Risk Stratification Process Research Articles

Reevaluating heart failure risk: integrating echocardiography with unconventional holter ECG parameters

Abstract Background Chronic heart failure (CHF) constitutes a multifaceted clinical syndrome arising from structural or functional abnormalities within the myocardium. Echocardiography serves as an indispensable diagnostic modality for identifying cardiac anomalies, facilitating comprehensive evaluation of disease severity, and informing therapeutic strategies. Additionally, Holter electrocardiography (ECG) offers a robust technique for the analysis of heart rate variability (HRV), thereby elucidating the autonomic nervous system's impact on cardiac function. Purpose Our research undertook a comparative analysis of echocardiographic parameters and HRV metrics derived from 24-hour Holter ECG, incorporating non-traditional measures such as acceleration capacity, deceleration capacity, and the triangular index. The objective was to ascertain whether a diminished triangular index or alterations in acceleration and deceleration capacities, in contrast to conventional HRV parameters, are associated with an elevated risk of cardiovascular mortality. Methods We enrolled 140 consecutive patients diagnosed with CHF, all of whom exhibited a left ventricular ejection fraction below 50%. Each participant underwent thorough echocardiographic examination alongside 24-hour Holter ECG monitoring. Results Our analysis of the correlation between the E/A ratio and HRV parameters identified significant associations with the Triangular Index (Spearman’s ρ = −0.233, p = 0.037), acceleration capacity (Spearman’s ρ = 0.226, p = 0.044), and deceleration capacity (Spearman’s ρ = −0.381, p < 0.001). These HRV parameters also demonstrated statistically significant relationships with the E/E' ratio: Triangular Index (Spearman’s ρ = −0.241, p = 0.031) and deceleration capacity (Spearman’s ρ = −0.230, p = 0.033), as well as with the E/E' septal ratio. Moreover, the mitral valve deceleration time showed notable associations with the Triangular Index (Spearman’s ρ = 0.251, p = 0.025), acceleration capacity (Spearman’s ρ = −0.293, p = 0.008), and deceleration capacity (Spearman’s ρ = 0.309, p = 0.005). A positive correlation was observed between estimated pulmonary artery systolic pressure and deceleration capacity. In contrast, no statistically significant relationships were found between the commonly used HRV parameters (SDNN, SDANN, and SDNN index) and echocardiographic parameters. Conclusions Less commonly utilized Holter ECG parameters, such as acceleration and deceleration capacity, along with the triangular index, demonstrated significant diagnostic efficacy, especially in scenarios where traditional HRV parameters remained within normal ranges. These findings underscore the importance of integrating non-traditional HRV metrics into the risk stratification processes for CHF patients. To substantiate their long-term prognostic value, further extensive multicenter studies are warranted.

Genotype-phenotype correlations in patients with titin variants and cardiomyopathy from a Swiss cohort

Abstract Background Alterations in titin (TTN) are mostly described with dilated cardiomyopathy (DCM). Few studies identified TTN variants in arrhythmogenic cardiomyopathy (ACM), but the overlap of dilated and arrhythmogenic phenotypes in TTN variants is scarcely studied. Most pathogenic TTN variants are located on the A-band, but there is few knowledge about the phenotypic presentation of I-band and Z-disc (non-A-band) variants. Purpose The aim of this study is to characterize and investigate the outcome of patients with cardiomyopathy and pathogenic (P) or likely pathogenic (LP) TTN variants with a particular focus on the cardiomyopathy phenotype (DCM vs. ACM) at initial presentation and follow-up. Further, we studied the association of the TTN variant (A-band vs. non-A-band regions) and a unique phenotype. Methods This is a retrospective multicenter study from a Swiss cohort including 34 patients with P/LP TTN variants and cardiomyopathy. The variables of the secured anonymized database include patient characteristics, genetic, ECG, echocardiographic, and cardiac magnetic resonance (CMR) data. Ventricular arrhythmia (VA) events were divided into non-sustained ventricular tachycardia (nsVT), sustained ventricular tachycardia (sVT) and sudden cardiac arrest (SCA +/- ventricular fibrillation). Results Of 34 included patients, 68% were male. Median age at presentation was 43.5 years. 29 (85%) patients presented with DCM, 7 (21%) left dominant ACM (2020 Padua criteria) and none ARVC (2010 ARVC Task Force criteria). At median follow-up of 48.5 months, 17 (50%) patients had VA events (15 nsVT, 5 sVT and 3 SCA events). VA events significantly increased over time (p=0.008) and were not associated with gender or left ventricular ejection fraction (LVEF) <35%. Under optimal guideline-directed medical therapy (GDMT) mean LVEF and right ventricular function increased significantly (LVEF: 28.3±14.4% vs. 41.9±9.8% and right ventricular fractional area change (RV FAC): 24.7±7.5% vs. 35.8±4.8%, p<0.05). Late gadolinium enhancement (LGE) on CMR was commonest in the basal septum, but no patient had higher degree atrioventricular block (AVB) at baseline and follow-up. At last follow-up, 8 (24%) patients fulfilled ACM and 13 (38%) DCM criteria (Figure 1). Most TTN variants were located on the A-band (21, 62%), 10 (29%) on the non-A-band regions. Latter had higher rates of sVT (log-rank p=0.041) during follow-up (Figure 2). 20 (59%) had LP and 11 (32%) P variants. P variant carriers were younger at disease presentation compared to LP variant carriers. Conclusion Patients with TTN variants frequently present as DCM, whereas presentation as left dominant ACM is less common. TTN does not seem to be a classical ARVC causing gene. Despite favourable biventricular remodelling under GDMT, ventricular arrhythmic events increase during follow-up. I-band and Z-disk variants are associated with a higher risk of sVT, which may help in the risk stratification process.

