Citations

Introduction/Purpose: To examine trends in patient presentation, diagnosis and outcomes of acute aortic dissection over 15 years since the original report from the International Registry of Acute Aortic Dissection (IRAD). Methods: Patient data were collected at 28 international referral centers from 1996 up to the present. Trends were analyzed among 3275 patients divided according to date of enrollment into 6 equal groups and by Type: A (n=2110) or B (n=1165). Results: There was no change over time in the presenting complaints of severe or worst ever pain for Type A and Type B (90% and 96%, respectively), or in the incidence of chest pain ( 80% in Type A and 70% in Type B, respectively), with considerable overlap in chest vs. back pain between types. The report of pulse deficits did not change over time, present in 30% of Type A patients. Normal chest X-ray on presentation increased in Type A acute aortic dissection (AoD) from 13.7% to 31.3% over time (p-value for trend <0.001). In Type B the report of normal chest X-ray increased from 19.9% to 40.9% (p-value for trend <0.001). There were significant trends in initial imaging modalities for Type A: increased use of CT (from 49.4% to 71.6%, p-value for trend <0.001) and decreased use of TEE (from 45.3% to 25.4%, p-value for trend <0.001). For Type B, use of CT increased from 77.2% to 88.4% (p-value for trend .013). A decrease in overall mortality over time was significant for both Type A and Type B patients (see graph). Surgical mortality in Type A patients fell from 25.3% to 16.5% (p-value for trend 0 .003). Conclusions: No significant difference was seen over time in pain severity, chest pain, and presence of pulse deficits. The incidences of a normal chest X-ray, originally thought to be uncommon in dissection cases, increased over time to 30% in Type A and 40% in Type B AoD. Use of CT as the initial imaging modality increased for both Type A and Type B. Lastly, a significant decrease in overall mortality was seen for both Type A and Type B patients.

OBJECTIVE The objective of this study was to compare clinical and patient-reported outcomes (PROs) between posterior foraminotomy and anterior cervical discectomy and fusion (ACDF) in patients presenting with cervical radiculopathy. METHODS The Quality Outcomes Database was queried for patients who had undergone ACDF or posterior foraminotomy for radiculopathy. To create two highly homogeneous groups, optimal individual matching was performed at a 5:1 ratio between the two groups on 29 baseline variables (including demographic characteristics, comorbidities, symptoms, patient-reported scores, underlying pathologies, and levels treated). Outcomes of interest were length of stay, reoperations, patient-reported satisfaction, increase in EQ-5D score, and decrease in Neck Disability Index (NDI) scores for arm and neck pain as long as 1 year after surgery. Noninferiority analysis of achieving patient satisfaction and minimal clinically important difference (MCID) in PROs was performed with an accepted risk difference of 5%. RESULTS A total of 7805 eligible patients were identified: 216 of these underwent posterior foraminotomy and were matched to 1080 patients who underwent ACDF. The patients who underwent ACDF had more underlying pathologies, lower EQ-5D scores, and higher NDI and neck pain scores at baseline. Posterior foraminotomy was associated with shorter hospitalization (0.5 vs 0.9 days, p < 0.001). Reoperations within 12 months were significantly more common among the posterior foraminotomy group (4.2% vs 1.9%, p = 0.04). The two groups performed similarly in PROs, with posterior foraminotomy being noninferior to ACDF in achieving MCID in EQ-5D and neck pain scores but also having lower rates of maximal satisfaction at 12 months (North American Spine Society score of 1 achieved by 65.2% posterior foraminotomy patients vs 74.6% of ACDF patients, p = 0.02). CONCLUSIONS The two procedures were found to be offered to different populations, with ACDF being selected for patients with more complicated pathologies and symptoms. After individual matching, posterior foraminotomy was associated with a higher reoperation risk within 1 year after surgery compared to ACDF (4.2% vs 1.9%). In terms of 12-month PROs, posterior foraminotomy was noninferior to ACDF in improving quality of life and neck pain. The two procedures also performed similarly in improving NDI scores and arm pain, but ACDF patients had higher maximal satisfaction rates.

