Volumetric computed tomography measurements as predictors for outcomes in a cohort of Fournier's gangrene patients.

PURPOSE: This study evaluates the prognostic value of CT findings, including volumetric measurements, in predicting outcomes for patients with Fournier gangrene (FG), focusing on mortality, ICU admission, hospital stay length, and healthcare costs. METHODS: A retrospective study was conducted on 38 FG patients who underwent CT scans before surgical debridement. We analyzed demographic data, CT volumetric measurements, and clinical outcomes using logistic and linear regression models. RESULTS: No single CT measurement significantly predicted mortality or ICU admission. The best model for mortality prediction included age, air volume, NSTI score, and male sex, with an AUC of 0.911. Intubation likelihood was modeled with an AUC of 0.913 using age, NSTI score, and visceral to subcutaneous fat ratio. The ICU admission model achieved an AUC of 0.677. Hospital stay was predicted by air volume (ß = 0.0002656, p = 0.0505) with an adjusted R-squared of 0.1287. Air volume significantly predicted hospital costs (ß = 2.859, p = 0.00558), resulting in an adjusted R-squared of 0.2165. CONCLUSION: Volumetric CT findings provide valuable prognostic insights for FG patients, suggesting a basis for informed clinical decisions and resource allocation. Further validation in larger, multi-center studies is recommended to develop robust predictive models for FG outcomes.

Pre-test Prediction of Non-ischemic Cardiomyopathies using Time-Series EHR Data.

Clinical imaging is an important diagnostic test to diagnose non-ischemic cardiomyopathies (NICM). However, accurate interpretation of imaging studies often requires readers to review patient histories, a time consuming and tedious task. We propose to use time-series analysis to predict the most likely NICMs using longitudinal electronic health records (EHR) as a pseudo-summary of EHR records. Time-series formatted EHR data can provide temporality information important towards accurate prediction of disease. Specifically, we leverage ICD-10 codes and various recurrent neural network architectures for predictive modeling. We trained our models on a large cohort of NICM patients who underwent cardiac magnetic resonance imaging (CMR) and a smaller cohort undergoing echocardiogram. The performance of the proposed technique achieved good micro-area under the curve (0.8357), F1 score (0.5708) and precision at 3 (0.8078) across all models for cardiac magnetic resonance imaging (CMR) but only moderate performance for transthoracic echocardiogram (TTE) of 0.6938, 0.4399 and 0.5864 respectively. We show that our model has the potential to provide accurate pre-test differential diagnosis, thereby potentially reducing clerical burden on physicians.

Improving routine use of clinical pathway decision support through integration of an EHR with a clinical library resource designed to provide evidence-based guidance within oncology workflows.

BACKGROUND: The rapid evolution, complexity, and specialization of oncology treatment makes it challenging for physicians to provide care based on the latest and best evidence. We hypothesized that physicians would use evidence-based trusted care pathways if they were easy to use and integrated into clinical workflow at the point of care. METHODS: Within a large integrated care delivery system, we assembled clinical experts to define and update drug treatment pathways, encoded them as flowcharts in an online library integrated with the electronic medical record, communicated expectations that clinicians would use these pathways for every eligible patient, and combined data from multiple sources to understand usage over time. RESULTS: We were able to achieve > 75% utilization of eligible protocols ordered through these pathways within two years, with > 90% of individual oncologists having consulted the pathway at least once, despite no requirements or external incentives associated with pathway usage. Feedback from users contributed to improvements and updates to the guidance. CONCLUSIONS: By making our clinical decision support easily accessible and actionable, we find that we have made considerable progress toward our goal of having physicians consult the latest evidence in their treatment decisions.

Physician and Artificial Intelligence Chatbot Responses to Cancer Questions From Social Media.