Influence of TP53 gene mutations and their allelic status in myelodysplastic syndromes with isolated 5q deletion

AbstractMutations in the TP53 gene, particularly multihit alterations, have been associated with unfavorable clinical features and prognosis in patients diagnosed with myelodysplastic syndrome (MDS). Despite this, the role of TP53 gene aberrations in MDS with isolated deletion of chromosome 5 [MDS-del(5q)] remains unclear. This study aimed to assess the impact of TP53 gene mutations and their allelic state in patients with MDS-del(5q). To that end, a comprehensive analysis of TP53 abnormalities, examining both TP53 mutations and allelic imbalances, in 682 patients diagnosed with MDS-del(5q) was conducted. Twenty-four percent of TP53-mutated patients exhibited multihit alterations, whereas the remaining patients displayed monoallelic mutations. TP53-multihit alterations were predictive of an increased risk of leukemic transformation. The impact of monoallelic alterations was dependent on the variant allele frequency (VAF); patients with TP53-monoallelic mutations and VAF <20% exhibited behavior similar to TP53 wild type, and those with TP53-monoallelic mutations and VAF ≥20% presented outcomes equivalent to TP53-multihit patients. This study underscores the importance of considering TP53 allelic state and VAF in the risk stratification and treatment decision-making process for patients with MDS-del(5q).

Anaesthetic and perioperative considerations for extrapleural pneumonectomy and extended pleurectomy/decortication: a scoping review protocol

IntroductionExtrapleural pneumonectomy (EPP) and extended pleurectomy/decortication (ePD) are surgical cytoreductive techniques aimed at achieving macroscopic resection in malignant pleural tumours such as pleural mesothelioma, non-mesothelioma pleural malignancies such as thymoma...

Machine Learning-Based Algorithms for Enhanced Prediction of Local Recurrence and Metastasis in Low Rectal Adenocarcinoma Using Imaging, Surgical, and Pathological Data.

(1) Background: Numerous variables could influence the risk of rectal cancer recurrence or metastasis, and machine learning (ML)-based algorithms can help us refine the risk stratification process of these patients and choose the best therapeutic approach. The aim of this study was to assess the predictive performance of 4 ML-based models for the prediction of local recurrence or distant metastasis in patients with locally advanced low rectal adenocarcinomas who underwent neoadjuvant chemoradiotherapy and surgical treatment; (2) Methods: Patients who were admitted at the first Oncologic Surgical Clinic from the Regional Institute of Oncology, Iasi, Romania were retrospectively included in this study between November 2019 and July 2023. Decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF) were used to analyze imagistic, surgical, and pathological data retrieved from the medical files, and their predictive performance was assessed; (3) Results: The best predictive performance was achieved by RF when used to predict disease recurrence (accuracy: 90.85%) or distant metastasis (accuracy: 89.63%). RF was closely followed by SVM (accuracy for recurrence 87.8%; accuracy for metastasis: 87.2%) in terms of predictive performance. NB and DT achieved moderate predictive power for the evaluated outcomes; (4) Conclusions: Complex algorithms such as RF and SVM could be useful for improving the prediction of adverse oncological outcomes in patients with low rectal adenocarcinoma.

