Citations

AbstractArtificial intelligence (AI) allows data analysis and integration at an unprecedented granularity and scale. Here we review the technological advances, challenges, and future perspectives of using AI for electro‐clinical phenotyping of animal models and patients with epilepsy. In translational research, AI models accurately identify behavioral states in animal models of epilepsy, allowing identification of correlations between neural activity and interictal and ictal behavior. Clinical applications of AI‐based automated and semi‐automated analysis of audio and video recordings of people with epilepsy, allow significant data reduction and reliable detection and classification of major motor seizures. AI models can accurately identify electrographic biomarkers of epilepsy, such as spikes, high‐frequency oscillations, and seizure patterns. Integrating AI analysis of electroencephalographic, clinical, and behavioral data will contribute to optimizing therapy for patients with epilepsy.

Background Patients often present to emergency departments (EDs) with concerns that do not require emergency care. Self-triage and other interventions may help some patients decide whether they should be seen in the ED. Symptoms associated with low risk of hospitalization can be identified in national ED data and can inform the design of interventions to reduce avoidable ED visits. Methods We used the National Hospital Ambulatory Medical Care Survey (NHAMCS) data from the United States National Health Care Statistics (NHCS) division of the Centers for Disease Control and Prevention (CDC). The ED datasets from 2011 through 2020 were combined. Primary reasons for ED visit and the binary field for hospital admission from the ED were used to estimate the proportion of ED patients admitted to the hospital for each reason for visit and age category. Results There were 221,027 surveyed ED visits during the 10-year data collection with 736 different primary reasons for visit and 23,228 hospitalizations. There were 145 million estimated hospitalizations from 1.37 billion estimated ED visits (10.6%). Inclusion criteria for this study were reasons for visit which had at least 30 ED visits in the sample; there were 396 separate reasons for visit which met this criteria. Of these 396 reasons for visit, 97 had admission percentages less than 2% and another 52 had hospital admissions estimated between 2% and 4%. However, there was a significant increase in hospitalizations within many of the ED reasons for visit in older adults. Conclusion Reasons for visit from national ED data can be ranked by hospitalization risk. Low-risk symptoms may help healthcare institutions identify potentially avoidable ED visits. Healthcare systems can use this information to help manage potentially avoidable ED visits with interventions designed to apply to their patient population and healthcare access.

Introduction: The incidence and pattern of neurological complications after congenital cardiac surgery have been changing over the years due to improvement in surgical technique and perioperative management. The aim of this study was to evaluate the incidence and pattern of neurological injury in our institute. Materials and Methods: We retrospectively reviewed all pediatric patients who underwent noncontrast computed tomography of the brain for suspected postoperative neurological injury occurring during the 1 st week after pediatric cardiac surgery between April 2016 and February 2020. We identified neurological injury as patients having ischemic infarct and intracranial hemorrhage. Results: A total of 2971 pediatric cardiac surgeries were performed at our institute. Sixty-seven patients (2.25%) developed neurological injury. Fifty-five patients (82%) developed ischemic infarct while 12 patients (18%) had intracranial hemorrhagic. Pattern of ischemic infarct included global hypoxic injury in 30 patients (54.5%), posterior cerebral artery territory in 9 patients (16.3%), middle cerebral artery territory in 8 patients (14.5%), multiterritory involvement in 5 patients (9.0%), and anterior cerebral artery territory in 3 patients (5.4%). In patients with intracranial hemorrhage, 5 patients (7.4%) developed subarachnoid hemorrhage (SAH), 4 patients (5.9%) developed subdural hemorrhage, and 3 patients (4.4%) developed intraparenchymal hemorrhage. Conclusions: Neurological complication accounts for significant morbidity and mortality after congenital cardiac surgery. In our study, ischemic infarct accounted for 82% cases. In ischemic infarct, global ischemia was the most common type and carried high risk of mortality. In hemorrhage group, SAH was the most common finding. Nevertheless, the aim of this study was to characterize the current incidence of acute clinically evident neurologic complications in children undergoing congenital cardiac surgery in a tertiary hospital, although acute neurologic morbidity appears to be appreciably lower than in the past at our institution.