Importance: Artificial intelligence (AI) chatbots pose the opportunity to draft template responses to patient questions. However, the ability of chatbots to generate responses based on domain-specific knowledge of cancer remains to be tested. Objective: To evaluate the competency of AI chatbots (GPT-3.5 [chatbot 1], GPT-4 [chatbot 2], and Claude AI [chatbot 3]) to generate high-quality, empathetic, and readable responses to patient questions about cancer. Design, Setting, and Participants: This equivalence study compared the AI chatbot responses and responses by 6 verified oncologists to 200 patient questions about cancer from a public online forum. Data were collected on May 31, 2023. Exposures: Random sample of 200 patient questions related to cancer from a public online forum (Reddit r/AskDocs) spanning from January 1, 2018, to May 31, 2023, was posed to 3 AI chatbots. Main Outcomes and Measures: The primary outcomes were pilot ratings of the quality, empathy, and readability on a Likert scale from 1 (very poor) to 5 (very good). Two teams of attending oncology specialists evaluated each response based on pilot measures of quality, empathy, and readability in triplicate. The secondary outcome was readability assessed using Flesch-Kincaid Grade Level. Results: Responses to 200 questions generated by chatbot 3, the best-performing AI chatbot, were rated consistently higher in overall measures of quality (mean, 3.56 [95% CI, 3.48-3.63] vs 3.00 [95% CI, 2.91-3.09]; P < .001), empathy (mean, 3.62 [95% CI, 3.53-3.70] vs 2.43 [95% CI, 2.32-2.53]; P < .001), and readability (mean, 3.79 [95% CI, 3.72-3.87] vs 3.07 [95% CI, 3.00-3.15]; P < .001) compared with physician responses. The mean Flesch-Kincaid Grade Level of physician responses (mean, 10.11 [95% CI, 9.21-11.03]) was not significantly different from chatbot 3 responses (mean, 10.31 [95% CI, 9.89-10.72]; P > .99) but was lower than those from chatbot 1 (mean, 12.33 [95% CI, 11.84-12.83]; P < .001) and chatbot 2 (mean, 11.32 [95% CI, 11.05-11.79]; P = .01). Conclusions and Relevance: The findings of this study suggest that chatbots can generate quality, empathetic, and readable responses to patient questions comparable to physician responses sourced from an online forum. Further research is required to assess the scope, process integration, and patient and physician outcomes of chatbot-facilitated interactions.

Ethical frameworks of informed consent in the age of pediatric precision medicine.

Precision medicine is an emergent medical paradigm that uses information technology to inform the use of targeted therapies and treatments. One of the first steps of precision medicine involves acquiring the patient's informed consent to protect their rights to autonomous medical decision-making. In pediatrics, there exists mixed recommendations and guidelines of consent-related practices designed to safeguard pediatric patient interests while protecting their autonomy. Here, we provide a high-level, clinical primer of (1) ethical informed consent frameworks widely used in clinical practice and (2) promising modern adaptations to improve informed consent practices in pediatric precision medicine. Given the rapid scientific advances and adoption of precision medicine, we highlight the dual need to both consider the clinical implementation of consent in pediatric precision medicine workflows as well as build rapport with pediatric patients and their substitute decision-makers working alongside interdisciplinary health teams.

Robotic transversus abdominis release using HUGO RAS system: our initial experience.

BACKGROUND: Transversus abdominis release (TAR) is an effective technique for treating large midline and off-midline hernias. Recent studies have demonstrated that robotic TAR (rTAR) is technically feasible and associated with improved outcomes compared to open surgery. There is no published experience to date describing abdominal wall reconstruction using the novel robotic platform HUGO RAS System (Medtronic®). METHODS: All consecutive patients who underwent a rTAR in our institution were included. Three of the four arm carts of the HUGO RAS System were used at any given time. Each arm configuration was defined by our team in conjunction with Medtronic® personnel. rTAR was performed as previously described. Upon completion of the TAR on one side, a redocking process with different, mirrored arms angles was performed to continue with the contralateral TAR. Operative variables and early morbidity were recorded. RESULTS: Ten patients were included in this study. The median BMI was 31 (21-40.6) kg/m2. The median height was 1.6 m (1.5-1.89 m). A trend of decreased operative time, console time, and redocking time was seen in these consecutive cases. No intraoperative events nor postoperative morbidity was reported. The median length of stay was 3 (1-6) days. CONCLUSION: Robotic TAR utilizing the HUGO RAS system is a feasible and safe procedure. The adoption of this procedure on this novel platform for the treatment of complex abdominal wall hernias has been successful for our team.

Ambient mass spectrometry imaging of food natural products by angled direct analysis in real time high-resolution mass spectrometry.

Direct surface analysis in ambient conditions provides information on the position and chemical composition of an object at the time of investigation. An angled sampling probe is developed in this work for direct analysis in real time (DART) ionization high-resolution mass spectrometry. The DART ion source and the interface were modified for improved surface resolution, increased ion transfer efficiency, as well as enabling two-dimensional surface scanning. The angled probe DART-MS system was used for investigating a variety of food samples including fruit peels, ginseng root, plant leaves and sections of radish. Abundant signals and distinct chemical profiles are obtained in seconds, and spatial distribution of different molecules across the sample surfaces can be observed. In addition, the developed system can quickly identify the chemical changes when the surfaces were treated. The method is capable of directly evaluating food sample surfaces with different shapes, hardness, and conditions, without any sample pretreatments.

Simultaneous quantification of six proteins related to liver injury using nano liquid chromatography-tandem mass spectrometry.