Gastrointestinal bleeding following Heartmate 3 left ventricular assist device implantation: The Michigan Bleeding Risk Model

BackgroundGastrointestinal bleeding (GIB) results in frequent hospitalizations and impairs quality of life in durable left ventricular assist device (LVAD) recipients. Anticipation of these events before implantation could have important implications for patient selection and management. MethodsThe study population included all adult HeartMate 3 (HM3) primary LVAD recipients enrolled in the STS-Intermacs registry from January 2017-December 2020. Using multivariable modeling methodologies, we investigated the relationships between preimplantation characteristics and postimplant bleeding, bleeding and death, and additional bleeding episodes on subsequent bleeding episodes, and created a risk score to predict the likelihood of post-LVAD GIB based solely on pre-implantation factors. ResultsOf 6425 patients who received a HM3 LVAD, 1010 (15.7%) patients experienced GIB. Thirteen pre-implantation factors were independent predictors of post-LVAD GIB. A risk score was created from these factors and calculated for each patient. By 3-years postimplant, GIB occurred in 11%, 26%,and 43% of low-, medium- and high-risk patients. Experiencing one post-LVAD GIB event was associated with an increased risk for further GIB events, with 33.9% of patients experiencing at least one recurrence. While post-LVAD GIB was associated with mortality, there was no relationship between number of GIB events and death. ConclusionThe Michigan Bleeding Risk Model is a simple tool which facilitates the prediction of post-LVAD GIB in HM3 recipients, by using 13 pre-implant variables. The implementation of this tool may help in the risk stratification process and may have therapeutic and clinical implications in HM3 LVAD recipients.

Characterizing patients ineligible for mitral valve intervention: Phenotypic clustering sub-analysis from the CHOICE-MI Registry

Abstract Background/Introduction Transcatheter mitral valve replacement (TMVR) is emerging as a therapeutic option for surgcal high-risk patients with mitral regurgitation (MR). However, a large proportion of these patients are still rejected due to clinical or anatomical reasons. The majority of these patients remain ineligible for any mitral valve (MV) intervention and continue medical treatment. Phenotypic characterization of these patients may assist in the identification of the anatomical challenges and drive future innovation efforts as well as assist in the risk stratification process of these patients. Purpose To characterize patients ineligible for TMVR and other MV interventions from a large international registry using an unsupervised phenotypic clustering approach integrating clinical, echocardiographic and computed tomography data to unveil differences between phenogroups. Methods Between 2014 and 2022, the CHOICE-MI registry included 984 patients undergoing screening for TMVR at 33 international sites. For this study, only patients with screening failure resulting in medical therapy alone were included. Patients receiving transcatheter or surgical treatment were excluded (Figure 1). A cluster analysis using K-means algorithm was performed on baseline clinical and imaging variables, and predictors of all-cause mortality within these clusters were assessed. Results Among 284 patients (77.4±8.82 years, 56.0% female, EuroSCORE II 6.6±5.8%) considered ineligible for any MV intervention, two clinically distinct phenogroups (PG) were identified using unsupervised hierarchical clustering of principal components (Figure 2): (PG1) Elderly women with primary MR, high left ventricular (LV) ejection fraction, and annular calcification (N=173, 60.9%); (PG2) Patients with secondary or mixed MR, LV and annular dilation, and high prevalence of comorbidities (N=111, 39.1%). There were no differences regarding Kaplan-Meier estimated 1-year all-cause mortality (PG1 vs. PG2, 21.4% vs. 23.4%, p=0.89) and 1-year cardiovascular mortality (10.4% vs. 13.5%, p=0.53). Predictors of mortality were albumin, renal function, extracardiac arteriopathy for PG1, and albumin, coronary artery disease, and prior myocardial infarction for PG2. Conclusions Using cluster analysis, this study identified two major subgroups among patients ineligible for mitral interventions with profound differences in clinical and anatomical profiles, and predictors of outcome. The combination of elderly women with primary MR, preserved LV ejection fraction and annular calcification was the most common phenogroup among patients rejected for mitral intervention. Identifying these factors may drive technological evolution to address unmet clinical and technical needs.

Clinical phenotype classification to predict risk and optimize the management of patients with atrial fibrillation using the Atrial Fibrillation Better Care (ABC) pathway: a report from the COOL-AF registry.

