Optimal patient selection for maze procedure in patients undergoing mitral valve disease.

OBJECTIVES: Although risk factors for unsuccessful Maze procedure have been demonstrated, an appropriate patient selection is still controversial. In our institute, Maze procedure is indicated for those whom normal sinus rhythm (NSR) was reestablished by intraoperative direct cardioversion (DC) after ventricular unloading by total cardiopulmonary bypass. The purpose of this study was to evaluate the effectiveness of our indication criteria for Maze procedure in patients with mitral valve disease. METHODS: Between October 2012 and October 2021, MAZE was indicated in 55 patients in whom normal sinus rhythm (NSR) was reestablished by intraoperative direct current cardioversion (DC). Three endpoints and predictors were examined: disappearance of atrial fibrillation (AF), NSR, and A-wave detection. RESULTS: Restoration of NSR by intraoperative DC was confirmed in 43 patients, and these patients underwent MAZE. AF disappeared in 39 patients (90.7%), and F-wave ≥ 0.1 mV was a significant predictive factor (odds ratio (OR) 20.99, 95% CI 1.22-1079.06). NSR was reestablished in 36 patients (83.7%), and F-wave ≥ 0.1 mV (odds ratio 15.62, 95% CI 1.62-359.86) + AF history ≤ 3 years (OR 8.30, 95% CI 1.09-177.04) were significant predictors. A-wave detection was confirmed in 26 patients (60.5%), and left atrial diameter ≤ 55 mm was a significant predictor (OR 5.22, 95% CI 1.28-24.79). CONCLUSIONS: Intraoperative DC after ventricular unloading resulted effective patient selection for concomitant Maze procedure. F-wave and AF history were predictive factor of electrical restoration of AF, and left atrial diameter was predictive factor of restoration of atrial function.

Should Children Be Included in Human Challenge Studies?

Human challenge studies, in which human research subjects are intentionally exposed to pathogens to contribute to scientific knowledge, raise many ethical complexities. One controversial question is whether it is ethically permissible to include children as participants. Commentary of the past decades endorses the exclusion of children, while new guidance suggests that pediatric human challenge studies can be ethically permissible. This paper argues that neither children's exclusion nor their inclusion are well justified. I examine and reject three arguments for exclusion, but suggest that these arguments establish pediatric human challenge studies as a complex ethical category of research that requires caution. I then argue for a strong presumption against children's inclusion, by drawing on an analogy to children's inclusion in phase I trials, emphasizing a requirement of necessity, and suggesting that accommodating children's vulnerability promotes an age de-escalation approach for pediatric human challenge studies research. In the final section, I suggest a procedure for ethics review.

Single incision robotic myomectomy: selection criteria, learning curve and cost.

The article "Comparison of operative and fertility outcomes of single-incision robotic myomectomy: a retrospective single-center analysis of 286 cases" by Kim et al. compares the effectiveness of robotic single-port myomectomy against the traditional multiport approach. The study finds similar operating outcomes, complication rates, and pregnancy rates in expert hands for both methods. Our systematic review supports these findings, revealing no significant differences in operative time, blood loss, or complication rates. Recent meta-analysis further emphasizes the benefits of the single-port approach in reducing morcellation time, overall operative duration, and blood loss. Our letter seeks insights on patient selection criteria to minimize conversion rates between surgical approaches and inquiries on learning curve differences. Additionally, we seek cost analysis details for both techniques. We appreciate the authors' valuable contributions to this field.

Substrate Selection Criteria in Regulated Intramembrane Proteolysis.

Alzheimer's disease is the most common form of dementia encountered in an aging population. Characteristic amyloid deposits of Aß peptides in the brain are generated through cleavage of amyloid precursor protein (APP) by γ-secretase, an intramembrane protease. Cryo-EM structures of substrate γ-secretase complexes revealed details of the process, but how substrates are recognized and enter the catalytic site is still largely ignored. γ-Secretase cleaves a diverse range of substrate sequences without a common consensus sequence, but strikingly, single point mutations within the transmembrane domain (TMD) of specific substrates may greatly affect cleavage efficiencies. Previously, conformational flexibility was hypothesized to be the main criterion for substrate selection. Here we review the 3D structure and dynamics of several γ-secretase substrate TMDs and compare them with mutants shown to affect the cleavage efficiency. In addition, we present structural and dynamic data on ITGB1, a known nonsubstrate of γ-secretase. A comparison of biophysical details between these TMDs and changes generated by introducing crucial mutations allowed us to unravel common principles that differ between substrates and nonsubstrates. We identified three motifs in the investigated substrates: a highly flexible transmembrane domain, a destabilization of the cleavage region, and a basic signature at the end of the transmembrane helix. None of these appears to be exclusive. While conformational flexibility on its own may increase cleavage efficiency in well-known substrates like APP or Notch1, our data suggest that the three motifs seem to be rather variably combined to determine whether a transmembrane helix is efficiently recognized as a γ-secretase substrate.

