Citations

Abstract Background The Mayo endoscopic subscore (MES) is an important quantitative measure of disease activity in ulcerative colitis. Colonoscopy reports in routine clinical care usually characterize ulcerative colitis disease activity using free text description, limiting their utility for clinical research and quality improvement. We sought to develop algorithms to classify colonoscopy reports according to their MES. Methods We annotated 500 colonoscopy reports from 2 health systems. We trained and evaluated 4 classes of algorithms. Our primary outcome was accuracy in identifying scorable reports (binary) and assigning an MES (ordinal). Secondary outcomes included learning efficiency, generalizability, and fairness. Results Automated machine learning models achieved 98% and 97% accuracy on the binary and ordinal prediction tasks, outperforming other models. Binary models trained on the University of California, San Francisco data alone maintained accuracy (96%) on validation data from Zuckerberg San Francisco General. When using 80% of the training data, models remained accurate for the binary task (97% [n = 320]) but lost accuracy on the ordinal task (67% [n = 194]). We found no evidence of bias by gender (P = .65) or area deprivation index (P = .80). Conclusions We derived a highly accurate pair of models capable of classifying reports by their MES and recognizing when to abstain from prediction. Our models were generalizable on outside institution validation. There was no evidence of algorithmic bias. Our methods have the potential to enable retrospective studies of treatment effectiveness, prospective identification of patients meeting study criteria, and quality improvement efforts in inflammatory bowel diseases.

We aimed to review the molecular characteristics of metastatic melanoma and the role of surgery in metastasectomy for metastatic melanoma. We performed a systematic literature search on PubMed to identify relevant studies focusing on several mutations, including NRAS, BRAF, NF1, MITF, PTEN, TP53, CDKN2A, TERT, TMB, EGFR, and c-KIT. This was performed in the context of metastatic melanoma and the role of metastasectomy in the metastatic melanoma population. A comprehensive review of these molecular characteristics is presented with a focus on their prognosis and role in surgical metastasectomy.

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder worldwide and progresses to end-stage renal disease (ESRD). However, its precise mechanism is not fully understood. In recent years, epigenetic reprogramming has drawn increasing attention regarding its effect on cyst growth. However, considering the complexity of epigenetic mechanisms and the broad range of alterations of epigenetic components in ADPKD, identifying more specific epigenetic factors and understanding how they are mechanistically linked to promote cyst growth is relevant for the development of treatment for ADPKD. Here, we find that the histone methyltransferase SMYD3, which activates gene transcription via histone H3 lysine 4 trimethylation (H3K4me3), is upregulated in PKD1 mutant mouse and human ADPKD kidneys. Genetic knockout of SMYD3 in a PKD1 knockout mouse model delayed cyst growth and improved kidney function compared with PKD1 single knockout mouse kidneys. Immunostaining and Western blot assays indicated that SMYD3 regulated PKD1-associated signaling pathways associated with proliferation, apoptosis, and cell cycle effectors in PKD1 mutant renal epithelial cells and tissues. In addition, we found that SMYD3 localized to the centrosome and regulated mitosis and cytokinesis via methylation of α-tubulin at lysine 40. In addition, SMYD3 regulated primary cilia assembly in PKD1 mutant mouse kidneys. In summary, our results demonstrate that overexpression of SMYD3 contributes to cyst progression and suggests targeting SMYD3 as a potential therapeutic strategy for ADPKD.

Complex structural chromosome abnormalities such as chromoanagenesis have been reported in acute myeloid leukemia (AML). They are usually not well characterized by conventional genetic methods, and the characterization of chromoanagenesis structural abnormalities from short-read sequencing still presents challenges. Here, we characterized complex structural abnormalities involving chromosomes 2, 3, and 7 in an AML patient using an integrated approach including CRISPR/Cas9-mediated nanopore sequencing, mate pair sequencing (MPseq), and SNP microarray analysis along with cytogenetic methods. SNP microarray analysis revealed chromoanagenesis involving chromosomes 3 and 7, and a pseudotricentric chromosome 7 was revealed by cytogenetic methods. MPseq revealed 138 structural variants (SVs) as putative junctions of complex rearrangements involving chromosomes 2, 3, and 7, which led to 16 novel gene fusions and 33 truncated genes. Thirty CRISPR RNA (crRNA) sequences were designed to map 29 SVs, of which 27 (93.1%) were on-target based on CRISPR/Cas9 crRNA nanopore sequencing. In addition to simple SVs, complex SVs involving over two breakpoints were also revealed. Twenty-one SVs (77.8% of the on-target SVs) were also revealed by MPseq with shared SV breakpoints. Approximately three-quarters of breakpoints were located within genes, especially intronic regions, and one-quarter of breakpoints were intergenic. Alu and LINE repeat elements were frequent among breakpoints. Amplification of the chromosome 7 centromere was also detected by nanopore sequencing. Given the high amplification of the chromosome 7 centromere, extra chromosome 7 centromere sequences (tricentric), and more gains than losses of genomic material, chromoanasynthesis and chromothripsis may be responsible for forming this highly complex structural abnormality. We showed this combination approach’s value in characterizing complex structural abnormalities for clinical and research applications. Characterization of these complex structural chromosome abnormalities not only will help understand the molecular mechanisms responsible for the process of chromoanagenesis, but also may identify specific molecular targets and their impact on therapy and overall survival.