RATIONALE: In clinical diagnosis of liver injury, which is an important health concern, serum aminotransferase assays have been the go-to method used worldwide. However, the measurement of serum enzyme activity has limitations, including inadequate disease specificity and enzyme specificity. METHODS: With the high selectivity and specificity provided by nano liquid chromatography-tandem mass spectrometry (LC/MS/MS), this work describes a method for the simultaneous determination of six proteins in liver that can be potentially used as biomarkers for liver injury: glutamic-pyruvic transaminase 1 (GPT1), glutamic oxaloacetic transaminase 1 (GOT1), methionine adenosyl transferase 1A (MAT1A), glutathione peroxidase 1 (GPX1), cytokeratin 18 (KRT18) and apolipoprotein E (APOE). RESULTS: In validation, the method was shown to have good selectivity and sensitivity (limits of detection at pg/mL level). The analytical method revealed that, compared with normal mice, in carbon tetrachloride-induced acute liver injury mice, liver MAT1A and GPX1 were significantly lower (p < 0.01 and p < 0.05, respectively), KRT18 was significantly higher (p < 0.05) and APOE and GPT1 were marginally significantly lower (p between 0.05 and 0.1). This is the first work reporting the absolute contents of GPT1, GOT1, MAT1A, GPX1 and KRT18 proteins based on LC/MS. CONCLUSIONS: The proposed method provides a basis for establishing more specific diagnostic indicators of liver injury.

Mapping single-cell developmental potential in health and disease with interpretable deep learning.

Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of cell fate in developmental systems. However, identifying the molecular hallmarks of potency - the capacity of a cell to differentiate into other cell types - has remained challenging. Here, we introduce CytoTRACE 2, an interpretable deep learning framework for characterizing potency and differentiation states on an absolute scale from scRNA-seq data. Across 31 human and mouse scRNA-seq datasets encompassing 28 tissue types, CytoTRACE 2 outperformed existing methods for recovering experimentally determined potency levels and differentiation states covering the entire range of cellular ontogeny. Moreover, it reconstructed the temporal hierarchy of mouse embryogenesis across 62 timepoints; identified pan-tissue expression programs that discriminate major potency levels; and facilitated discovery of cellular phenotypes in cancer linked to survival and immunotherapy resistance. Our results illuminate a fundamental feature of cell biology and provide a broadly applicable platform for delineating single-cell differentiation landscapes in health and disease.

The Impact of potential 'confounders' on the diagnostic sensitivity of circulating free DNA in management of FIT+ patients: a pilot study.

Cell-free DNA (cfDNA) has long been established as a useful diagnostic and prognostic tool in a variety of clinical settings, ranging from infectious to cardiovascular and neoplastic diseases. However, non-neoplastic diseases can act as confounders impacting on the amount of cfDNA shed in bloodstream and on technical feasibility of tumour derived free circulating nucleic acids selecting patients with cancer. Here, we investigated the potential impact of other pathological processes in the clinical stratification of 637 FIT+ patients. A single and multiple logistic regression yielded similar results. Crude sensitivity was 75.9% versus adjusted sensitivity of 74.1%, relative risk 0.9761 (0.8516 to 1.1188), risk difference 0.0181 (-0.0835 to 0.1199) and OR 0.9079 (0.5264 to 1.5658). Potential confounding effect from other source of cfDNA plays a pivotal role in the clinical stratification of FIT+ patients.

Biomedical text readability after hypernym substitution with fine-tuned large language models.

The advent of patient access to complex medical information online has highlighted the need for simplification of biomedical text to improve patient understanding and engagement in taking ownership of their health. However, comprehension of biomedical text remains a difficult task due to the need for domain-specific expertise. We aimed to study the simplification of biomedical text via large language models (LLMs) commonly used for general natural language processing tasks involve text comprehension, summarization, generation, and prediction of new text from prompts. Specifically, we finetuned three variants of large language models to perform substitutions of complex words and word phrases in biomedical text with a related hypernym. The output of the text substitution process using LLMs was evaluated by comparing the pre- and post-substitution texts using four readability metrics and two measures of sentence complexity. A sample of 1,000 biomedical definitions in the National Library of Medicine's Unified Medical Language System (UMLS) was processed with three LLM approaches, and each showed an improvement in readability and sentence complexity after hypernym substitution. Readability scores were translated from a pre-processed collegiate reading level to a post-processed US high-school level. Comparison between the three LLMs showed that the GPT-J-6b approach had the best improvement in measures of sentence complexity. This study demonstrates the merit of hypernym substitution to improve readability of complex biomedical text for the public and highlights the use case for fine-tuning open-access large language models for biomedical natural language processing.

Role of diverting colostomy and reconstruction in managing Fournier's gangrene-a narrative review.

