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Abstract The role of diet in colorectal cancer prognosis is not well understood and specific lifestyle recommendations are lacking. We searched for randomised controlled trials (RCTs) and longitudinal observational studies on post‐diagnosis dietary factors, supplement use and colorectal cancer survival outcomes in PubMed and Embase from inception until 28th February 2022. Random‐effects dose–response meta‐analyses were conducted when at least three studies had sufficient information. The evidence was interpreted and graded by the CUP Global independent Expert Committee on Cancer Survivorship and Expert Panel. Five RCTs and 35 observational studies were included (30,242 cases, over 8700 all‐cause and 2100 colorectal cancer deaths, 3700 progression, recurrence, or disease‐free events). Meta‐analyses, including 3–10 observational studies each, were conducted for: whole grains, nuts/peanuts, red and processed meat, dairy products, sugary drinks, artificially sweetened beverages, coffee, alcohol, dietary glycaemic load/index, insulin load/index, marine omega‐3 polyunsaturated fatty acids, supplemental calcium, circulating 25‐hydroxyvitamin D (25[OH]D) and all‐cause mortality; for alcohol, supplemental calcium, circulating 25(OH)D and colorectal cancer‐specific mortality; and for circulating 25(OH)D and recurrence/disease‐free survival. The overall evidence was graded as ‘limited’. The inverse associations between healthy dietary and/or lifestyle patterns (including diets that comprised plant‐based foods), whole grains, total, caffeinated, or decaffeinated coffee and all‐cause mortality and the positive associations between unhealthy dietary patterns, sugary drinks and all‐cause mortality provided ‘limited—suggestive’ evidence. All other exposure‐outcome associations provided ‘limited—no conclusion’ evidence. Additional, well‐conducted cohort studies and carefully designed RCTs are needed to develop specific lifestyle recommendations for colorectal cancer survivors.

AbstractIntroductionStructured data capture requires defined languages such as minimal Common Oncology Data Elements (mCODE). This pilot assessed the feasibility of capturing 5 mCODE categories (stage, disease status, performance status (PS), intent of therapy and intent to change therapy).MethodsA tool (SmartPhrase) using existing and custom structured data elements was Built to capture 4 data categories (disease status, PS, intent of therapy and intent to change therapy) typically documented as free‐text within notes. Existing functionality for stage was supported by the Build. Participant survey data, presence of data (per encounter), and time in chart were collected prior to go‐live and repeat timepoints. The anticipated outcome was capture of >50% sustained over time without undue burden.ResultsPre‐intervention (5‐weeks before go‐live), participants had 1390 encounters (1207 patients). The median percent capture across all participants was 32% for stage; no structured data was available for other categories pre‐intervention. During a 6‐month pilot with 14 participants across three sites, 4995 encounters (3071 patients) occurred. The median percent capture across all participants and all post‐intervention months increased to 64% for stage and 81%–82% for the other data categories post‐intervention. No increase in participant time in chart was noted. Participants reported that data were meaningful to capture.ConclusionsStructured data can be captured (1) in real‐time, (2) sustained over time without (3) undue provider burden using note‐based tools. Our system is expanding the pilot, with integration of these data into clinical decision support, practice dashboards and potential for clinical trial matching.

Introduction: Asymptomatic LV systolic dysfunction is often underdiagnosed, leading to missed opportunities for treatment. In a recently completed pragmatic RCT, an AI algorithm performed on the ECGs ordered as part of routine practice increased early diagnosis of low EF. The current study aimed to understand whether the effectiveness of the AI algorithm integrated into routine care differed by the socioeconomic status of the patient. Methods: The main findings of the RCT were previously published. Clinicians in the intervention group had access to AI results (i.e., a positive or negative screening result, with positive results indicating a high likelihood of low EF). When a positive result was found, clinicians in the intervention group received an alert that encouraged them to order TTE if considered clinically appropriate. Clinicians in the control group did not have access or received alerts. Area deprivation index (ADI) was used to measure area-level social determinants of health. This study included 16,992 patients (control 8,225; intervention: 8,767) who had ECG performed for any indications between 8/5/2019 and 3/31/2020, no prior HF, and a valid address to derive ADI. The primary endpoint was a new diagnosis of EF≤50% within 3 months. Results: The mean age was 60.5±17.6 y. AI increased the diagnosis of low EF in the overall cohort (OR 1.42 [1.13, 1.78], p=0.01). The magnitude of benefit was greater in patients with higher socioeconomic status, e.g., living in an area that is less deprived (OR 1.88 [1.16, 3.05]), with higher median income, lower poverty rate, higher education level, better housing conditions, and higher proportion of white-collar workers, although the interaction was not statistically significant (Figure). Conclusions: AI enables early diagnosis of low EF and the magnitude of benefit might be numerically greater in patients with higher socioeconomic status, possibly due to variations in access to or referral for subsequent testing.

