility of personalized prediction of response to ASMs based on clinical information. With improvement of performance, such as by incorporating genetic and imaging data, this model may potentially assist clinicians in selecting the right drug at the first trial.

An interim oral appliance as a screening tool during drug-induced sleep endoscopy to predict treatment success with a mandibular advancement device for obstructive sleep apnea.

PurposePrevious studies have shown a wide range of efficacy (29 to 71%) of a mandibular advancement device (MAD) in the treatment of obstructive sleep apnea (OSA). Currently, the ability to preselect suitable patients for MAD therapy based on individual characteristics related to upper airway collapsibility is limited. We investigated if the use of non-custom interim MAD during drug-induced sleep endoscopy (DISE) could be a valuable screening tool to predict MAD treatment outcome.MethodsIn a single-center prospective study including a consecutive series of patients with OSA, we compared DISE outcomes with a MAD in situ with polysomnography results after 3 months of using the same MAD that was used during DISE.ResultsOf 41 patients who completed the study, the median apnea–hypopnea index (AHI) was 16.0 events/h [IQR 7.4–23.4]. Respiratory outcomes on polysomnography, including apnea index (AI), total AHI, AHI in supine position, and oxygen desaturation index, all significantly improved after 3 months of MAD treatment. With complete improvement of the upper airway obstruction with the MAD in situ during DISE in supine position, patients were 6.3 times more likely to be a responder to MAD treatment compared to patients with a persisting complete obstruction, although not statistically significant (OR 6.3; 95%CI 0.9–42.7; p = 0.060).ConclusionThe potential predictive value with regard to MAD therapy outcomes of the use of an interim MAD during DISE would be an important finding, since the prediction of MAD therapy outcome is of great clinical and scientific interest. A study with a larger cohort should be performed to further investigate our findings.

Factors Associated With Treatment Response in an Internet-Based Intervention for Prolonged Grief Disorder After Cancer Bereavement

Internet-based psychological interventions have proven effective in the treatment of prolonged grief disorder (PGD). Yet, some patients do not benefit from treatment in a clinically significant way. We aimed to examine predictors of symptom reduction in an Internet-based intervention for PGD after cancer bereavement, in order to identify possible treatment mechanisms and discern directions for future intervention design. A secondary analysis of data from a randomized wait-list controlled trial on an Internet-based intervention for PGD after cancer bereavement was conducted. Multiple regression models were used (1) to test for the influence of pretreatment PGD, working alliance, avoidance and gender on PGD symptom reduction; and (2) to explore further predictors of treatment success with a best subset selection protocol. The regression models explained 18% (Model 1) and 34% (Model 2) of variance in symptom reduction. Participants with more favorable symptom change had more severe pretreatment PGD scores and better working alliance. Those with lower social support and less posttraumatic growth experienced more PGD symptom change. In conclusion, therapeutic alliance is an important factor that should be monitored and fostered. Findings regarding social support and posttraumatic growth need further replication and clarification.

Predictor Factors of Tuberculosis Treatment Success in Sleman Regency of Indonesia

Background : Tuberculosis (TB) is the leading cause of mortality worldwide. Several studies have created risk scores to predict treatment success in TB patients. However, cohort study did not consider other clinical forms of TB, such as negative AFB smears and extrapulmonary TB. The objectives of this study was to knowing the predictor factors for the success of TB treatment in Sleman Regency by taking into account other clinical forms of TB such as negative smear and extrapulmonary TB. Methods : The type and design of this study was an analytical study using a cross- sectional design conducted on TB patients in Sleman Regency from 2015 – 2018. Data were collected from TB 01 or TB 03 register of the Sleman District Health Office, including age, sex, BMI at the beginning of treatment, OAT (Antituberculosis Drugs) guideline, anatomic location, initial AFB status, AFB conversion status in intensive phase, type of TB patient, and treatment outcome. Chi-Square analysis and logistic regression were used to determine the predictors of TB treatment success. Results : The research sample was 2308 people: 2158 successful treatments and 150 patients whofailed. AFB conversion in the intensive phase was the only variable to have a role in the TB treatment success (OR = 6.655, 95% CI: 3.354–13,207, p = 0.000). Conclusion : Conversion of AFB status in the intensive phase is a variable that contributes to the success of TB treatment. Age, sex, BMI at the beginning of treatment, OAT guidelines, anatomic location, initial AFB status, and type of TB patient are not predictors of TB success.

