Citations

AbstractBackgroundWe aimed to cluster deceased donor kidney transplant recipients with prolonged cold ischemia time (CIT) using an unsupervised machine learning approach.MethodsWe performed consensus cluster analysis on 11 615 deceased donor kidney transplant patients with CIT exceeding 24 h using OPTN/UNOS data from 2015 to 2019. Cluster characteristics of clinical significance were identified, and post‐transplant outcomes were compared.ResultsConsensus cluster analysis identified two clinically distinct clusters. Cluster 1 was characterized by young, non‐diabetic patients who received kidney transplants from young, non‐hypertensive, non‐ECD deceased donors with lower KDPI scores. In contrast, the patients in cluster 2 were older and more likely to have diabetes. Cluster 2 recipients were more likely to receive transplants from older donors with a higher KDPI. There was lower use of machine perfusion in Cluster 1 and incrementally longer CIT in Cluster 2. Cluster 2 had a higher incidence of delayed graft function (42% vs. 29%), and lower 1‐year patient (95% vs. 98%) and death‐censored (95% vs. 97%) graft survival compared to Cluster 1.ConclusionsUnsupervised machine learning characterized deceased donor kidney transplant recipients with prolonged CIT into two clusters with differing outcomes. Although Cluster 1 had more favorable recipient and donor characteristics and better survival, the outcomes observed in Cluster 2 were also satisfactory. Overall, both clusters demonstrated good survival suggesting opportunities for transplant centers to incrementally increase CIT.

AbstractPancreas transplantation alone (PTA) is a β cell replacement option for selected patients with type 1 diabetes mellitus; concerns have been raised regarding deterioration in kidney function (KF) after PTA. This retrospective multicenter study assessed actual impact of transplantation and immunosuppression on KF in PTA recipients at three Transplant Centers. The primary composite endpoint 10 years after PTA was >50% eGFR decline, eGFR < 30 mL/min/1.73 m2, and/or receiving a kidney transplant (KT). Overall, 822 PTA recipients met eligibility. Median baseline and 10‐year eGFR (mL/min/1.73 m2) were 76.3 (58.1–100.8) and 51.3 (35.3–65.9), respectively. Primary composite endpoint occurred in 98 patients (53.5%) with 45 experiencing a >50% decrease in eGFR by 10 years post‐transplant, 38 eGFR < 30 mL/min/1.73 m2 and 49 requiring KT. KF declined most significantly within 6 months post‐PTA, more often in females and patients with better preserved GFR up to 5 years with 11.6% kidney failure at 10 years. Patient survival and death‐censored graft survival were both 68% at 10 years with overall graft thrombosis rate 8%. KF declined initially after PTA but stabilized with further slow progression. In conclusion, prospective intervention studies are needed to test renal sparing interventions while gathering more granular data.

AbstractIntroductionThe infusion of autograft Natural Killer Cells (NKC)/CD14+HLA‐DRDIM ratio is a predictor of survival in lymphoma patients undergoing autologous peripheral blood hematopoietic stem cell transplantation (APBHSCT). This study evaluated if the Day 100 NKC/CD14+HLA‐DRDIM ratio still functions as a prognostic immune‐biomarker.MethodsThis was a retrospective, single‐institution, cohort analysis including 107 patients in this study that had clinical assessment at Day 100 post‐APBHSCT from our prior phase III trial. We evaluated the prognostic ability of the Day 100 NKC/CD14+HLA‐DRDIM ratio to predict overall survival (OS) and progression‐free survival (PFS) using Cox regression model for outcome analysis and survival by Kaplan–Meier method.ResultsThe median follow‐up from day 100 was 94.7 months (range 4.83–158.1 months) for the entire cohort. Patients with a Day 100 NKC/CD14+HLA‐DRDIM ratio ≥1.67 experienced better OS and PFS versus those with a Day 100 NKC/CD14+HLA‐DRDIM ratio <1.67: median OS was not reached versus 49.7 months, the 5‐year OS rates were 91% (95% CI, 81%–96%) versus 40% (95% CI, 27%–55%), p < .0001, respectively; and median PFS was not reached versus 23.5 months, the 5‐year PFS rates were 66% (95% CI, 55%–81%) versus 21% (95% CI, 15%–40%), p < .0001, respectively. Day 100 NKC/CD14+HLA‐DRDIM ratio was an independent predictor for OS and PFS in the multivariate analysis.ConclusionsDay 100 NKC/CD14+HLA‐DRDIM ratio is a prognostic immune‐biomarker in lymphoma patients post‐ APBHSCT.

