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Computer-Aided Polyp Detection Increases Adenoma Detection Tate in a High Adenoma Detecting Group: A Multi-Site Community Practice Experience
No full textInstitutions: Tower Health, USA; U.S. Digestive Health, USA. Disclosure compliance: I understand. Participant disclosure: Parth Desai: NO financial relationship with a commercial interest; Nicholas Giordano: NO financial relationship with a commercial interest; Thomas Wasser: NO financial relationship with a commercial interest; Dale Whitebloom: NO financial relationship with a commercial interest; Nirav Shah: Speaking and Teaching: Medtronic. Introduction: Real-time computer-aided polyp detection (CADe) systems have demonstrated efficacy in increasing adenoma detection rates (ADR) during colonoscopy in randomized controlled trials. Subsequent real-world studies of CADe systems, from tertiary centers, have demonstrated similar ADR in CADe and non-CADe groups. However there remains a paucity of data on the benefit of CADe systems in community-based practice. This retrospective observational study evaluates the influence of CADe system implementation on ADR in a high ADR-detecting community-based gastroenterology practice. Methods: Colonoscopy data performed by 40 gastroenterologists from two ambulatory surgery centers was extracted from the GIQuIC database. Data was compared from before and after CADe implementation time periods: June 2021 through March 2022 (pre-CADe) and September 2022 through June 2023 (post-CADe). Exclusion criteria included colonoscopies performed on patients under age 40 or history of inflammatory bowel disease and those performed by gastroenterologists who opted out of CADe use. Baseline characteristics including age, gender, race, insurance, and risk assessment were analyzed in pre- and post-CADe groups. ADR, advanced adenoma detection rate, and sessile serrated adenoma detection rates were compared pre- and post-CADe implementation. Chi-squared tests were used for categorical variables and T-tests for continuous variables. Results: A total 37,975 colonoscopies were analyzed (pre-CADe, n=15,298; post-CADe, n=22,677). There was a similar distribution of males in the pre- and post-CADe groups (47.3% vs 46.7%, p=0.215). There was a statistically significant but clinically minute difference in the distribution of white compared with non-white patients between the periods (87.3 vs 85.7, p\u3c0.001). There were more high-neoplasm risk patients in the pre-CADe period (53.9% vs 48.4%). ADR increased from the pre- to post-CADe periods (43.5% vs. 47%, p\u3c0.001) across all endoscopists, an 8% relative rate increase. Advanced neoplasms (defined as size ≥ 10mm, high grade dysplasia or villous component) were similar between the two groups (6.7% vs 6.8%, p=0.535). Serrated adenoma detection was diminutively higher in the pre-CADe group (12.0% vs 11.2%, 0.021). Withdrawal time was similar between the pre- and post-CADe groups (10.57 vs 10.61 minutes, p=0.414). Conclusion: Post-CADe implementation was associated with increased ADR within this multi-site analysis, despite a lower proportion of high neoplasm risk patients compared with the pre-CADe group. Although baseline ADR surpassed the national mean of 39% at 43.5%, the post-CADe implementation ADR improved to 47%. High adenoma detecting community practice groups may increase ADR through use of CADe systems. Further studies are needed to assess how CADe systems affect colon cancer-related mortality and morbidity outcomes. [Formula presented] [Formula presented
Exploring the Unknown: Appreciating the Challenges of Non-compaction Cardiomyopathy.
No full textLeft ventricular non-compaction cardiomyopathy (LVNC), or non-compaction cardiomyopathy (NCCM), is defined by pronounced left ventricular trabeculations and deep intertrabecular recesses connecting with the ventricular cavity. Patients with NCCM can be asymptomatic or have severe complications, including heart failure, arrhythmias, thromboembolism, and sudden cardiac death. Our case discusses a patient with shortness of breath who was found to have a newly decreased ejection fraction. The workup revealed non-ischemic cardiomyopathy and cardiac MRI showed hyper-trabeculations consistent with NCCM. The patient was started on oral anticoagulation and guideline-directed medical therapy (GDMT) and discharged with an event monitor. NCCM stands as a relatively rare and enigmatic condition, often veiled in ambiguity. The absence of standardized diagnostic and management protocols further complicates its clinical landscape. While echocardiography is the primary diagnostic tool, its tendency for under-diagnosis poses a significant challenge. Conversely, advanced imaging modalities like cardiac MRI may lead to instances of overdiagnosis. Treatment approaches are non-specific, incorporating GDMT, anticoagulation, implantable cardioverter-defibrillator placement, and genetic testing paired with counseling. Prioritizing genetic research is crucial to uncover tailored therapeutic interventions. Establishing consensus guidelines and refining diagnostic accuracy are pivotal steps toward mitigating the risks associated with under and over-diagnosis
Hot and Achy : A Case of an Extensive Spinal Epidural Abscess.