Predicting the success of multimodal rehabilitation in chronic ankle instability based on patient-reported outcomes

BackgroundThe aim of this study was to identify potential indicators to predict the success of multimodal rehabilitation in chronic ankle instability (CAI) patients based on patient-reported outcomes. MethodsSixty patients with self-reported CAI participated. Their demographic information, injury history, and symptoms were recorded. Physical examinations and dynamic posture control tests were performed. The participants underwent sixteen 30-min treatment sessions of multimodal rehabilitation over 8 weeks. Fifty-one patients (85.0%) were available for follow-up after 8 weeks of the intervention. Treatment success was defined based on the participants’ perceived recovery using the global rating of change (GRC). Potential predictor variables were entered into a stepwise logistic regression model to identify variables for the prediction of treatment success.ResultsForty of 51 participants (78.4%) were considered to have a successful outcome. Of the variables assessed, time since last sprain ≤ 8 months was a predictor of treatment success (p < 0.05). If a patient met the criteria, there was an 88.03% probability of successful multimodal rehabilitation.ConclusionA time since the last sprain ≤ 8 months may predict successful patient-reported outcomes after multimodal rehabilitation in CAI patients.Level of evidenceProspective study, Level 2.

Reducing severe fatigue in patients with diffuse glioma: a study protocol for an RCT on the effect of blended cognitive behavioural therapy

BackgroundFatigue is the most frequent and burdensome symptom of patients with diffuse glioma. It is closely linked to decreased health-related quality of life and symptoms such as depression and sleep disturbances. Currently, there is no evidence-based treatment that targets severe fatigue in patients with brain tumours. Cognitive behavioural therapy is aimed at fatigue-maintaining beliefs and behaviour. This therapy has been proven effective in reducing severe fatigue in cancer survivors and patients with multiple sclerosis. A blended therapy program combines sessions with a therapist with therapist-guided web-based therapy modules. The aim of this randomized controlled trial is to determine the efficacy of blended cognitive behavioural therapy in treating severe fatigue in patients with diffuse glioma.MethodsWe will include a maximum of 100 patients with diffuse glioma with clinically and radiologically stable disease and severe fatigue (i.e. Checklist Individual Strength, subscale fatigue severity ≥ 35). Patients will be randomized to blended cognitive behavioural therapy or a waiting list condition. The 12-week intervention GRIP on fatigue consists of five patient-therapist sessions and five to eight individualized web-based therapy modules supported by email contact. The primary outcome measure is fatigue severity. Secondary outcome measures include sleep quality, health-related quality of life, depression, anxiety, functional impairment and subjective and objective cognitive functioning. Primary and secondary outcome measures will be assessed at baseline and after 14 and 24 weeks. Magnetoencephalography and MRI will be used to evaluate potential biomarkers for intervention success. This trial has a Bayesian design: we will conduct multiple interim analyses to test for efficacy or futility of the trial. This is the first trial within the GRIP trial platform: a platform developing four to five different interventions for the most common symptoms in patients with diffuse glioma.DiscussionThe results of the GRIP on fatigue trial will provide information about the efficacy of this intervention on fatigue in patients with diffuse glioma. Multiple other outcomes and possible predictors of treatment success will also be explored.Trial registrationNetherlands Trial Register NL8711. Registered on 14 June 2020.

Are the current nomograms sufficient to predict shockwave lithotripsy outcomes?