Phenotypic classification is a method of grouping patients with similar phenotypes. We aimed to use phenotype classification based on a clustering process for risk stratification of patients with non-valvular atrial fibrillation (AF) and second, to assess the benefit of the Atrial Fibrillation Better Care (ABC) pathway. Patients with AF were prospectively enrolled from 27 hospitals in Thailand from 2014 to 2017, and followed up every 6 months for 3 years. Cluster analysis was performed from 46 variables using the hierarchical clustering using the Ward minimum variance method. Outcomes were a composite of all-cause death, ischemic stroke/systemic embolism, acute myocardial infarction and heart failure. A total of 3405 patients were enrolled (mean age 67.8 ± 11.3 years, 58.2% male). During the mean follow-up of 31.8 ± 8.7 months. Three clusters were identified: Cluster 1 had the highest risk followed by Cluster 3 and Cluster 2 with a hazard ratio (HR) and 95% confidence interval (CI) of composite outcomes of 2.78 (2.25, 3.43), P < 0.001 for Cluster 1 and 1.99 (1.63, 2.42), P < 0.001 for Cluster 3 compared with Cluster 2. Management according to the ABC pathway was associated with reductions in adverse clinical outcomes especially those who belonged to Clusters 1 and 3 with HR and 95%CI of the composite outcome of 0.54 (0.40, 073), P < 0.001 for Cluster 1 and 0.49 (0.38, 0.63), P < 0.001 for Cluster 3. Phenotypic classification helps in risk stratification and prognostication. Compliance with the ABC pathway was associated with improved clinical outcomes.

Employing machine learning to predict adverse acute post-surgical outcomes following elective ulnar collateral ligament reconstruction

Background: Ulnar collateral ligament reconstruction ameliorates valgus elbow instability in various patient populations, including overhead athletes, patients with acute UCL rupture following high energy trauma, and those with chronic, subclinical elbow laxity. This study aims to explore machine learning algorithms to identify risk factors in patients undergoing elective UCL reconstruction in the ambulatory setting to predict postoperative outcomes. Methods: RStudio was used to create a filtering code to identify adult patients who underwent elective UCL reconstruction from 2008 to 2018 in the American college of surgeons national surgical quality improvement program database. Patients were analyzed using six ML algorithms, which were trained to predict outcomes such as extended length of stay, non-home discharge, and adverse events based on various patient characteristics and surgical variables. Algorithmic performance was then assessed and top performing algorithms underwent further analysis to determine relative feature importance using a permutation feature importance method. Results: ML exhibited excellent performance in predicting LOS, with an average AUC of 0.953, similar to that of logistic regression. Regarding NHD, ML demonstrated a 60.8% increase in AUC compared to LR. In predicting AAE, ML achieved an average AUC that was 12.7% higher than LR. Conclusions: The highly predictive capability of ML indicates the possibility to represent a procedure-specific complementary tool for the preoperative risk stratification process. This study provides a comprehensive analysis of UCL reconstruction in the management and outcomes of any patient, regardless of age or activity level.

Recent advances in the treatment of complex congenital diaphragmatic hernia-a narrative review.

Congenital diaphragmatic hernia (CDH) is an anomaly of the cardiopulmonary system maturation process that results from both a global embryopathy and concomitant mechanical compression of the cardiopulmonary system from the abdominal contents during fetal maturation. This results in pulmonary hypertension, pulmonary hypoplasia, and cardiac dysfunction, requiring intense critical care management. The patients with highest risk CDH are the most challenging, resource-intensive, and bear most of the mortality. Advances at the basic, translational, and clinical research levels are leading to novel therapies and management strategies for complex, high-risk CDH. Our objective is to review novel approaches in thinking and management for the most complex and high-risk CDH patients. These include patients with prenatal and postnatal indicators of high-risk defects, those receiving extracorporeal life support (ECLS), and those with concomitant anomalies such as complex cardiac and/or chromosomal abnormalities. PubMed was searched in late 2022 and early 2023 to identify relevant evidence. Search terms included congenital diaphragmatic hernia (CDH)", "extracorporeal life support (ECLS)", "pulmonary hypertension", "dual-hit hypothesis", "risk reduction", "cardiac/chromosomal anomalies", and "novel therapies". We included trials, multicenter studies (prospective and retrospective), single-center reports, and review articles/expert opinion. CDH is a congenital anomaly of the cardiopulmonary and diaphragmatic systems that represents a spectrum of disease. High-risk or complex patients are defined by prenatal/postnatal risk stratification, receipt of ECLS, and/or having concomitant anomalies, representing the severe end of that spectrum. Overall survival of high-risk CDH is about 50% and comprises the vast majority of mortality, mandating special emphasis. The development of risk-stratification processes, best practices or guidelines of management, and novel therapies is critical to optimize the care of these infants. CDH patients with high-risk disease remain a challenging subset of CDH patients. Increasing opportunities for survival are being realized with novel, investigational approaches.