Assessing the properties of patient-specific treatment effect estimates from causal forest algorithms under essential heterogeneity.

BACKGROUND: Treatment variation from observational data has been used to estimate patient-specific treatment effects. Causal Forest Algorithms (CFAs) developed for this task have unknown properties when treatment effect heterogeneity from unmeasured patient factors influences treatment choice - essential heterogeneity. METHODS: We simulated eleven populations with identical treatment effect distributions based on patient factors. The populations varied in the extent that treatment effect heterogeneity influenced treatment choice. We used the generalized random forest application (CFA-GRF) to estimate patient-specific treatment effects for each population. Average differences between true and estimated effects for patient subsets were evaluated. RESULTS: CFA-GRF performed well across the population when treatment effect heterogeneity did not influence treatment choice. Under essential heterogeneity, however, CFA-GRF yielded treatment effect estimates that reflected true treatment effects only for treated patients and were on average greater than true treatment effects for untreated patients. CONCLUSIONS: Patient-specific estimates produced by CFAs are sensitive to why patients in real-world practice make different treatment choices. Researchers using CFAs should develop conceptual frameworks of treatment choice prior to estimation to guide estimate interpretation ex post.

Enhancing site selection strategies in clinical trial recruitment using real-world data modeling.

Slow patient enrollment or failing to enroll the required number of patients is a disruptor of clinical trial timelines. To meet the planned trial recruitment, site selection strategies are used during clinical trial planning to identify research sites that are most likely to recruit a sufficiently high number of subjects within trial timelines. We developed a machine learning approach that outperforms baseline methods to rank research sites based on their expected recruitment in future studies. Indication level historical recruitment and real-world data are used in the machine learning approach to predict patient enrollment at site level. We define covariates based on published recruitment hypotheses and examine the effect of these covariates in predicting patient enrollment. We compare model performance of a linear and a non-linear machine learning model with common industry baselines that are constructed from historical recruitment data. Performance of the methodology is evaluated and reported for two disease indications, inflammatory bowel disease and multiple myeloma, both of which are actively being pursued in clinical development. We validate recruitment hypotheses by reviewing the covariates relationship with patient recruitment. For both indications, the non-linear model significantly outperforms the baselines and the linear model on the test set. In this paper, we present a machine learning approach to site selection that incorporates site-level recruitment and real-world patient data. The model ranks research sites by predicting the number of recruited patients and our results suggest that the model can improve site ranking compared to common industry baselines.

How can current oncological datasets be adjusted to support the automated patient recruitment in clinical trials?

OBJECTIVES: This study aims to identify necessary adjustments required in existing oncological datasets to effectively support automated patient recruitment. METHODS: We extracted and categorized the inclusion and exclusion criteria from 115 oncological trials registered on ClinicalTrials.gov in 2022. These criteria were then compared with the content of the oBDS (Oncological Base Dataset version 3.0), Germany's legally mandated oncological data standard. RESULTS: The analysis revealed that 42.9% of generalized inclusion and exclusion criteria are typically present as data fields in the oBDS. On average, 54.6% of all criteria per trial were covered. Notably, certain criteria such as comorbidities, pregnancy status, and laboratory values frequently appeared in trial protocols but were absent in the oBDS. CONCLUSION: The omission of criteria, notably comorbidities, within the oBDS restricts its functionality to support trial recruitment. Addressing this limitation would enhance its overall effectiveness. Furthermore, the implications of these findings extend beyond Germany, suggesting potential relevance and applicability to oncological datasets globally.

Is central venous catheter in haemodialysis still the main factor of mortality after hospitalization?

BACKGROUND: Haemodialysis is the most frequently prescribed Renal Replacement Therapy modality worldwide. However, patients undergoing this therapy have an unpredictable evolution related to vascular access. OBJECTIVE: To determine the factors associated with the mortality and hospitalization rate in haemodialysis patients at a third-level care Centre in the Dominican Republic. METHODS: This was an observational and prospective study involving a cohort of 192 haemodialysis patients. The patient selection was non-probabilistic for convenience, and a direct source questionnaire was applied. RESULTS: Of the 192 patients in the cohort, 103 (53.6%) were hospitalized and evaluated. The most frequent cause of hospitalization was catheter-related bloodstream infections (53.4%). Almost one-third (28.2%) of the hospitalized patients died, mostly due to infections (12.6%). Of those who died 29 patients (90%) had a Central venous catheter (CVC) with a non-tunnelled catheter (NTCVC) (65.5%); having an NTC CVC makes a patient 85.5 times more likely to be hospitalized than patients with arteriovenous fistulas. CONCLUSION: Vascular access plays a predominant role in the hospitalization and mortality rates in haemodialysis. Patients with an arteriovenous fistula obtained significantly better outcomes than those with central venous catheters.