Introduction and objectivesTo investigate factors affecting SWL outcomes, validate three current nomograms (Kim JK, Triple D and S3HoCKwave) and compare the predictive ability of the nomograms for SWL outcomes in upper urinary tract stones. Patients and methodsMedical records of patients with renal and proximal ureteral stones treated with SWL between March 2013 and October 2020 were retrospectively reviewed. Factors affecting SWL success were analyzed with multivariate logistic regression analysis and the three predictive scoring systems compared with the area under the curve (AUC). ResultsA total of 580 patients were included in our study. The overall stone free rate was 61% and 144/580 patients (24.8%) were stone free after one session. In multivariate logistic regression analysis, stone location at upper calyx (OR:2.988; 95%Cl: 1.350–6.612; p = 0.007), middle calyx (OR:3.036; 95%Cl: 1.472–6.258; p = 0.003), and lower calyx (OR:2.131; 95%Cl: 1.182–3.839; p = 0.012), as well as number of stones (OR:1.663; 95%Cl: 1.140–2.425; p = 0.008), maximum diameter of stone (OR:1.156; 95%Cl: 1.098–1.217; p < 0.001) and maximum Hounsfield Unit (OR:1.001; 95%Cl: 1.001–1.002; p < 0.001) were independent risk factors of SWL failure. The AUCs of the Kim JK, Triple D and S2HoCKwave scores for predicting SWL success were 0.678, 0.548, and 0.626 respectively. ConclusionsStone location, number, maximal diameter, and maximum HU were independent predictive factors for SWL outcome in the treatment of upper urinary tract stones. Current nomograms, “Kim JK nomogram”, “Triple D score” and “S3HoCKwave score” can predict treatment success after SWL, but all of them have poor discrimination according to AUC analysis.

Predictors of Treatment Success in Awake Prone Positioning for Non-Intubated COVID-19 Patients With Acute Hypoxemic Respiratory Failure.

Prone positioning is known to reduce mortality among patients on mechanical ventilation with moderate-to-severe ARDS.[1][1] When extrapolating data about these patients with ARDS, awake prone positioning is touted as a low-risk intervention that can be performed outside the ICU. Studies show that

The usefulness of the Hounsfield unit and stone heterogeneity variation in predicting the shockwave lithotripsy outcome.

PURPOSE This study aimed to evaluate the use of stone density variation coefficient (SDVC) as an indicator of stone heterogeneity and previously reported parameters for predicting extracorporeal shock wave lithotripsy (ESWL) outcome in urinary calculi. Moreover, a new formula that could be used to predict ESWL success was suggested. METHODS A total of 850 patients, who underwent the first session of ESWL for urinary stones between 2015 and 2020, were examined, and 220 eligible patients were included in the study. Stone density variation coefficient and other parameters associated with stone attenuation values and stone size parameters were studied as potential predictors based on noncontrast com- puted tomography (NCCT). Extracorporeal shock wave lithotripsy success was considered after 3 months by radiography or NCCT. Logistic regression analysis was performed to determine the factors contributing to treatment success. RESULTS For the 220 patients, ESWL success rate was 39.5%. The receiver operating characteristic analysis showed that SDVC (AUC=0.82; 95% confidence interval [CI]: 0.76-0.87; P < .001), mean stone density (AUC=0.81; 95% CI:0.75-0.87; P < .001), maximum stone density (AUC=0.70; 95% CI: 0.63-0.78; P < .001), stone volume (AUC=0.70; 95% CI: 0.62-0.77; P < .001), and major diam- eter (AUC=0.67; 95% CI: 0.59-0.74; P < .001) had significant prediction accuracy from high to low. Additionally, SDVC was found to be successful in predicting ESWL success, especially for patients with high mean stone density (OR = 10; 95% CI: 3.55-28.57; P < .001). The logistic regres- sion model, in which the "stone disintegration probability" (SDP) formula was found, correctly predicted ESWL success with a single session by 79.1%. CONCLUSION In conclusion, size and attenuation values were predictors of treatment success, and the best predictor was SDVC. Evaluation of SDP formula prior to ESWL could predict treatment outcomes and facilitate the decisions regarding treatment strategies.

¿Son suficientes los nomogramas actuales para predecir los resultados de la litotricia por ondas de choque?