Key Points Using multiple markers may improve GFR estimation especially in settings where creatinine and cystatin C are known to be limited. Panel eGFR is a novel multimarker eGFR equation consisting of age, sex, cystatin C, and nuclear magnetic resonance–measured creatinine, valine, and myo-inositol. eGFR-Cr and eGFR-Cr-CysC may underestimate measured GFR, while panel eGFR was unbiased among younger Black male individuals. Background Using multiple markers may improve accuracy in GFR estimation. We sought to externally validate and compare the performance of a novel multimarker eGFR (panel eGFR) equation among Black and White persons using the Genetic Epidemiology Network of Arteriopathy cohort. Methods We included 224 sex, race/ethnicity, and measured GFR (mGFR) category–matched persons, with GFR measured using urinary clearance of iothalamate. We calculated panel eGFR using serum creatinine, valine, myo-inositol, cystatin C, age, and sex. We compared its reliability with current eGFR equations (2021 CKD Epidemiology Collaboration creatinine [eGFR-Cr] and creatinine with cystatin C [eGFR-Cr-CysC]) using median bias, precision, and accuracy metrics. We evaluated each equation's performance in age, sex, and race subgroups. Results In the overall cohort, 49% were Black individuals, and mean mGFR was 79 ml/min per 1.73 m 2 . Panel eGFR overestimated mGFR (bias: −2.4 ml/min per 1.73 m 2 ; 95% confidence interval [CI], −4.4 to −0.7), eGFR-Cr-CysC underestimated mGFR (bias: 4.8 ml/min per 1.73 m 2 ; 95% CI, 2.1 to 6.7), while eGFR-Cr was unbiased (bias: 2.0 ml/min per 1.73 m 2 ; 95% CI, −1.1 to 4.6). All equations had comparable accuracy. Among Black male individuals younger than 65 years, both eGFR-Cr (bias: 17.0 ml/min per 1.73 m 2 ; 95% CI, 8.6 to 23.5) and eGFR-Cr-CysC (bias: 14.5 ml/min per 1.73 m 2 ; 95% CI, 6.0 to 19.7) underestimated mGFR, whereas panel eGFR was unbiased (bias: 1.7 ml/min per 1.73 m 2 ; 95% CI, −3.4 to 10.0). Metrics of accuracy for all eGFRs were acceptable in all subgroups except for panel eGFR in Black female individuals younger than 65 years (P30: 73.3%). Conclusions Panel eGFR can be used to estimate mGFR and may have utility among Black male individuals younger than 65 years where current CKD Epidemiology Collaboration equations are biased.

Key Points AKI survivors experience gaps in care that contribute to worse outcomes, experience, and cost. Challenges to optimal care include issues with information transfer, education, collaborative care, and use of digital health tools. Research is needed to study these challenges and inform optimal use of diagnostic and therapeutic interventions to promote recovery AKI affects one in five hospitalized patients and is associated with poor short-term and long-term clinical and patient-centered outcomes. Among those who survive to discharge, significant gaps in documentation, education, communication, and follow-up have been observed. The American Society of Nephrology established the AKINow taskforce to address these gaps and improve AKI care. The AKINow Recovery workgroup convened two focus groups, one each focused on dialysis-independent and dialysis-requiring AKI, to summarize the key considerations, challenges, and opportunities in the care of AKI survivors. This article highlights the discussion surrounding care of AKI survivors discharged without the need for dialysis. On May 3, 2022, 48 patients and multidisciplinary clinicians from diverse settings were gathered virtually. The agenda included a patient testimonial, plenary sessions, facilitated small group discussions, and debriefing. Core challenges and opportunities for AKI care identified were in the domains of transitions of care, education, collaborative care delivery, diagnostic and therapeutic interventions, and digital health applications. Integrated multispecialty care delivery was identified as one of the greatest challenges to AKI survivor care. Adequate templates for communication and documentation; education of patients, care partners, and clinicians about AKI; and a well-coordinated multidisciplinary posthospital follow-up plan form the basis for a successful care transition at hospital discharge. The AKINow Recovery workgroup concluded that advancements in evidence-based, patient-centered care of AKI survivors are needed to improve health outcomes, care quality, and patient and provider experience. Tools are being developed by the AKINow Recovery workgroup for use at the hospital discharge to facilitate care continuity.

Goals: We aim to describe the weight loss outcomes of patients with celiac disease (CeD) taking antiobesity medications (AOMs) and compare it with the weight loss outcomes of patients without CeD taking AOMs. Background: Increasing rates of obesity and obesity-associated comorbidities have been previously reported in patients with CeD on a gluten-free diet. The effectiveness of AOMs in this population has not been previously described. Methods: In our retrospective cohort study, we matched 39 patients with treated CeD to 78 patients without CeD based on sex and AOM. We assessed the weight loss outcomes at 3, 6, and 12 months after starting the AOM in both cohorts and analyzed if there was a differential response when comparing by type of AOM [injectable glucagon-like peptide 1 (GLP-1) receptor agonists vs. oral non-GLP-1 AOMs]. Results: Both cohorts had similar baseline demographic and anthropometric characteristics. At 12 months, the CeD cohort had a nonsignificantly inferior total body weight loss percentage compared with the cohort without CeD (6.5% vs. 9.5%, P=0.13). The CeD cohort had a similar proportion of patients achieving a total body weight loss percentage of ≥5% than the cohort without CeD (72.7% vs. 72.1%, P=1.00). No significant difference was observed when comparing the weight loss outcomes of injectables (GLP-1 receptor agonists) to oral AOMs. The proportion of patients reporting side effects was similar for both groups, regardless of the type of AOM. Conclusion: Patients with CeD taking AOMs had similar weight loss outcomes to patients without CeD. Hence, AOMs can be a safe and effective therapy for weight management in patients with CeD.