In modern eye care, the adoption of ophthalmology chatbots stands out as a pivotal technological progression. These digital assistants present numerous benefits, such as better access to vital information, heightened patient interaction, and streamlined triaging. Recent evaluations have highlighted their performance in both the triage of ophthalmology conditions and ophthalmology knowledge assessment, underscoring their potential and areas for improvement. However, assimilating these chatbots into the prevailing healthcare infrastructures brings challenges. These encompass ethical dilemmas, legal compliance, seamless integration with electronic health records (EHR), and fostering effective dialogue with medical professionals. Addressing these challenges necessitates the creation of bespoke standards and protocols for ophthalmology chatbots. The horizon for these chatbots is illuminated by advancements and anticipated innovations, poised to redefine the delivery of eye care. The synergy of artificial intelligence (AI) and machine learning (ML) with chatbots amplifies their diagnostic prowess. Additionally, their capability to adapt linguistically and culturally ensures they can cater to a global patient demographic. In this article, we explore in detail the utilization of chatbots in ophthalmology, examining their accuracy, reliability, data protection, security, transparency, potential algorithmic biases, and ethical considerations. We provide a comprehensive review of their roles in the triage of ophthalmology conditions and knowledge assessment, emphasizing their significance and future potential in the field.

Ketamine has shown rapid antidepressant and anti-suicidal effects in treatment-resistant depression (TRD) with single and serial intravenous (IV) infusions, but the effectiveness for depressive episodes of bipolar disorder is less clear. We conducted an updated systematic review and meta-analysis to appraise the current evidence on the efficacy and tolerability of ketamine/esketamine in bipolar depression. A search was conducted to identify randomized controlled trials (RCTs) and non-randomized studies examining single or multiple infusions of ketamine or esketamine treatments. A total of 2657 articles were screened; 11 studies were included in the systematic review of which 7 studies were included in the meta-analysis (five non-randomized, N = 159; two RCTs, N = 33) with a mean age of 42.58 ± 13.1 years and 54.5% females. Pooled analysis from two RCTs showed a significant improvement in depression symptoms measured with MADRS after receiving a single infusion of ketamine (1-day WMD = −11.07; and 2 days WMD = −12.03). Non-randomized studies showed significant response (53%, p < 0.001) and remission rates (38%, p < 0.001) at the study endpoint. The response (54% vs. 55%) and remission (30% vs. 40%) rates for single versus serial ketamine infusion studies were similar. The affective switch rate in the included studies approximated 2.4%. Esketamine data for bipolar depression are limited, based on non-randomized, small sample-sized studies. Further studies with larger sample sizes are required to strengthen the evidence.

AbstractIntroduction/AimsIn 2016, nusinersen became the first disease‐modifying medication approved by the U.S. Food and Drug Administration (FDA) for spinal muscular atrophy (SMA). With the later availability of risdiplam in 2020, individuals now have the option of switching from nusinersen to risdiplam. Limited published data exist to inform this decision. This study aims to evaluate the perceptions and experiences of adult participants and parents of minor participants who previously received nusinersen and switched to risdiplam for the treatment of SMA.MethodsInstitutional Review Board (IRB) approval was obtained from the Wake Forest IRB prior to the initiation of this study. A cross‐sectional, observational study, with qualitative and quantitative data gathered via questionnaire and medical record review, was performed. Inclusion criteria included (1) prior diagnosis of SMA, (2) previous treatment with nusinersen, and (3) change to treatment with risdiplam. No participants were excluded based on age.ResultsFourteen participants—eight adults and six children—were enrolled in the study. Respondents noted improvements in physical function with each medication. Overall, respondents reported worse satisfaction with the method of delivery of the intrathecally delivered nusinersen compared to the orally‐delivered risdiplam, but no respondent reported negative overall satisfaction with either medication. A majority (78.6%) of respondents reported that switching from nusinersen to risdiplam was the correct decision.DiscussionThese results suggest that most patients are satisfied when switching from nusinersen to risdiplam, with the method of delivery being a primary factor.