Effect of an oncology care management program on unplanned hospital admissions in a commercially insured population.

1547 Background: Despite advances in cancer outcomes, costs of cancer care continue to rise. Acute care utilization contributes significantly to these costs. The Cancer Support Program’s (CSP) care management services focus on providing education on symptom management, palliative care and advance care planning, addressing psychosocial needs and closing gaps in care in members with cancer who are at high risk for unplanned hospital admissions (UHA). Methods: Beginning 1/1/22, commercially insured members with an active cancer diagnosis were clinically stratified as high or low risk for UHA. All high-risk members were invited to participate in the CSP program. Individuals who agreed to participate received individualized telephonic care management support. Medical claims from 1/1/22 through 9/30/22 were evaluated, and rates of UHA were compared between participants and non-participants within the identified high-risk population for an average period of 4 months after identification (the period equivalent to the average enrollment period of participants). Results: The study population included 3,113 members who stratified as high risk. Of those, 36% were enrolled in the program. Reasons for non-enrollment include inability to reach (72%), member refused (27%) and bad contact information (1%). There were no statistically significant differences between the two groups’ demographic composition except for age (the enrolled group had slightly more in the 51-64 age group [63% vs. 59%; p &lt; 0.001] and slightly fewer in the &gt; 65 age group (9% vs. 15%; p &lt; 0.001]). There were 358 UHA in the participating group and 737 UHA in the non-participating group. When normalized, there were 1,179 UHA per thousand members per year (PTMPY), 99% CI [1,171 UHA, 1,184 UHA] (bootstrap) in the participating group and 1,526 UHA PTMPY, 99% CI [1,523 UHA, 1,535 UHA] (bootstrap) in the non-participating group. Conclusions: Early results show lower UHA rates for members who participated in the care management program, suggesting the program is effective in reducing acute care utilization within the high-risk population. Limitations of this study include potential enrollment bias, changes in risk status from clinical or social factors, and the potential for human error or inconsistency in the risk stratification process. Further study is underway to validate these results.

P17 MITRAL ANNULUS CALCIFICATION IN TRANSCATHETER AORTIC VALVE IMPLANTS

Abstract Background Mitral annular calcium (MAC) is a common finding in patients undergoing transcatheter aortic valve implantation (TAVI). However, assessment of MAC in the pre–TAVI diagnostic pathway is not among the procedures routinely performed. Aim of the study In this retrospective study conducted in patients undergoing TAVI, we evaluated (1) the presence and extent of MAC using a multimodal imaging approach; (2) the clinical and structural factors associated with it; and (3) the possible prognostic role of MAC. Methods Between 2016 and 2022, 62 patients with severe aortic stenosis underwent TAVI at the Cardiovascular Department of A.O.U. Careggi (Florence, Italy). Baseline and post–TAVI clinical and echocardiographic data were collected at Santo Stefano Hospital (Prato, Italy). MAC assessment was performed by quantitative analysis on echocardiographic and computed tomography (CT) images, obtaining a MAC severity score. A clinical follow–up was conducted at 30–day intervals in all patients. Results MAC was detected in 48 patients (77%), a severe MAC in 16 patients (26%). CT analysis was more accurate in defining the presence and extent of MAC. Patients with MAC were more female, older in age, with greater cardiovascular risk profile and comorbidities; they presented more frequently mitral valvulopathy and arrhythmias. These differences were amplified by stratifying the population according to MAC severity score. Patients with severe MAC had a pattern of ventricular remodeling with predominantly concentric hypertrophy. Post–TAVI, patients with severe MAC had less hemodynamic benefit and a greater need for pacemaker implantation. A trend of increasing all–cause mortality as MAC score increased was noted. Conclusions Assessment of mitral annular calcium and its extension should become an integral part of the patient‘s pre–TAVI risk stratification process. A phenotypic pattern of concentric left ventricular hypertrophy, mainly associated with patients with severe MAC, identifies a category with lower post procedural recovery.

Prognostic value of modified-Gustave-Roussy Immunity Score in resectable proximal gastric cancer.