No full textWe present a case of a 94-year-old female who presented to the emergency room with a fever and generalized weakness without an initial obvious source of infection. Throughout admission, she continued to be febrile despite broad-spectrum antibiotics. Several days into admission, the patient complained of severe back pain, necessitating magnetic resonance imaging (MRI) of the entire spine. The imaging revealed an extensive epidural fluid collection consistent with a spinal epidural abscess. Fortunately, she did not have any neurological deficits and was treated conservatively with IV antibiotics with improvement. This case highlights this rare presentation and the importance of early diagnosis and management of spinal epidural abscesses
Opioid Use in Pelvic Fractures: The Impact of Opioid Prescribing Laws in Pennsylvania.
No full textPennsylvania\u27s Prescription Drug Monitoring Program (PDMP) was established in 2016, but its impact on opioid use for pelvic fractures is understudied. We compared opioid use in 277 pelvic fracture cases between two periods: 2015-2017 (T1) and 2018-2020 (T2). Outcomes included daily inpatient morphine milligram equivalents (MME), long-term opioid use (LOU) 60-90 days post-discharge, and intermediate-term opioid use (IOU) 30-60 days post-discharge. T1 and T2 had comparable baseline characteristics. T2 was associated with a decrease in average daily inpatient MME (58.6 vs 78.5
Role of Machine Learning and Artificial Intelligence in Arrhythmias and Electrophysiology.
No full textMachine learning (ML), a subset of artificial intelligence (AI) centered on machines learning from extensive datasets, stands at the forefront of a technological revolution shaping various facets of society. Cardiovascular medicine has emerged as a key domain for ML applications, with considerable efforts to integrate these innovations into routine clinical practice. Within cardiac electrophysiology, ML applications, especially in the automated interpretation of electrocardiograms, have garnered substantial attention in existing literature. However, less recognized are the diverse applications of ML in cardiac electrophysiology and arrhythmias, spanning basic science research on arrhythmia mechanisms, both experimental and computational, as well as contributions to enhanced techniques for mapping cardiac electrical function and translational research related to arrhythmia management. This comprehensive review delves into various ML applications within the scope of this journal, organized into 3 parts. The first section provides a fundamental understanding of general ML principles and methodologies, serving as a foundational resource for readers interested in exploring ML applications in arrhythmia research. The second part offers an in-depth review of studies in arrhythmia and electrophysiology that leverage ML methodologies, showcasing the broad potential of ML approaches. Each subject is thoroughly outlined, accompanied by a review of notable ML research advancements. Finally, the review delves into the primary challenges and future perspectives surrounding ML-driven cardiac electrophysiology and arrhythmias research
Infertility and risk of postmenopausal breast cancer in the women\u27s health initiative.
No full textPURPOSE: Although infertility (i.e., failure to conceive after ≥ 12 months of trying) is strongly correlated with established breast cancer risk factors (e.g., nulliparity, number of pregnancies, and age at first pregnancy), its association with breast cancer incidence is not fully understood. Previous studies were primarily small clinic-based or registry studies with short follow-up and predominantly focused on premenopausal breast cancer. The objective of this study was to assess the relationship between infertility and postmenopausal breast cancer risk among participants in the Women\u27s Health Initiative (analytic sample = 131,784; \u3e 25 years of follow-up).
METHODS: At study entry, participants were asked about their pregnancy history, infertility history, and diagnosed reasons for infertility. Incident breast cancers were self-reported with adjudication by trained physicians reviewing medical records. Cox proportional hazards models were used to estimate risk of incident postmenopausal breast cancer for women with infertility (overall and specific infertility diagnoses) compared to parous women with no history of infertility. We examined mediation of these associations by parity, age at first term pregnancy, postmenopausal hormone therapy use at baseline, age at menopause, breastfeeding, and oophorectomy.
RESULTS: We observed a modest association between infertility (n = 23,406) and risk of postmenopausal breast cancer (HR = 1.07; 95% CI 1.02-1.13). The association was largely mediated by age at first term pregnancy (natural indirect effect: 46.4% mediated, CI 12.2-84.3%).
CONCLUSION: These findings suggest that infertility may be modestly associated with future risk of postmenopausal breast cancer due to age at first pregnancy and highlight the importance of incorporating reproductive history across the life course into breast cancer analyses
Knowing Your Patient Population: Techniques to Capture Infants at High Risk for Physical Abuse in a Trauma Registry.
No full textBACKGROUND: Physical abuse is a major public health concern and a leading cause of morbidity and mortality in infants. Clinical decision tools derived from trauma registries can facilitate timely risk-stratification. The Trauma Quality Improvement Program (TQIP) database does not report age for childrenage.
METHODS: Patients ≤17 years were identified from TQIP (2017-2019). The primary outcomes included injuries resulting from confirmed or suspected child abuse captured by diagnosis codes or report/investigation of physical abuse, or different caregiver at discharge available in TQIP. We used two methods to select infants within TQIP. In the first, World Health Organization (WHO) growth standards for stature or length-for-age and weight-for-age were selected to capture children younger than 1 year. In the second, a K-means machine learning algorithm was used to cluster patients by weight and height. We compared outcome and injury data with and without patientsyear.
RESULTS: Using the WHO growth standard 19,916 children20,513 patients had a report of physical abuse filed, and 9393 were infants[95% CI] were seen for fractures of the upper limb (1.28 [1.22-1.34]), vertebrae (1.89 [1.68-2.13]), ribs (5.2 [4.8-5.63]), and spinal cord (3.39 [2.85-4.02]) and head injuries (1.55 [1.5-1.6]) with infants included.