Context.— Machine learning applications in the pathology clinical domain are emerging rapidly. As decision support systems continue to mature, laboratories will increasingly need guidance to evaluate their performance in clinical practice. Currently there are no formal guidelines to assist pathology laboratories in verification and/or validation of such systems. These recommendations are being proposed for the evaluation of machine learning systems in the clinical practice of pathology. Objective.— To propose recommendations for performance evaluation of in vitro diagnostic tests on patient samples that incorporate machine learning as part of the preanalytical, analytical, or postanalytical phases of the laboratory workflow. Topics described include considerations for machine learning model evaluation including risk assessment, predeployment requirements, data sourcing and curation, verification and validation, change control management, human-computer interaction, practitioner training, and competency evaluation. Data Sources.— An expert panel performed a review of the literature, Clinical and Laboratory Standards Institute guidance, and laboratory and government regulatory frameworks. Conclusions.— Review of the literature and existing documents enabled the development of proposed recommendations. This white paper pertains to performance evaluation of machine learning systems intended to be implemented for clinical patient testing. Further studies with real-world clinical data are encouraged to support these proposed recommendations. Performance evaluation of machine learning models is critical to verification and/or validation of in vitro diagnostic tests using machine learning intended for clinical practice.

Abstract Background Alcohol use disorder (AUD) has been associated with the development of neurodegenerative diseases, including Alzheimer's disease (AD). However, recent studies demonstrate that moderate alcohol consumption may be protective against dementia and cognitive decline. Methods We examined astrocyte function, low-density lipoprotein (LDL) receptor-related protein 1 (LRP1), and the NF-κB p65 and IKK-α/β signaling pathways in modulating neuroinflammation and amyloid beta (Aβ) deposition. We assessed apolipoprotein E (ApoE) in the mouse brain using IHC and ELISA in response to moderate ethanol exposure (MEE). First, to confirm the intracerebral distribution of ApoE, we co-stained with GFAP, a marker for astrocytes that biosynthesize ApoE. We sought to investigate whether the ethanol-induced upregulation of LRP1 could potentially inhibit the activity of IL-1β and TNF-α induced IKK-α/β towards NF-κB p65, resulting in a reduction of pro-inflammatory cytokines. To evaluate the actual Aβ load in the brains of APP/PS1 mice, we performed with a specific antibody Aβ (Thioflavin S) on both air- and ethanol-exposed groups, subsequently analyzing Aβ levels. We also measured glucose uptake activity using 18F-FDG in APP/PS1 mice. Finally, we investigated whether MEE induced cognitive and memory changes using the Y maze, noble objective recognition (NOR) test, and Morris water maze (MWM). Results Our findings demonstrate that MEE reduced astrocytic glial fibrillary acidic protein (GFAP) and ApoE levels in the cortex and hippocampus in presymptomatic APP/PS1 mice. Interestingly, increased LRP1 protein expression is accompanied by dampening the IKK-α/β-NF-κB p65 pathway, resulting in decreased IL-1β and TNF-α levels in male mice. Notably, female mice show reduced anti-inflammatory cytokines, IL-4, and IL-10 levels without altering IL-1β and TNF-α concentrations. In both males and females, Aβ plaques, a hallmark of AD, were reduced in the cortex and hippocampus of ethanol-exposed presymptomatic APP/PS1 mice. Consistently, MEE increased fluorodeoxyglucose (FDG)-positron emission tomography (PET)-based brain activities and normalized cognitive and memory deficits in the APP/PS1 mice. Conclusions Our findings suggest that MEE may benefit AD pathology via modulating LRP1 expression, potentially reducing neuroinflammation and attenuating Aβ deposition. Our study implies that reduced astrocyte derived ApoE and LDL cholesterol levels are critical for attenuating AD pathology.