Abstract Aims Mobile devices such as smartphones and watches can now record single-lead electrocardiograms (ECGs), making wearables a potential screening tool for cardiac and wellness monitoring outside of healthcare settings. Because friends and family often share their smart phones and devices, confirmation that a sample is from a given patient is important before it is added to the electronic health record. Methods and results We sought to determine whether the application of Siamese neural network would permit the diagnostic ECG sample to serve as both a medical test and biometric identifier. When using similarity scores to discriminate whether a pair of ECGs came from the same patient or different patients, inputs of single-lead and 12-lead medians produced an area under the curve of 0.94 and 0.97, respectively. Conclusion The similar performance of the single-lead and 12-lead configurations underscores the potential use of mobile devices to monitor cardiac health.

Study Design: Retrospective cohort analysis. Objective: To determine whether the C2 exposure technique was a predictor of change in cervical alignment and patient-reported outcomes measures (PROMs) after posterior cervical decompression and fusion (PCDF) for degenerative indications. Background: In PCDF handling of the C2 posterior paraspinal musculature during the operative approach varies by surgeon technique. To date, no studies have investigated whether maintenance of the upper cervical semispinalis cervicis attachments as compared with complete reflection of upper cervical paraspinal musculature from the posterior bony elements is associated with superior radiographic and clinical outcomes after PCDF. Patients and Methods: All adult patients who underwent C2–T2 PCDF for myelopathy or myeloradiculopathy at multi-institutional academic centers between 2013 and 2020 were retrospectively identified. Patients were dichotomized by the C2 exposure technique into semispinalis preservation or midline muscular reflection groups. Preoperative and short and long-term postoperative radiographic outcomes (upper cervical alignment, global alignment, and fusion status) and PROMs (Visual Analog Scale–Neck, Neck Disability Index, and Short Form-12) were collected. Univariate analysis compared patient factors, radiographic measures, and PROMs across C2 exposure groups. Results: A total of 129 patients met the inclusion/exclusion criteria (73 muscle preservation and 56 muscle reflection). Patients in the muscular preservation group were on average younger (P = 0.005) and more likely to have bone morphogenic protein (P < 0.001) and C2 pars screws (P = 0.006) used during surgery. Preoperative to postoperative changes in C2 slope, C2 tilt, C2–C3 segmental lordosis, C2–C3 listhesis, C0–C2 Cobb angle, proximal junctional kyphosis, ADI, C1 lamina-occiput distance, C2 sagittal vertical axis, C2–C7 lordosis, and PROMs at all follow-up intervals did not vary significantly by C2 exposure technique. Likewise, there were no significant differences in fusion status, C2–C3 pseudoarthrosis, C2 screw loosening, and complication and revision rates between C2 exposure groups. Conclusions: Preservation of C2 semispinalis attachments versus muscular reflection did not significantly impact cervical alignment, clinical outcomes, or proximal junction complications in long-segment PCDF. Level of Evidence: Level III.

Abstract Pulmonary hypertension (PH) associated with left heart failure (LHF) (PH-LHF) is one of the most common causes of PH. It directly contributes to symptoms and reduced functional capacity and negatively affects right heart function, ultimately leading to a poor prognosis. There are no specific treatments for PH-LHF, despite the high number of drugs tested so far. This scientific document addresses the main knowledge gaps in PH-LHF with emphasis on pathophysiology and clinical trials. Key identified issues include better understanding of the role of pulmonary venous versus arteriolar remodelling, multidimensional phenotyping to recognize patient subgroups positioned to respond to different therapies, and conduct of rigorous pre-clinical studies combining small and large animal models. Advancements in these areas are expected to better inform the design of clinical trials and extend treatment options beyond those effective in pulmonary arterial hypertension. Enrichment strategies, endpoint assessments, and thorough haemodynamic studies, both at rest and during exercise, are proposed to play primary roles to optimize early-stage development of candidate therapies for PH-LHF.