CONCLUSIONS: In a nationwide trauma registry, WHO growth standards can be used to capture patients under one year who are more adversely impacted by maltreatment.
TYPE OF STUDY: Retrospective, Cross-sectional.
LEVEL OF EVIDENCE: Level III, Diagnostic
The prevalence and predictors of metabolic dysfunction-associated steatotic liver disease and fibrosis/cirrhosis among adolescents/young adults.
No full textOBJECTIVES: We investigated the current prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) and fibrosis/cirrhosis and identified at-risk populations for MASLD and MASLD-related fibrosis among US adolescents and young adults in the United States.
METHODS: Utilizing the National Health and Nutrition Examination Survey 2017-2020, the prevalence of MASLD and fibrosis/cirrhosis was assessed via controlled attenuation parameter (CAP) score and liver stiffness measurements by transient elastography in participants aged 12-29 years with at least one cardiometabolic criteria and absence of other chronic liver disease. Multivariable logistic regression was performed to determine predictors of MASLD and MASLD-related fibrosis.
RESULTS: The overall prevalence of MASLD was 23.9% (95% confidence interval [CI]: 21.3-26.5 for CAP ≥ 263 dB/m) and 17.3% (95% CI: 14.7-20.0 for ≥285 dB/m), respectively. The prevalence of fibrosis and cirrhosis in MASLD was 11.0% and 3.1%, respectively. When categorized by age, the prevalence of MASLD varied from 16.8% (of which 6.2% [fibrosis], 1.8% [cirrhosis]) in early and middle adolescents (12-17 years), to 25.5% (11.8% [fibrosis], 4.8% [cirrhosis]) in late adolescents and young adults (18-24 years), and to 30.4% (of which 13.2% [fibrosis] and 2.1% [cirrhosis]) in older young adults (25-29 years). The independent predictors for MASLD included male sex, Hispanic, non-Hispanic Asian, body mass index, and low HDL-cholesterol. In contrast, diabetes and body mass index were associated with an increased risk of fibrosis in individuals with MASLD.
CONCLUSIONS: The prevalence of MASLD and related fibrosis in adolescents and young adults in the United States has reached a significant level, with a substantial proportion of cirrhosis
Scanning the aged to minimize missed injury: An EAST multicenter study.
No full textBACKGROUND: Despite the high incidence of blunt trauma in older adults, there is a lack of evidence-based guidance for computed tomography (CT) imaging in this population. We aimed to identify an algorithm to guide use of a Pan-Scan (Head/C-spine/Torso) or a Selective Scan (Head/C-spine ± Torso). We hypothesized that a patient\u27s initial history and exam could be used to guide imaging.
METHODS: We prospectively studied blunt trauma patients aged 65+ at 18 Level I/II trauma centers. Patients presenting \u3e24 h after injury or who died upon arrival were excluded. We collected history and physical elements and final injury diagnoses. Injury diagnoses were categorized into CT body regions of Head/C-spine or Torso (chest, abdomen/pelvis, and T/L spine). Using machine learning and regression modeling as well as a priori clinical algorithms based, we tested various decision rules against our dataset. Our priority was to identify a simple rule which could be applied at the bedside, maximizing sensitivity (Sens) and negative predictive value (NPV) to minimize missed injuries.
RESULTS: We enrolled 5,498 patients with 3,082 injuries. Nearly half (47.1%, n = 2,587) had an injury within the defined CT body regions. No rule to guide a Pan-Scan could be identified with suitable Sens/NPV for clinical use. A clinical algorithm to identify patients for Pan-Scan, using a combination of physical exam findings and specific high-risk criteria, was identified and had a Sens of 0.94 and NPV of 0.86 This rule would have identified injuries in all but 90 patients (1.6%) and would theoretically spare 11.9% (655) of blunt trauma patients a torso CT.
CONCLUSIONS: Our findings advocate for Head/Cspine CT in all geriatric patients with the addition of torso CT in the setting of positive clinical findings and high-risk criteria. Prospective validation of this rule could lead to streamlined diagnostic care of this growing trauma population.
LEVEL OF EVIDENCE: Level 2, Diagnostic Tests or Criteria
Delirious Mania in a 77-Year-Old Female.
No full textDelirium is associated with acute episodes of disturbances in attention and awareness along with changes to cognition, including memory deficits and disorientation. Delirious mania (DM) is an unusual phenomenon where symptoms of delirium co-exist with symptoms of mania such as elevated or irritable mood, grandiosity, agitation, and cognitive disorganization. There is no formal agreement upon clinical symptoms for DM, but it generally includes acute onset of confusion, poor orientation, excitation, restlessness, and delusions. DM was first identified in the mid-1800s by Dr. Luther Bell and has only been identified by case reports since. We investigated a 77-year-old woman who was found at a gas station in an altered mental state. Upon observation, she has symptoms consistent with DM, including inappropriate laughter, distraction and confusion. She was diagnosed with acute metabolic encephalopathy, but the presentation of DM was considered in the differential and remains a unique finding