The prognostic evaluation of GRIm score has been confirmed in many tumor species. The purpose of this study is to clarify the value of GRIm score in the prognostic evaluation of patients with resectable proximal gastric cancer. A single center retrospective study was conducted in 174 patients with proximal gastric cancer who underwent radical total gastrectomy. An in-depth analysis was carried out to explore the prognostic differences between high and low GRIm, and the influencing factors of disease-free survival rates and overall survival rates were analyzed by Cox regression model and Kaplan-Meier method. A total of 174 patients were divided into two groups: 135 patients were marked in L-mGRIm and 39 patients in H-mGRIm groups respectively. The median OS of the H-mGRIm and L-mGRIm groups were 23.2 and 38.6 months, respectively. The median DFS of the H-mGRIm and L-mGRIm groups was 16.9 and 31.7 months, respectively. Both DFS and OS were significantly different between groups (P = .000, P = .000). In multivariate analysis, ZPS (2 vs 0-1: HR 1.99 95% CI 1.05-3.76 P = .035), LDH (≥193 vs <193:HR 0.6; 95% CI 0.38-0.95 P = .028), mGRIm score (2-3 vs 0-1: HR 2.4; 95% CI 1.09-5.23 P = .029) was independent risk factors of OS. The age (>65 vs ≤65 years HR 0.63; 95% CI 0.4-0.95 P = .003), LDH (>193 U/L vs ≤193 U/L: HR 0.55; 95% CI 0.37-0.82 P = .004) and mGRIm score (2-3 vs 0-1: HR 4.74; 95% CI 2.24-9.9 P = .000) as an independent risk factor for DFS. mGRIm score is a novel, simple and effective index for prognosis evaluation of resectable cardiac cancer and can be used as a part of the risk stratification process.

Comparative Overview of Different Radiological Imaging Techniques in the Diagnosis of Pulmonary Embolism

Background: Imaging techniques such as chest X-ray (CXR), computed tomography pulmonary angiography (CTPA), ventilation-perfusion (V/Q) scintigraphy, and magnetic resonance imaging (MRI) are some methods used to detect and manage acute pulmonary embolism (PE). The aim of this review was a comparative analysis of the various imaging techniques used to evaluate PE. Methods and Results: The incidence, distribution, clinical features, classification of PE and clinical assessment of the current methods for diagnosis of PE were discussed. CTPA is the gold standard for fast turnaround and accurate diagnosis. Additional probable reasons for sudden chest pain can also be learned through a CT scan. Lung perfusion anomalies can be identified and measured using dual-energy CT. Chest radiographs are only marginally beneficial, occasionally revealing PE or infarction signs, but are helpful in ruling out other possible causes of chest pain. These patients' ventilation-perfusion mismatches are evident in the V/Q scan, which has many grading schemes with conventional ranges from normal to high. While MRI, which is only available in specialist facilities and calls for higher degrees of competence, also offers accurate diagnosis. Conclusion: Early diagnosis and treatment of PE is challenging due to asymptomatic conditions or overlapping symptoms. Diagnosis of PE in expectant mothers and those with suspected PE recurrence is typically difficult. Over-diagnosis and overtreatment, particularly regarding sub-segmental PE, and the lowered clinical suspicion threshold remain a major concern in PE diagnosis. The routine use and integration of the above diagnostic techniques need to be encouraged in clinical practice to overcome the diagnostic hurdles. The introduction of new diagnostic techniques or improved risk stratification processes might enhance the management of PE.

Machine Learning Approaches for the Prediction of Hepatitis B and C Seropositivity.

(1) Background: The identification of patients at risk for hepatitis B and C viral infection is a challenge for the clinicians and public health specialists. The aim of this study was to evaluate and compare the predictive performances of four machine learning-based models for the prediction of HBV and HCV status. (2) Methods: This prospective cohort screening study evaluated adults from the North-Eastern and South-Eastern regions of Romania between January 2022 and November 2022 who underwent viral hepatitis screening in their family physician's offices. The patients' clinical characteristics were extracted from a structured survey and were included in four machine learning-based models: support vector machine (SVM), random forest (RF), naïve Bayes (NB), and K nearest neighbors (KNN), and their predictive performance was assessed. (3) Results: All evaluated models performed better when used to predict HCV status. The highest predictive performance was achieved by KNN algorithm (accuracy: 98.1%), followed by SVM and RF with equal accuracies (97.6%) and NB (95.7%). The predictive performance of these models was modest for HBV status, with accuracies ranging from 78.2% to 97.6%. (4) Conclusions: The machine learning-based models could be useful tools for HCV infection prediction and for the risk stratification process of adult patients who undergo a viral hepatitis screening program.