Introduction and objectivesTo investigate factors affecting SWL outcomes, validate three current nomograms (Kim JK, Triple D and S3HoCKwave) and compare the predictive ability of the nomograms for SWL outcomes in upper urinary tract stones. Patients and methodsMedical records of patients with renal and proximal ureteral stones treated with SWL between March 2013 and October 2020 were retrospectively reviewed. Factors affecting SWL success were analyzed with multivariate logistic regression analysis and the three predictive scoring systems compared with the area under the curve (AUC). ResultsA total of 580 patients were included in our study. The overall stone free rate was 61% and 144/580 patients (24.8%) were stone free after one session. In multivariate logistic regression analysis, stone location at upper calyx (OR:2.988; 95%Cl: 1.350–6.612; p=0.007), middle calyx (OR:3.036; 95%Cl: 1.472–6.258; p=0.003), and lower calyx (OR:2.131; 95%Cl: 1.182–3.839; p=0.012), as well as number of stones (OR:1.663; 95%Cl: 1.140–2.425; p=0.008), maximum diameter of stone (OR:1.156; 95%Cl: 1.098–1.217; p<0.001) and maximum Hounsfield Unit (OR:1.001; 95%Cl: 1.001–1.002; p<0.001) were independent risk factors of SWL failure. The AUCs of the Kim JK, Triple D and S2HoCKwave scores for predicting SWL success were 0.678, 0.548, and 0.626 respectively. ConclusionsStone location, number, maximal diameter, and maximum HU were independent predictive factors for SWL outcome in the treatment of upper urinary tract stones. Current nomograms, Kim JK nomogram, Triple D score and S3HoCKwave score can predict treatment success after SWL, but all of them have poor discrimination according to AUC analysis.

Delaying Invasive Treatment in Unilateral Head and Neck Lymphatic Malformation Improves Outcomes.

Large (De Serres stage [IV-V]) head and neck lymphatic malformations (HNLMs) often have multiple, high-risk, invasive treatments (ITs) to address functional compromise. Logically reducing HNLM ITs should reduce treatment risk. We tested whether delaying HNLM ITs reduces total IT number. Consecutive HNLM patients (n= 199) between 2010 and 2017, aged 0-18 years. ITs (surgery or sclerotherapy) were offered for persistent or dysfunction causing HNLMs. Treatment effectiveness categorized by IT number: optimal (0-1), acceptable (2-5), or suboptimal (>5). Clinical data were summarized, and outcome associations tested (χ2 ). Relative risk (RR) with a Poisson working model tested whether HNLM observation or IT delay (>6 months post-diagnosis) predicts treatment success (i.e., ≤1 IT). Median age at HNLM diagnosis was 1.3 months (interquartile range [IQR] 0-45 m) with 107/199(54%) male. HNLM were stage I-III (174 [88%]), IV-V (25 [13%]). Initial treatment was observation (70 [35%]), invasive (129 [65%]). Treatment outcomes were optimal (137 [69%]), acceptable (36 [18%]), and suboptimal (26 [13%]). Suboptimal outcome associations: EXIT procedure, stage IV-V, oral location, and tracheotomy (p< 0.001). Stage I-III HNLMs were initially observed compared with stage I-III having ITs within 6 months of HNLM diagnosis, had a 82% lower relative treatment failure risk ([i.e., >1 IT], RR=0.09, 95% CI 0.02-0.36, p< 0.001). Stage I-III HNLMs with non-delayed ITs had reduced treatment failure risk compared with IV-V (RR=0.47, 95% CI 0.33-0.66, p< 0.001). Observation and delayed IT in stage I-III HNLM ("Grade 1") is safe and reduces IT (i.e., ≤1 IT). Stage IV-V HNLMs ("Grade 2") with early IT have a greater risk of multiple ITs. 4 Laryngoscope, 133:956-962, 2023.

Coupling gamified continuing education with confidence-based assessment to address knowledge gaps and assess attitudes towards liquid biopsy for cancer screening among primary care providers.

