Introduction of a high sensitivity troponin reduces ED length of stay.

BACKGROUND: High sensitivity cardiac troponins (hs-cTn) allow earlier identification and exclusion of acute myocardial infarction. We determined if transitioning from contemporary to high sensitivity troponin T (hs-cTnT) would reduce ED length of stay in chest pain (CP) patients. METHODS: We conducted a pragmatic, prospective, before and after study of implementing a hs-cTnT by reviewing the electronic health records in all adult ED patients presenting to a large, suburban academic medical center during the 3 months before and after transitioning from a 4th generation troponin to a 5th generation hs-cTnT (Elecsys® Troponin T-high sensitive, Roche Diagnostics, Indianapolis, IN). RESULTS: There were 1431 and 1437 CP patients before and after the intervention. Mean (SD) age was 51.5 (18) yrs. and 54.3% were female. The median (IQR) ED LOS for chest pain patients directly discharged to home was 6.2 (4.7-8.4) and 5.3 (4.0-7.2) hours before and after introducing hs-cTn respectively; difference 47 min (95%CI, 35-59); P < 0.001. The median (IQR) ED LOS for chest pain patients admitted to the hospital was 9.5 (6.6-13.8) and 8.1 (5.7-11.2) hours before and after introducing hs-cTn respectively; difference 77 min (95%CI, 35-121); P < 0.001. Overall admission rates (22 vs 21% both before and after) did not change during the study. The rates of computed tomography coronary angiography before and after the intervention were 21 and 20.4% respectively. The rates of invasive coronary angiography before and after the intervention were 5.8 and 5.6% respectively. CONCLUSIONS: Transitioning to a hs-cTnT is associated with a clinically relevant and statistically significant reduction in ED LOS for both discharged and admitted patients with and without CP with no increase in admission or coronary angiography rates.

Venous thromboembolic disease in admitted blunt trauma patients: what matters?

BACKGROUND: Venous thromboembolic events (VTE) are a significant cause of morbidity and mortality following traumatic injury. We examined demographic characteristics, chemoprophylaxis, and outcomes of VTE patients with blunt trauma requiring hospitalization. METHODS: A retrospective review of adult blunt trauma hospitalizations with and without VTE between 2012 and 2019 was conducted. Deaths in the emergency department were excluded. Univariate and multivariable analyses, including machine learning classification algorithms for VTE, were performed. RESULTS: Of 10,926 admitted adult blunt trauma patients, 177 had VTE events. VTE events occurred at a median of 6 [IQR 3-11] days, with 7.3% occurring within 1 day of admission. VTE patients were more often male, and more often underwent surgery. They had higher injury severity as well as longer intensive care unit and hospital lengths of stay. While VTE occurred throughout the spectrum of injury severity, 27.7% had low injury severity (ISS < = 9). In multivariable analyses, both heparin and enoxaparin had reduced adjusted odds ratios for VTE. CONCLUSION: Approximately 7.3% of VTE events occurred within one day of admission. A substantial proportion of VTE events occurred in patients with low injury severity (ISS < = 9). Subcutaneous unfractionated heparin and enoxaparin chemoprophylaxis were both inversely associated with VTE. These findings underscore the need for vigilance for VTE identification in blunt trauma patients throughout their hospitalization and VTE prevention efforts.

Digital pathology, deep learning, and cancer: a narrative review.

Background and Objective: Cancer is a leading cause of morbidity and mortality worldwide. The emergence of digital pathology and deep learning technologies signifies a transformative era in healthcare. These technologies can enhance cancer detection, streamline operations, and bolster patient care. A substantial gap exists between the development phase of deep learning models in controlled laboratory environments and their translations into clinical practice. This narrative review evaluates the current landscape of deep learning and digital pathology, analyzing the factors influencing model development and implementation into clinical practice. Methods: We searched multiple databases, including Web of Science, Arxiv, MedRxiv, BioRxiv, Embase, PubMed, DBLP, Google Scholar, IEEE Xplore, Semantic Scholar, and Cochrane, targeting articles on whole slide imaging and deep learning published from 2014 and 2023. Out of 776 articles identified based on inclusion criteria, we selected 36 papers for the analysis. Key Content and Findings: Most articles in this review focus on the in-laboratory phase of deep learning model development, a critical stage in the deep learning lifecycle. Challenges arise during model development and their integration into clinical practice. Notably, lab performance metrics may not always match real-world clinical outcomes. As technology advances and regulations evolve, we expect more clinical trials to bridge this performance gap and validate deep learning models' effectiveness in clinical care. High clinical accuracy is vital for informed decision-making throughout a patient's cancer care. Conclusions: Deep learning technology can enhance cancer detection, clinical workflows, and patient care. Challenges may arise during model development. The deep learning lifecycle involves data preprocessing, model development, and clinical implementation. Achieving health equity requires including diverse patient groups and eliminating bias during implementation. While model development is integral, most articles focus on the pre-deployment phase. Future longitudinal studies are crucial for validating models in real-world settings post-deployment. A collaborative approach among computational pathologists, technologists, industry, and healthcare providers is essential for driving adoption in clinical settings.