Histological criteria for selecting patients who need clonality test for non-gastric MALT lymphoma diagnosis.

The histological diagnosis of extranodal marginal zone lymphoma of the mucosa-associated lymphoid tissue (MALT lymphoma) is difficult for pathologists. Recently, digital pathology systems have been widely used to provide tools that can objectively measure lesions on slides. In this study, we measured the extent of marginal zone expansion in suspected MALT lymphoma cases and compared the results with those of a molecular clonality test. In total, 115 patients who underwent an IGH gene rearrangement test for suspected MALT lymphoma were included in this study. All cases were histologically classified into three patterns; "small lymphoid aggregates with no germinal center (Pattern 1)," "lymphoid follicles with germinal center (Pattern 2)" and " fused marginal zone or diffuse small lymphocytic proliferation (Pattern 3)." The proportions of monoclonality in Pattern 1, 2, and 3 were 25.0%, 55.0%, and 97.9%, respectively. The ratios of marginal zone thickness to germinal center diameter and entire lymphoid follicle area to germinal center area were measured in Pattern 2 cases using a digital pathology system. Combining the width cutoff of 1.5 and the areal cutoff of 3.5, the sensitivity, specificity, positive predictive value, and negative predictive value for MALT lymphoma were 96.97%, 70.37%, 80.00%, and 95.00%, respectively. In conclusion, through objective measurement of the marginal zone, suspected cases of MALT lymphoma requiring a molecular clonality test can be effectively selected.

Functional Mitral Regurgitation: Patient Selection and Optimization.

Functional mitral regurgitation appears commonly among all heart failure phenotypes and can affect symptom burden and degree of maladaptive remodeling. Transcatheter mitral valve edge-to-edge repair therapies recently became an important part of the routine heart failure armamentarium for carefully selected and medically optimized candidates. Patient selection is considering heart failure staging, relevant comorbidities, as well as anatomic criteria. Indications and device platforms are currently expanding.

Fluidity of Equipoise in a Multi-Centred Pilot RCT: Influences on Clinician Decision-Making in Offering Trial Entry.

OBJECTIVES: The embedded Qualitative Process Evaluation (QPE) within the CSTICH- Pilot RCT explored facilitators and barriers to recruitment within the Pilot. This study reports a secondary analysis of the overarching theme of Fluidity of Equipoise and the influences on individual and community clinical equipoise around the use of Emergency Cervical Cerclage (ECC). STUDY DESIGN: RCT recruitment assumes clinical equipoise and is defined as genuine uncertainty about an intervention. The ability of trial recruiters to convey this equipoise is also key to participant recruitment and fully informed consent. This exploratory qualitative process evaluation used semi-structured interviews with healthcare professionals (HCPs) involved in trial recruitment. Interviews were audio-recorded, transcribed, and analysed using codebook thematic analysis. RESULTS: 23 HCPs were interviewed. Clinical equipoise around the use of ECC was variable and influenced by a multitude of factors including: (1) obstetric history; (2) gestation; (3) standard site practice, and (4) HCPs previous experiences of ECC. We have interpreted this variability as 'fluidity of equipoise'. CONCLUSIONS: Clinical equipoise around complex pregnancy related conditions was fluid and influenced by the complexities of obstetric histories and gestation at presentation. Equipoise of HCPs involved in trial recruitment should be considered carefully as it can impact the nuances of recruitment, particularly in more challenging trials such as CSTICH-2. Study-specific documents and training can be used to increase staff and patient awareness of uncertainty in the evidence base for interventions under investigation. Further research is needed around the potential consequences of equipoise fluidity.

Review article: Current indications and selection criteria for early liver transplantation in severe alcohol-associated hepatitis.