Abstract Background The electronic health record (EHR) presents new opportunities for the timely identification of patients at high risk of critical illness and the implementation of preventive strategies. This study aims to externally validate an EHR‐based Elders Risk Assessment (ERA) score to identify older patients at high risk of future critical illness during a primary care visit. Methods This historical cohort study included patients aged ≥65 years who had primary care visits at Mayo Clinic Rochester, MN, between July 2019 and December 2021. The ERA score at the time of the primary care visit was used to predict critical illness, defined as death or ICU admission within 1 year of the visit. Results A total of 12,885 patients were included in the analysis. The median age at the time of the primary care visit was 75 years, with 44.6% being male. 93.7% of participants were White, and 64.2% were married. The median (25th, 75th percentile) ERA score was 4 (0, 9). 11.3% of study participants were admitted to the ICU or died within 1 year of the visit. The ERA score predicted critical illness within 1 year of a primary care visit with an area under the receiver operating characteristic curve of 0.84 (95% CI 0.83–0.85), which indicates good discrimination. An ERA score of 9 was identified as optimal for implementing and testing potential preventive strategies, with the odds ratio of having the primary outcome in patients with ERA score ≥9 being 11.33 (95%CI 9.98–12.87). Conclusions This simple EHR‐based risk assessment model can predict critical illness within 1 year of primary care visits in older patients. The findings of this study can serve as a basis for testing and implementation of preventive strategies to promote the well‐being of older adults at risk of critical illness and its consequences.

ObjectivesRacial disparities are pervasive in access to pediatric surgery. The goal of this study was to test the hypotheses that, compared with White children, non‐White and Hispanic children: (1) were less likely to attend evaluations by otolaryngologists after a diagnosis of otitis media (OM) eligible for surgical referral, and (2) these children were less likely to receive tympanostomy tube (TT) after surgical consultation.MethodsThe OptumLabs Data Warehouse is a de‐identified claims database of privately insured enrollees. Guidelines on the management of OMs suggest that children should be evaluated for surgery if they have recurrent acute OM or chronic OM with effusion. A cohort of children who were diagnosed with OM were constructed. For Hypothesis 1, the primary outcome was otolaryngology office visit within 6 months of a diagnosis of recurrent or chronic OM. For Hypothesis 2, the outcome was TT placement within 6 months following the otolaryngology office visit. Cox regression models were used to determine the relationship between race/ethnicity and the primary outcomes.ResultsAmong 187,776 children with OMs, 72,774 (38.8%) had otolaryngology visits. In a multivariate Cox model, the hazard ratios of attending otolaryngology visit for Black, Hispanic, and Asian children were 0.93 (95% CI,0.90, 0.96), 0.86 (0.83, 0.88), and 0.74 (0.71, 0.77), compared with White children. Among the children evaluated by otolaryngologists, 46,554 (63.97%) received TT. Black, Hispanic, and Asian children with recurrent acute OM had lower likelihood of receiving TT.ConclusionsRacial disparities in attending otolaryngology office visit contributed to the disparities in receiving TT.Quality of EvidenceLevel 3 Laryngoscope, 134:3846–3852, 2024

Defecation function is negatively impacted in patients with neurogenic bowel dysfunction (NBD), who require effective bowel care for stool evacuation. NBD comprises fecal incontinence and/or constipation, which can reduce the quality of life and dignity. Transanal irrigation (TAI) is recommended by several clinical guidelines as the second-line treatment after conservative treatment and before surgical options are considered. As the only class in the second-line treatment with an established safety and efficacy profile, the mechanism of action of TAI has not fully been elucidated when administered through a rectal catheter with a balloon. This review examines the current understanding regarding the mechanism of action of TAI, with a focus on the pathophysiology of neurogenic bowel and irregular defecation. By understanding the functional implications of TAI, clinicians may be better able to integrate this modality into bowel care programs, especially for patients with NBD who have significant constipation due to delayed colonic motility and impaired stool emptying with loss of voluntary control of defecation, and those who are unresponsive to conservative treatment, including enemas.

Abstract Aim The morphometry of sural nerve biopsies, such as fibre diameter and myelin thickness, helps us understand the underlying mechanism of peripheral neuropathies. However, in current clinical practice, only a portion of the specimen is measured manually because of its labour‐intensive nature. In this study, we aimed to develop a machine learning‐based application that inputs a whole slide image (WSI) of the biopsied sural nerve and automatically performs morphometric analyses. Methods Our application consists of three supervised learning models: (1) nerve fascicle instance segmentation, (2) myelinated fibre detection and (3) myelin sheath segmentation. We fine‐tuned these models using 86 toluidine blue‐stained slides from various neuropathies and developed an open‐source Python library. Results Performance evaluation showed (1) a mask average precision (AP) of 0.861 for fascicle segmentation, (2) box AP of 0.711 for fibre detection and (3) a mean intersection over union (mIoU) of 0.817 for myelin segmentation. Our software identified 323,298 nerve fibres and 782 fascicles in 70 WSIs. Small and large fibre populations were objectively determined based on clustering analysis. The demyelination group had large fibres with thinner myelin sheaths and higher g‐ratios than the vasculitis group. The slope of the regression line from the scatter plots of the diameters and g‐ratios was higher in the demyelination group than in the vasculitis group. Conclusion We developed an application that performs whole slide morphometry of human biopsy samples. Our open‐source software can be used by clinicians and pathologists without specific machine learning skills, which we expect will facilitate data‐driven analysis of sural nerve biopsies for a more detailed understanding of these diseases.