A retrospective observational study to evaluate the reliability of staging and risk stratification of adolescent and adult patients with Hodgkin’s lymphoma registered at the lymphoma clinic of a tertiary cancer center in Western India

ABSTRACT Export Background: The treatment for Hodgkin’s lymphoma is based on risk stratification of the disease, which is determined by staging, clinical, and laboratory parameters. The current staging systems are highly prone to error due to overlapping components and inter-observer variability. Objectives: We aimed to assess the reliability of staging and risk stratification performed by the clinicians at our busy multidisciplinary clinic. Materials and Methods: We conducted a retrospective analysis of 115 patients with newly diagnosed Hodgkin’s lymphoma at the Tata Memorial Hospital, Mumbai, India, from 2016-2018. Patients who underwent baseline staging and risk stratification in the multidisciplinary lymphoma clinic were included in the analysis. The multidisciplinary lymphoma clinic is a collaboration between medical oncologists, radiation oncologists, nurses, social workers, and patient navigators. The staging and risk stratification performed during the multidisciplinary clinic were compared with those of a team of independent experts from medical oncology, radiation oncology, and nuclear medicine based on standard references (guidelines established by the German Hodgkin Study Group and the Ann Arbor Staging). Results: Discordance rates of 11.3% (n = 13) in disease staging and 7.8% (n = 9) in risk stratification were observed between the multidisciplinary clinic and the independent expert team. In all the discordant cases, there was up-staging of patients by the multidisciplinary clinic; all nine patients in early favorable risk category were misclassified as early unfavorable. The discordance rates were not significant, with a kappa score of 0.841 for staging and 0.855 for risk stratification. Conclusion: Misclassification of patients with Hodgkin’s lymphoma based on the staging, and risk stratification may lead to over- or under-treatment. There is a need for a simpler, objective, and technology-driven risk stratification process.

Snapshot of suspected acute coronary syndrome assessment processes in the emergency department: A national cross-sectional survey.

The Snapshot of Suspected ACS Assessment (SSAASY) study aims to describe the assessment processes for patients with suspected acute coronary syndrome (ACS) in Australian EDs, and to compare these processes with the National Heart Foundation of Australia and Cardiac Society of Australia and New Zealand (NHFA/CSANZ) guidelines. Between March and May 2021, a cross-sectional survey of Australian EDs was undertaken to investigate the assessment strategies used within the ED. All public and private hospitals identified as having dedicated EDs were invited to participate. Respondents provided data on hospital, ED and cardiac service characteristics. They also provided data on the risk stratification process recommended within their department (risk scores, troponin testing, objective testing for coronary artery disease). Awareness of the NHFA/CSANZ guidelines was assessed. Responses were received from 109/162 departments (67%). Most sites (n=100, 92%) reported using dedicated protocols developed by ED clinicians that included risk stratification scores. Highly sensitive troponin assays were used at 103 (94%) sites. Serial troponin testing was performed over 2h for low-risk patients in 53 (49%) sites and 2-3h for intermediate and high-risk patients in 74 (68%) sites. Further investigations included exercise stress tests (48%) and stress echocardiography (38%), with 45% of sites ordering outpatient investigations. The SSAASY study reported the strategies used to assess suspected ACS. In line with current NHFA/CSANZ guidelines, highly sensitive troponin assays are widely utilised. However, serial sampling intervals were longer than guideline recommendations, suggesting a translational gap between guidelines and clinical practice.

Individual and Community-Level Characteristics and Adherence to Specialty Medications

Background: Understanding risk factors for nonadherence can help specialty pharmacies optimize resources to prevent nonadherence and inform risk-stratification processes. Objective: To determine which individual and community-level characteristics are associated with nonadherence to specialty medications. Methods: We analyzed a cohort of patients enrolled in a prospective randomized controlled trial having filled a specialty medication at least 4 times in the previous 12 months with a proportion of days (PDC) covered < 0.90. We collected patient age, gender, race, medication administration type, therapy start date, home address, insurance type, and online patient portal status from the electronic health record. An ordinal logistic regression model was used to assess the association of nonadherence with individual and community-level patient characteristics. Results: Most patients were female (68%), white (82%), and held commercial insurance (58%) with a median age of 53 (interquartile range [IQR] 40, 64) years. Patients were mostly from the adult rheumatology (35%), multiple sclerosis (20%) and lipid (17%) clinics. Given a 10-year increase in age, patients had lower odds of having lower PDC (odds ratio [OR] = 0.82, 95% confidence interval [CI] = 0.71-0.94, P = 0.005). Patients on therapy greater than or equal to 1 year had half the odds of having lower PDC relative to patients on therapy less than 1 year (OR = 0.52, CI = 0.35 – 0.75, P < 0.001). No statistically significant associations were found between PDC and gender, race, insurance type, route of administration, clinic type, patient portal status, median income, percent receiving government assistance, or percent with no health insurance. Conclusion: Patients with younger age and shorter duration on treatment may be at-risk for lower adherence. Specialty pharmacies may benefit from targeting adherence interventions to these groups.