Abstract Aims Recently, deep learning artificial intelligence (AI) models have been trained to detect cardiovascular conditions, including hypertrophic cardiomyopathy (HCM), from the 12-lead electrocardiogram (ECG). In this external validation study, we sought to assess the performance of an AI-ECG algorithm for detecting HCM in diverse international cohorts. Methods and results A convolutional neural network-based AI-ECG algorithm was developed previously in a single-centre North American HCM cohort (Mayo Clinic). This algorithm was applied to the raw 12-lead ECG data of patients with HCM and non-HCM controls from three external cohorts (Bern, Switzerland; Oxford, UK; and Seoul, South Korea). The algorithm’s ability to distinguish HCM vs. non-HCM status from the ECG alone was examined. A total of 773 patients with HCM and 3867 non-HCM controls were included across three sites in the merged external validation cohort. The HCM study sample comprised 54.6% East Asian, 43.2% White, and 2.2% Black patients. Median AI-ECG probabilities of HCM were 85% for patients with HCM and 0.3% for controls (P &lt; 0.001). Overall, the AI-ECG algorithm had an area under the receiver operating characteristic curve (AUC) of 0.922 [95% confidence interval (CI) 0.910–0.934], with diagnostic accuracy 86.9%, sensitivity 82.8%, and specificity 87.7% for HCM detection. In age- and sex-matched analysis (case–control ratio 1:2), the AUC was 0.921 (95% CI 0.909–0.934) with accuracy 88.5%, sensitivity 82.8%, and specificity 90.4%. Conclusion The AI-ECG algorithm determined HCM status from the 12-lead ECG with high accuracy in diverse international cohorts, providing evidence for external validity. The value of this algorithm in improving HCM detection in clinical practice and screening settings requires prospective evaluation.

Abstract Aims Patients with heart failure and mildly reduced or preserved ejection fraction have limited therapeutic options. The ALT-FLOW Early Feasibility Study evaluated safety, haemodynamics and outcomes for the APTURE transcatheter shunt system, a novel left atrium to coronary sinus shunt in these patients. Methods and results Safety and shunt implantation success was evaluated for all 116 enrolled patients. An analysis population of implanted patients with a left ventricular ejection fraction (LVEF) &gt;40% (n = 95) was chosen to assess efficacy via paired comparison between baseline and follow-up haemodynamic (3 and 6 months), and echocardiographic, clinical and functional outcomes (6 months and 1 year). Health status and quality of life outcomes were assessed using the Kansas City Cardiomyopathy Questionnaire overall summary score (KCCQ-OSS). The primary safety endpoint, major adverse cardiac, cerebral, and renal events, and reintervention through 30 days, occurred in 3/116 patients (2.6%). All implanted shunts were patent at 1 year. In patients with LVEF &gt;40%, the mean (95% confidence interval) reduction in exercise pulmonary capillary wedge pressure (PCWP) at 20 W was −5.7 (−8.6, −2.9) mmHg at 6 months (p &lt; 0.001). At baseline, 8% had New York Heart Association class I–II status and improved to 68% at 1 year (p &lt; 0.001). KCCQ-OSS at baseline was 39 (35, 43) and improved at 6 months and 1 year by 25 (20–30) and 27 (22–32) points, respectively (both p &lt; 0.0001). No adverse changes in haemodynamic and echocardiographic indices of right heart function were observed at 1 year. Overall, the reduction in PCWP at 20 W and improvement in KCCQ-OSS in multiple subgroups were consistent with those observed for the entire population. Conclusions In patients with heart failure and LVEF &gt;40%, the APTURE shunt demonstrated an acceptable safety profile with significant sustained improvements in haemodynamic and patient-centred outcomes, underscoring the need for further evaluation of the APTURE shunt in a randomized trial.