BACKGROUND: Alcohol-associated hepatitis (AH) is a severe inflammatory form of alcohol-associated liver disease (ALD) that carries a high mortality rate. Early liver transplantation for severe AH is increasingly available. However, specific criteria for referral and selection remain a subject of debate. AIMS: To provide a narrative review of the natural history, diagnostic criteria and indications for referral for early liver transplantation for severe AH. METHODS: We searched PubMed for articles published through August 2023. Key search terms were 'alcoholic hepatitis,' 'alcohol-associated hepatitis,' 'abstinence,' 'alcohol relapse,' and 'liver transplantation.' RESULTS: Previously, a six-month period of alcohol abstinence was required before patients with ALD were considered for liver transplantation. However, studies in recent years have demonstrated that, among carefully selected patients, patients who received early transplants have much higher survival rates than patients with similarly severe disease who did not undergo transplants (77% vs. 23%). Despite these successes, early liver transplantation remains controversial, as these patients have typically not undergone treatment for alcohol use disorder, with the ensuing risk of returning to alcohol use. CONCLUSIONS: While early liver transplantation for AH has survival benefits, many patients would not have received treatment for alcohol use disorder. An integrated approach to evaluating candidacy for early liver transplantation is needed.

The Registry-Based Randomized Trial - A Pragmatic Study Design.

Randomized controlled trials are the gold standard of clinical research for comparing therapies in well-defined groups of participants.1 Randomization avoids confounding due to unmeasured variables or to treatment selection and enables a causal interpretation of the estimated treatment effect. It has long been recognized, however, that standard explanatory clinical trials are slow, costly, and subject to participant selection. To preserve the strengths of randomized trials while mitigating their weaknesses, pragmatic randomized clinical trials emerged; these trials aim to facilitate decision-making rather than explicate a mechanism of action and enroll a diverse set of participants using existing structures and data sources.2.

Refining patient selection for next-generation immunotherapeutic early-phase clinical trials with a novel and externally validated prognostic nomogram.

Introduction: Identifying which patient may benefit from immunotherapeutic early-phase clinical trials is an unmet need in drug development. Among several proposed prognostic scores, none has been validated in patients receiving immunomodulating agents (IMAs)-based combinations. Patients and methods: We retrospectively collected data of 208 patients enrolled in early-phase clinical trials investigating IMAs at our Institution, correlating clinical and blood-based variables with overall survival (OS). A retrospective cohort of 50 patients treated with IMAs at Imperial College (Hammersmith Hospital, London, UK) was used for validation. Results: A total of 173 subjects were selected for analyses. Most frequent cancers included non-small cell lung cancer (26%), hepatocellular carcinoma (21.5%) and glioblastoma (13%). Multivariate analysis (MVA) revealed 3 factors to be independently associated with OS: line of treatment (second and third vs subsequent, HR 0.61, 95% CI 0.40-0.93, p 0.02), serum albumin as continuous variable (HR 0.57, 95% CI 0.36-0.91, p 0.02) and number of metastatic sites (<3 vs ≥3, HR 0.68, 95% CI 0.48-0.98, p 0.04). After splitting albumin value at the median (3.84 g/dL), a score system was capable of stratifying patients in 3 groups with significantly different OS (p<0.0001). Relationship with OS reproduced in the external cohort (p=0.008). Then, from these factors we built a nomogram. Conclusions: Prior treatment, serum albumin and number of metastatic sites are readily available prognostic traits in patients with advanced malignancies participating into immunotherapy early-phase trials. Combination of these factors can optimize patient selection at study enrollment, maximizing therapeutic intent.

Proton Therapy in Breast Cancer: A Review of Potential Approaches for Patient Selection.

Proton radiotherapy may be a compelling technical option for the treatment of breast cancer due to its unique physical property known as the "Bragg peak." This feature offers distinct advantages, promising superior dose conformity within the tumor area and reduced radiation exposure to surrounding healthy tissues, enhancing the potential for better treatment outcomes. However, proton therapy is accompanied by inherent challenges, primarily higher costs and limited accessibility when compared to well-developed photon irradiation. Thus, in clinical practice, it is important for radiation oncologists to carefully select patients before recommendation of proton therapy to ensure the transformation of dosimetric benefits into tangible clinical benefits. Yet, the optimal indications for proton therapy in breast cancer patients remain uncertain. While there is no widely recognized methodology for patient selection, numerous attempts have been made in this direction. In this review, we intended to present an inspiring summarization and discussion about the current practices and exploration on the approaches of this treatment decision-making process in terms of treatment-related side-effects, tumor control, and cost-efficiency, including the normal tissue complication probability (NTCP) model, the tumor control probability (TCP) model, genomic biomarkers, cost-effectiveness analyses (CEAs), and so on. Additionally, we conducted an evaluation of the eligibility criteria in ongoing randomized controlled trials and analyzed their reference value in patient selection. We evaluated the pros and cons of various potential patient selection approaches and proposed possible directions for further optimization and exploration. In summary, while proton therapy holds significant promise in breast cancer treatment, its integration into clinical practice calls for a thoughtful, evidence-driven strategy. By continuously refining the patient selection criteria, we can harness the full potential of proton radiotherapy while ensuring maximum benefit for breast cancer patients.