OBJECTIVE: To examine the role of bowel diversion and reconstructive surgeries in managing Fournier's gangrene (FG) to facilitate multidisciplinary collaboration between urologists, colorectal and plastic surgery teams. METHODS: A review of the literature was conducted using the databases Medline, Embase, PubMed in June 2023. The review included studies that evaluated the outcomes of FG following reconstructive surgeries or diverting colostomies. RESULTS: The existing evidence suggests that bowel diversion and colostomy formation could reduce the need for further debridement, shorten the time to wound healing, and facilitate skin graft or flap uptake in patients with FG. Additionally, the psychological impact of a stoma was shown not to be a major concern for patients. However, stoma carries a risk of perioperative complications and therefore may prolong the length of hospital stay. In reviewing the evidence for reconstruction in FG, large and deep defects seem to benefit from skin grafts or flaps. Noticeably, burial of testicles in thigh pockets has grown out of favour due to concerns regarding the thermoregulation of the testicles and the psychological impact on patients. CONCLUSION: The use of bowel diversion and reconstructive surgeries in managing FG is case dependent. Therefore, it is important to have close discussions with colorectal and plastic surgery teams when managing FG.

Validity and reliability study of a novel surface electromyography sensor using a well-consolidated electromyography system in individuals with cervical spinal cord injury.

STUDY DESIGN: Non-interventional, cross-sectional pilot study. OBJECTIVES: To establish the validity and reliability of the BioStamp nPoint biosensor (Medidata Solutions, New York, NY, USA [formerly MC10, Inc.]) for measuring electromyography in individuals with cervical spinal cord injury (SCI) by comparing the surface electromyography (sEMG) metrics with the Trigno wireless electromyography system (Delsys, Natick, MA, USA). SETTING: Participants were recruited from the Shirley Ryan AbilityLab registry. METHODS: Individuals aged 18-70 years with cervical SCI were evaluated with the two biosensors to capture activity on upper-extremity muscles during two study sessions conducted over 2 days (day 1-consent alone; day 2-two data collections in same session). Time and frequency metrics were captured, and signal-to-noise ratio was determined for each muscle group. Test-retest reliability was determined using Pearson's correlation. Validation of the BioStamp nPoint system was based on Bland-Altmann analysis. RESULTS: Among the 11 participants, 30.8% had subacute cervical injury at C5-C6; 53.8% were injured within 1 year of the study. Results from the test-retest reliability assessment revealed that most Pearson's correlations between the two sensory measurements were strong (≥0.50). The Bland-Altman analysis found values of the signal-to-noise ratio, frequency, and peak amplitude were within the level of agreement. Signal-to-noise ratios ranged from 7.06 to 22.1. CONCLUSIONS: In most instances, the performance of the BioStamp nPoint sensors was moderately to strongly correlated with that of the Trigno sensors in all muscle groups tested. The BioStamp nPoint system is a valid and reliable approach to assess sEMG measures in individuals with cervical SCI. SPONSORSHIP: The present study was supported by AbbVie Inc.

Mutational signature-based identification of DNA repair deficient gastroesophageal adenocarcinomas for therapeutic targeting.

Homologous recombination (HR) and nucleotide excision repair (NER) are the two most frequently disabled DNA repair pathways in cancer. HR-deficient breast, ovarian, pancreatic and prostate cancers respond well to platinum chemotherapy and PARP inhibitors. However, the frequency of HR deficiency in gastric and esophageal adenocarcinoma (GEA) still lacks diagnostic and functional validation. Using whole exome and genome sequencing data, we found that a significant subset of GEA, but very few colorectal adenocarcinomas, show evidence of HR deficiency by mutational signature analysis (HRD score). High HRD gastric cancer cell lines demonstrated functional HR deficiency by RAD51 foci assay and increased sensitivity to platinum chemotherapy and PARP inhibitors. Of clinical relevance, analysis of three different GEA patient cohorts demonstrated that platinum treated HR deficient cancers had better outcomes. A gastric cancer cell line with strong sensitivity to cisplatin showed HR proficiency but exhibited NER deficiency by two photoproduct repair assays. Single-cell RNA-sequencing revealed that, in addition to inducing apoptosis, cisplatin treatment triggered ferroptosis in a NER-deficient gastric cancer, validated by intracellular GSH assay. Overall, our study provides preclinical evidence that a subset of GEAs harbor genomic features of HR and NER deficiency and may therefore benefit from platinum chemotherapy and PARP inhibitors.

Femtosecond laser-assisted cataract surgery for complex cataracts - A review.

Since its inception in 2009, femtosecond laser-assisted cataract surgery (FLACS) has become an alternative to conventional phacoemulsification cataract surgery (CPCS). Clinical studies were unable to demonstrate superior visual outcomes, but revealed reduced endothelial cell loss. More recently, the cost-effectiveness of FLACS over CPCS in routine cataract surgeries has been challenged. However, the unique abilities of FLACS to customize anterior capsulotomies precisely, soften and fragment the nucleus without capsular bag stress, and create corneal incisions may have special utility in complex cataract and less-common scenarios. In this article, we review the unique role of FLACS in complex cataract surgeries and how it could play a role to improve the safety and predictability of nonroutine cataract surgery.