BACKGROUND AND OBJECTIVES: Cervical disk arthroplasty (CDA) offers the advantage of motion preservation in the treatment of focal cervical pathology. At present, implant sizing is performed using subjective tactile feedback and imaging of trial cages. This study aims to construct interpretable machine learning (IML) models to accurately predict postoperative range of motion (ROM) and identify the optimal implant sizes that maximize ROM in patients undergoing CDA. METHODS: Adult patients who underwent CDA for single-level disease from 2012 to 2020 were identified. Patient demographics, comorbidities, and outcomes were collected, including symptoms, examination findings, subsidence, and reoperation. Affected disk height, healthy rostral disk height, and implant height were collected at sequential time points. Linear regression and IML models, including bagged regression tree, bagged multivariate adaptive regression spline, and k-nearest neighbors, were used to predict ROM change. Model performance was assessed by calculating the root mean square error (RMSE) between predicted and actual changes in ROM in the validation cohort. Variable importance was assessed using RMSE loss. Area under the curve analyses were performed to identify the ideal implant size cutoffs in predicting improved ROM. RESULTS: Forty-seven patients were included. The average RMSE between predicted and actual ROM was 7.6° (range: 5.8-10.1) in the k-nearest neighbors model, 7.8° (range: 6.5-10.0) in the bagged regression tree model, 7.8° (range: 6.2-10.0) in the bagged multivariate adaptive regression spline model, and 15.8° (range: 14.3-17.5°) in a linear regression model. In the highest-performing IML model, graft size was the most important predictor with RMSE loss of 6.2, followed by age (RMSE loss = 5.9) and preoperative caudal disk height (RMSE loss = 5.8). Implant size at 110% of the normal adjacent disk height was the optimal cutoff associated with improved ROM. CONCLUSION: IML models can reliably predict change in ROM after CDA within an average of 7.6 degrees of error. Implants sized comparably with the healthy adjacent disk may maximize ROM.

Background and Aims: Portal hypertension is a serious complication of cirrhosis, which leads to life-threatening complications. HVPG, a surrogate of portal pressure, is the reference standard test to assess the severity of portal hypertension. However, since HVPG is limited by its invasiveness and availability, noninvasive liver disease assessments to assess portal pressure, especially clinically significant portal hypertension (CSPH), are needed. Approach and Results: We conducted a systematic review of Ovid MEDLINE(R) Ovid EMBASE, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, and Scopus from each database’s inception to April 22, 2022. We included only studies in English that examined ≥50 patients in single liver disease etiologies, which compared noninvasive tests (blood and/or imaging) to HVPG for predicting clinically significant portal hypertension (CSPH; defined as HVPG ≥ 10 mm Hg) in patients with chronic liver disease. Outcomes included measures of diagnostic test accuracy. Additionally, a narrative review of studies not eligible for the systematic review is also provided. Nine studies with 2492 patients met the inclusion criteria. There was substantial heterogeneity with regard to liver disease studied and cutoff values used to detect CSPH. Blood-based tests, including aspartate-to-platelet ratio index (APRI) (56% sensitivity and 68% specificity) and FIB-4 (54% sensitivity and 73% specificity) had low accuracy measures. Imaging-based tests (transient elastography and shear wave elastography detection of liver stiffness measurement [LSM]) had better accuracy but also had substantial variation; at 15 kPa, TE sensitivity was 90%–96% and specificity was 48%–50%, while at 25 kPa, its sensitivity and specificity were 57%–85% and 82%–93%, respectively. The narrative review suggested that imaging-based tests are the best available noninvasive liver disease assessment to detect CSPH; CSPH is highly unlikely to be present at an LSM ≤15 kPa and likely to be present at an LSM ≥25 kPa. Conclusions: While imaging-based noninvasive liver disease assessment appeared to have higher accuracy than blood-based tests to detect CSPH, only 9 studies fit the a priori established inclusion criteria for the systematic review. In addition, there was substantial study heterogeneity and variation in cutoffs for LSM to detect CSPH, limiting the ability to establish definitive cutoffs to detect CSPH.