Abstract Background Error analysis plays a crucial role in clinical concept extraction, a fundamental subtask within clinical natural language processing (NLP). The process typically involves a manual review of error types, such as contextual and linguistic factors contributing to their occurrence, and the identification of underlying causes to refine the NLP model and improve its performance. Conducting error analysis can be complex, requiring a combination of NLP expertise and domain-specific knowledge. Due to the high heterogeneity of electronic health record (EHR) settings across different institutions, challenges may arise when attempting to standardize and reproduce the error analysis process. Objectives This study aims to facilitate a collaborative effort to establish common definitions and taxonomies for capturing diverse error types, fostering community consensus on error analysis for clinical concept extraction tasks. Materials and Methods We iteratively developed and evaluated an error taxonomy based on existing literature, standards, real-world data, multisite case evaluations, and community feedback. The finalized taxonomy was released in both .dtd and .owl formats at the Open Health Natural Language Processing Consortium. The taxonomy is compatible with several different open-source annotation tools, including MAE, Brat, and MedTator. Results The resulting error taxonomy comprises 43 distinct error classes, organized into 6 error dimensions and 4 properties, including model type (symbolic and statistical machine learning), evaluation subject (model and human), evaluation level (patient, document, sentence, and concept), and annotation examples. Internal and external evaluations revealed strong variations in error types across methodological approaches, tasks, and EHR settings. Key points emerged from community feedback, including the need to enhancing clarity, generalizability, and usability of the taxonomy, along with dissemination strategies. Conclusion The proposed taxonomy can facilitate the acceleration and standardization of the error analysis process in multi-site settings, thus improving the provenance, interpretability, and portability of NLP models. Future researchers could explore the potential direction of developing automated or semi-automated methods to assist in the classification and standardization of error analysis.

Evidence from medicine and other fields has shown that gender diversity results in better decision making and outcomes. The incoming workforce of congenital heart specialists (especially in pediatric cardiology) appears to be more gender balanced, but past studies have shown many inequities. Gender‐associated differences in leadership positions, opportunities presented for academic advancement, and recognition for academic contributions to the field persist. In addition, compensation packages remain disparate if evaluated based on gender with equivalent experience and expertise. This review explores these inequities and has suggested individual and institutional changes that could be made to recruit and retain women, monitor the climate of the institution, and identify and eliminate bias in areas like salary and promotions.

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 Axicabtagene ciloleucel (axi-cel) is an autologous anti-CD19 chimeric antigen receptor (CAR) T-cell therapy approved for relapsed/refractory (R/R) large B-cell lymphoma (LBCL). Despite extensive data supporting its use, outcomes stratified by race and ethnicity groups are limited. Here, we report clinical outcomes with axi-cel in patients with R/R LBCL by race and ethnicity in both real-world and clinical trial settings. In the real-world setting, 1290 patients who received axi-cel between 2017 and 2020 were identified from the Center for International Blood and Marrow Transplant Research database; 106 and 169 patients were included from the ZUMA-1 and ZUMA-7 trials, respectively. Overall survival was consistent across race/ethnicity groups. However, non-Hispanic (NH) Black patients had lower overall response rate (OR, 0.37; 95% CI, 0.22-0.63) and lower complete response rate (OR, 0.57; 95% CI, 0.33-0.97) than NH White patients. NH Black patients also had a shorter progression-free survival vs NH White (HR, 1.41; 95% CI, 1.04-1.90) and NH Asian patients (HR, 1.67; 95% CI, 1.08-2.59). NH Asian patients had a longer duration of response than NH White (HR, 0.56; 95% CI, 0.33-0.94) and Hispanic patients (HR, 0.54; 95% CI, 0.30-0.97). There was no difference in cytokine release syndrome by race/ethnicity; however, higher rates of any-grade immune effector cell–associated neurotoxicity syndrome were observed in NH White patients than in other patients. These results provide important context when treating patients with R/R LBCL with CAR T-cell therapy across different racial and ethnic groups. ZUMA-1 and ZUMA-7 (ClinicalTrials.gov identifiers: #NCT02348216 and #NCT03391466, respectively) are registered on ClinicalTrials.gov.