Poor compliance with ACG guidelines for nutrition and antibiotics in the management of acute pancreatitis: a North American survey of gastrointestinal specialists and primary care physicians.

CONTEXT: Despite recent updates in the treatment of acute pancreatitis emphasizing enteral nutrition over parenteral nutrition as well as minimizing antibiotic usage, mortality rates from acute pancreatitis have not improved. Data has been limited regarding physician compliance to these guidelines in the United States. METHODS: A 20 question survey regarding practice patterns in the management of acute pancreatitis was distributed to physicians at multiple internal medicine and gastroenterology conferences in North America between 2009 and 2010. Responses were analyzed using the chi-square test and multivariate logistic regression. RESULTS: Out of 406 available respondents, 43.3% of physicians utilize total parenteral nutrition/peripheral parenteral nutrition (TPN/PPN) and 36.5% utilize nasojejunal (NJ) feedings. The preferred route of nutrition was significantly related to practice type (P<0.001): academic physicians were more likely to use NJ tube feeding than private practice physicians (52.1% vs. 19.9%) while private practitioners were more likely to utilize TPN/PPN than academic physicians (70.2% vs. 20.5%). Gastroenterologists and primary care physicians were equally non-compliant as both groups favored parenteral nutrition. Multivariate logistic regression demonstrated that practice type (P<0.001) was the only independent predictor of route of nutrition. Most survey respondents appropriately do not routinely utilize antibiotics for acute pancreatitis, but when antibiotics are initiated, they are for inappropriate indications such as fever and infection prophylaxis. CONCLUSIONS: Many North American physicians are noncompliant with current ACG practice guidelines for the use of artificial nutrition in the management of acute pancreatitis, with overuse of TPN/PPN and underutilization of jejunal feedings. Antibiotics are initiated in acute pancreatitis for inappropriate indications, although there are conflicting recommendations for antibiotics in severe acute pancreatitis. Improved compliance with guidelines is needed to improve patient outcomes.

Efficacy of gelatamp in controlling the postoperative sequelae following mandibular posterior teeth extraction - A split-mouth study.

Purpose: This study aimed to evaluate the effectiveness of gelatamp on soft tissue healing, bleeding, and pain following mandibular posterior teeth extraction. Methods: This study was designed as a split-mouth, prospective randomized double-blind controlled trial conducted in a single tertiary care center. Thirty-five subjects indicated for routine mandibular posterior teeth extraction were divided into two groups using the lottery technique: the experimental group (n = 30), which received gelatamp after extraction, and the control group (n = 30), which received no intervention. The primary outcomes included soft tissue healing(Landry, Turnbull, Howley index) and Pain(VAS score). The secondary outcomes assessed were bleeding(Maani et al. index) and swelling(Sauza and Consone assessment). Result: The results showed a statistically significant difference in soft tissue healing on the third and seventh days in the experimental group (p ≤ 0.05) than in the control group. A significant difference in bleeding scores at 5 min, 30 min, and 2 h postoperatively in the study group (p ≤ 0.05) was noted. There was no significant difference between the groups for pain on the first, third or seventh day postoperatively (p ≤ 0.05). The swelling assessment also showed no significant changes (p = 0.831) for the study and the control group. Conclusion: Based on the findings of this study, gelatamp can be effectively used to reduce postoperative sequelae such as bleeding with better soft tissue healing following extractions and surgical removal of tooth.

An In vitro study of biomechanical comparison between titanium 4-hole 3D plates and titanium conventional 4-hole miniplates for internal fixation of mandibular angle fractures.