P003: A retrospective study to evaluate the reliability of staging and risk stratification of adolescent and adult patients with Hodgkin’s lymphoma registered in the lymphoma clinic at Tata Memorial Centre.

Table 1: Baseline characteristics Purpose: Risk stratification is a key factor,which depends on staging, clinical and laboratory parameters in determining the treatment in Hodgkin’s lymphoma (HL). However, this is highly prone to erroneous results due to overlapping components in the staging systems and inter-observer variability.We conducted this study to assess the reliability of risk stratification performed by our clinicians at our busy multidisciplinary clinic (MDC). Methods: A retrospective analysisof newly diagnosed HL patients from the multidisciplinary clinic database for the year 2016-18was conducted.All patients underwent an 18-FDG PET/CT scan and other evaluations as per our institutional checklist. The reliability of staging and risk stratification done during the MDC was compared with a team of independent experts (medical oncology, radiation oncology and nuclear medicine) based on a standard reference. The concordance testing was done using kappa statistic for agreement (≥ 0.8 as perfect agreement) andP <0.05 was considered significant. Results: 120 patients were analyzed, and the baseline characteristics are described in Table 1. The patients initially underwent staging by MDC and were risk stratified into early favorable (16 patients [13.5%]), early unfavorable (29 patients [24%]) and advanced (75 patients [62.5%]). A discordance rate of 10% (12 patients) was observed in disease staging and 8.3% in risk stratification (10 patients) between the MDC and the expert team. All deviations were due to up-staging of patients by MDC, of which 9 patients in early favorable were misclassified as early unfavorable and 1 patient as advanced from early unfavorable. This resulted in 10 patients receiving higher dose of chemotherapy and radiation. However, no patients were under treated. On completion of treatment, 82%of patientshadcomplete response, 12%had partial responseand 5%had disease progression. Our results show that the discordance rates were not significantbetween the independent reviewers and MDC team with kappa score of 0.859 for stagingand 0.847 for risk stratification. Conclusion: Despite our busy setting, the risk stratification was found to be reliable and comparable to reference standards. One reason for this would be the involvement of a multidisciplinary team in our lymphoma clinic. Yet, 8% of the patients received a more intense therapy than needed, demonstrating the need for a simpler, objective and technology driven risk stratification process.

Patient-rated satisfaction and improvement following hip and knee replacements: Development of prediction models.

Effective preoperative assessments of determinants of health status and function may improve postoperative outcomes. We developed risk scores of preoperative patient factors and patient-reported outcome measures (PROMs) as predictors of patient-rated satisfaction and improvement following hip and knee replacements. Prospectively collected National Health Service and independent sector patient data (n = 30,457), including patients' self-reported demographics, comorbidities, PROMs (Oxford Hip/Knee score (OHS/OKS)and European Quality of Life (EQ5D index and health-scale), were analysed. Outcomes were defined as patient-reported satisfaction and improvement following surgery at 7-month follow-up. Univariable and multivariable-adjusted logistic regressions were undertaken to build prediction models; model discrimination was evaluated with the concordance index (c-index) and nomograms were developed to allow the estimation of probabilities. Of the 14,651 subjects with responses for satisfaction following hip replacements 564 (3.8%) reported dissatisfaction, and 1433 (9.2%) of the 15,560 following knee replacement reported dissatisfaction. A total of 14,662 had responses for perceived improvement following hip replacement (lack of improvement in 391; 2.7%) and 15,588 following knee replacement (lack of improvements in 1092; 7.0%). Patients reporting poor outcomes had worse preoperative PROMs. Several factors, including age, gender, patient comorbiditiesand EQ5D, were included in the final prediction models: C-indices of these models were 0.613 and 0.618 for dissatisfaction and lack of improvement, respectively, for hip replacementand 0.614 and 0.598, respectively, for knee replacement. Using easily accessible preoperative patient factors, including PROMs, we developed models which may help predict dissatisfaction and lack of improvement following hip and knee replacements and facilitate risk stratification and decision-making processes.