OBJECTIVE Cervical spondylotic myelopathy (CSM) can cause significant difficulty with driving and a subsequent reduction in an individual’s quality of life due to neurological deterioration. The positive impact of surgery on postoperative patient-reported driving capabilities has been seldom explored. METHODS The CSM module of the Quality Outcomes Database was utilized. Patient-reported driving ability was assessed via the driving section of the Neck Disability Index (NDI) questionnaire. This is an ordinal scale in which 0 represents the absence of symptoms while driving and 5 represents a complete inability to drive due to symptoms. Patients were considered to have an impairment in their driving ability if they reported an NDI driving score of 3 or higher (signifying impairment in driving duration due to symptoms). Multivariable logistic regression models were fitted to evaluate mediators of baseline impairment and improvement at 24 months after surgery, which was defined as an NDI driving score < 3. RESULTS A total of 1128 patients who underwent surgical intervention for CSM were included, of whom 354 (31.4%) had baseline driving impairment due to CSM. Moderate (OR 2.3) and severe (OR 6.3) neck pain, severe arm pain (OR 1.6), mild-moderate (OR 2.1) and severe (OR 2.5) impairment in hand/arm dexterity, severe impairment in leg use/walking (OR 1.9), and severe impairment of urinary function (OR 1.8) were associated with impaired driving ability at baseline. Of the 291 patients with baseline impairment and available 24-month follow-up data, 209 (71.8%) reported postoperative improvement in their driving ability. This improvement seemed to be mediated particularly through the achievement of the minimal clinically important difference (MCID) in neck pain and improvement in leg function/walking. Patients with improved driving at 24 months noted higher postoperative satisfaction (88.5% vs 62.2%, p < 0.01) and were more likely to achieve a clinically significant improvement in their quality of life (50.7% vs 37.8%, p < 0.01). CONCLUSIONS Nearly one-third of patients with CSM report impaired driving ability at presentation. Seventy-two percent of these patients reported improvements in their driving ability within 24 months of surgery. Surgical management of CSM can significantly improve patients’ driving abilities at 24 months and hence patients’ quality of life.

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 Introduction/Aims Biomarkers have shown promise in amyotrophic lateral sclerosis (ALS) research, but the quest for reliable biomarkers remains active. This study evaluates the effect of debamestrocel on cerebrospinal fluid (CSF) biomarkers, an exploratory endpoint. Methods A total of 196 participants randomly received debamestrocel or placebo. Seven CSF samples were to be collected from all participants. Forty‐five biomarkers were analyzed in the overall study and by two subgroups characterized by the ALS Functional Rating Scale‐Revised (ALSFRS‐R). A prespecified model was employed to predict clinical outcomes leveraging biomarkers and disease characteristics. Causal inference was used to analyze relationships between neurofilament light chain (NfL) and ALSFRS‐R. Results We observed significant changes with debamestrocel in 64% of the biomarkers studied, spanning pathways implicated in ALS pathology (63% neuroinflammation, 50% neurodegeneration, and 89% neuroprotection). Biomarker changes with debamestrocel show biological activity in trial participants, including those with advanced ALS. CSF biomarkers were predictive of clinical outcomes in debamestrocel‐treated participants (baseline NfL, baseline latency‐associated peptide/transforming growth factor beta1 [LAP/TGFβ1], change galectin‐1, all p < .01), with baseline NfL and LAP/TGFβ1 remaining ( p < .05) when disease characteristics ( p < .005) were incorporated. Change from baseline to the last measurement showed debamestrocel‐driven reductions in NfL were associated with less decline in ALSFRS‐R. Debamestrocel significantly reduced NfL from baseline compared with placebo (11% vs. 1.6%, p = .037). Discussion Following debamestrocel treatment, many biomarkers showed increases (anti‐inflammatory/neuroprotective) or decreases (inflammatory/neurodegenerative) suggesting a possible treatment effect. Neuroinflammatory and neuroprotective biomarkers were predictive of clinical response, suggesting a potential multimodal mechanism of action. These results offer preliminary insights that need to be confirmed.