Background: Fracture fixation, in the present times, is classically done using mini plates. The position and number of plates to fixate a mandibular angle fracture have been and are still extensively researched and reported in the literature. A more recent addition is 3D mini plates. Aim: To compare and evaluate the biomechanical behavior of one 2.0 mm titanium 3D miniplate fixation plate (4- hole) and one 2.0 mm titanium 4-hole miniplate in internal fixation of mandibular angle fractures. Objective: To measure load at break, maximum load, and displacement at maximal load for internal fixation done with 3D mini plates and conventional mini plates respectively. Methods: Five dry cadaveric mandibles were sectioned into 10 hemi-mandibles. Each cadaveric mandible was sectioned at the angle of mandible to simulate unfavorable mandibular angle fracture. The obtained hemimandible were divided into experimental groups (GROUP 1 and GROUP 2) with 5 samples in each group, plated with a linear miniplate and 3D miniplate respectively. Maximal load, Load at break, and displacement at maximum load were the only obtained parameters for comparison. Results: Conventional miniplate showed greater mean maximum load values of 174.93 N±54.45 compared to 3D mini plates which recorded a mean maximum load value of 106.96 N ± 23.86. Load at break and displacement at maximum load were found to be both insignificant. Conclusion: The results in this study showed statistically no significant difference with any of the above parameters except maximal load, between the two groups evaluated. Conventional linear miniplate according to Champy's lines of osteosynthesis can be used successfully for providing satisfactory osteosynthesis with the definitive advantage of cost-effectiveness.

"3D printed locator guides"; Fusion deposited starch guides for surgical removal of impacted maxillary teeth.

The rapid prototyping technology helped to convert the virtual surgical plans into action by the help of fusion deposition techniques. Starch based polymers like PLA (Poly lactic acid) are commonly used in the field of tissue engineering for making scaffolds. In dentistry its use is limited because of lack of precision. We tried to make a 3D printed locator guide for surgical removal of impacted maxillary premolar by using a starch based polymer.

A reference guide to rapidly implementing an institutional dashboard for resource allocation and oversight during COVID-19 pandemic surge.

OBJECTIVES: We develop a dashboard that leverages electronic health record (EHR) data to monitor intensive care unit patient status and ventilator utilization in the setting of the COVID-19 pandemic. MATERIALS AND METHODS: Data visualization software is used to display information from critical care data mart that extracts information from the EHR. A multidisciplinary collaborative led the development. RESULTS: The dashboard displays institution-level ventilator utilization details, as well as patient-level details such as ventilator settings, organ-system specific parameters, laboratory values, and infusions. DISCUSSION: Components of the dashboard were selected to facilitate the determination of resources and simultaneous assessment of multiple patients. Abnormal values are color coded. An overall illness assessment score is tracked daily to capture illness severity over time. CONCLUSION: This reference guide shares the architecture and sample reusable code to implement a robust, flexible, and scalable dashboard for monitoring ventilator utilization and illness severity in intensive care unit ventilated patients.

Risk Factors Associated with Linkage to Care among Suburban Hepatitis C-Positive Baby Boomers and Injection Drug Users.

INTRODUCTION: Suffolk County, located in Eastern Long Island, has been an epicenter for the opioid epidemic in New York State, yet no studies have examined hepatitis C virus (HCV) prevalence in this population. Additionally, few studies have assessed barriers for linkage to care (LTC) to HCV treatment in people who inject drugs (PWID), a high-risk HCV cohort. We aimed to determine prevalence of HCV infection in a suburban medical center and to assess risk factors associated with LTC in HCV-positive baby boomers and young PWID. METHODS: A retrospective chart review was carried out on adult patients with ICD-9/10 diagnostic codes for HCV from January 2016 to December 2018 at Stony Brook Medicine. Data collected included sociodemographics, RNA serostatus, LTC, health insurance, employment, past medical or psychiatric history, and substance or injection drug use. RESULTS: Overall, 27,049 individuals were screened for HCV and 1017 were HCV seropositive (3.8%), 437 (42.9%) were HCV RNA-positive and 153 (40.6%) achieved LTC. In multivariate analysis, living with cirrhosis was associated with a positive LTC. Medicaid or Medicare insurance was associated with a negative LTC. Intravenous drug users were more likely to be young and have concomitant polysubstance use and psychiatric disease. A bimodal distribution of HCV-positives is present in our population. CONCLUSION: Those with liver cirrhosis are more likely to achieve LTC, as are those with private insurance. Public health efforts to promote awareness of HCV and to facilitate access to treatment among PWID are needed.

Deep Learning on Electronic Health Records to Improve Disease Coding Accuracy.

Characterization of a patient's clinical phenotype is central to biomedical informatics. ICD codes, assigned to inpatient encounters by coders, is important for population health and cohort discovery when clinical information is limited. While ICD codes are assigned to patients by professionals trained and certified in coding there is substantial variability in coding. We present a methodology that uses deep learning methods to model coder decision making and that predicts ICD codes. Our approach predicts codes based on demographics, lab results, and medications, as well as codes from previous encounters. We are able to predict existing codes with high accuracy for all three of the test cases we investigated: diabetes, acute renal failure, and chronic kidney disease. We employed a panel of clinicians, in a blinded manner, to assess ground truth and compared the predictions of coders, model and clinicians. When disparities between the model prediction and coder assigned codes were reviewed, our model outperformed coder assigned ICD codes.