11012 Background: Blood-based liquid biopsy assays offer a simplified approach to detect cancer early, guide clinical decision making, and predict treatment success. Given their novelty, primary care providers need education to improve knowledge and confidence regarding their use. The use of gamification in continuing medical education (CME) has been shown to increase engagement and knowledge transfer, and confidence-based learning can improve the educational experience by identified areas in which learners lack comfort. Methods: We provided a gamified CME activity based on the principles of confidence-based learning designed to educate primary care providers (PCPs) on the latest advances regarding the use of liquid biopsy for cancer screening. The game coupled knowledge questions with self-assessment of confidence to gage awareness of these topics. Pre- and post-test was used to quantify the impact of the education. The CE activity was available for credit from March 31, 2021 to March 31, 2022. Results: As of January 2022, 389 PCPs have participated. Overall, participants scored an average 76% on gaming questions related to the rationale behind the use of cell free DNA (cfDNA) for cancer screening and the benefits of liquid biopsy over tissue biopsy, demonstrating relatively high baseline knowledge on these topics. Self-reported confidence among those who answered correctly, however, was only 3.4 out of 5.0, suggesting a lack of comfort with the concepts despite answering correctly. On topics related to specific studies that demonstrated the clinical utility of liquid biopsy, participants scored only 59% and confidence scored averaged 3.17 out of 5.0, demonstrating a lack of knowledge and comfort on these topics. Across all topics, providers scored a 61% on a pre-test. Post-learning, providers scored 89%, highlighting the impact of the education on knowledge gaps. Moreover, while 52% of participants had never ordered a liquid biopsy for cancer screening prior to the education, 69% report being likely or extremely likely to do so because of the education provided. Conclusions: Integration of gamified and confidence-based learning into CE activities is an impactful way to identify and address knowledge gaps while also informing the need for future education. In this study, while self-report of confidence generally correlated with knowledge scores, confidence scores were only average even among those who answered correctly, demonstrating the need for skills-based learning that may improve comfort with liquid biopsy in the clinical setting.

Equal effect of a noncustom vs a custom mandibular advancement device in treatment of obstructive sleep apnea.

Numerous types of mandibular advancement devices (MADs) are available to treat patients with obstructive sleep apnea, varying from noncustom to custom devices. Only a limited number of studies have been performed to determine whether a noncustom MAD could be used to predict treatment success of a custom MAD. In this study, we investigated the potential of a new-generation noncustom MAD, by comparing its effectiveness with a custom MAD. We hypothesized that the effectiveness of the devices is similar with regard to both objective (polysomnography) and self-reported (questionnaires, adherence, and patient satisfaction) outcomes. This was a single-center prospective randomized crossover study including a consecutive series of patients with obstructive sleep apnea. Patients were randomized to start either with the noncustom or custom MAD. Both MADs were applied for 12 weeks, followed by polysomnography with MAD in situ and questionnaires. After the first 12 weeks of follow-up, a washout period of 1 week was applied. Equal effectiveness was defined as no significant differences in both objective and self-reported outcomes between both devices. Fifty-eight patients were included; 40 completed the full follow-up. The median apnea-hypopnea index significantly decreased from 16.3 (7.7, 24.8) events/h to 10.7 (5.6, 16.6) events/h with the custom MAD (P = .010) and to 7.8 (2.9, 16.1) events/h with the noncustom MAD (P < .001). Self-reported outcomes significantly improved in both groups. No significant differences were found between both devices. The effectiveness of a noncustom and custom MAD is comparable, which suggests that a noncustom MAD can be used as a selection tool for MAD treatment eligibility to improve MAD treatment outcome. Registry: Netherlands Trial Register; Name: The Use of a Boil and Bite Mandibular Advancement Device vs a Custom Mandibular Advancement Device in Obstructive Sleep Apnea Management; URL: https://www.trialregister.nl/trial/7249; Identifier: NL64738.100.18. Bosschieter PFN, Uniken Venema JAM, Vonk PE, etal. Equal effect of a noncustom vs a custom mandibular advancement device in treatment of obstructive sleep apnea. J Clin Sleep Med. 2022;18(9):2155-2165.

PO-669-01 LONG-TERM ADHERENCE TO FLECAINIDE AS A RHYTHM CONTROL THERAPY IN RECURRENT ATRIAL FIBRILLATION - A RETROSPECTIVE COHORT STUDY

The choice of rhythm control drugs for recurrent atrial fibrillation (AF) remains empirical and is based on the safety profile rather than predicted efficacy. Flecainide is recommended for prevention of AF recurrence in patients without structural heart disease however predictors of treatment success are insufficiently studied.