by
Robert Ward;
Shiva Ponamgi;
Christopher DeSimone;
Stephen English;
David O Hodge;
Joshua P Slusser;
Jonathan Graff-Radford;
Alejandro A Rabinstein;
Sameul J Asirvatham;
David Holmes
Objective: To determine the utility of the HAS-BLED (Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly, Drugs/alcohol concomitantly) and CHA2DS2-VASc (Congestive heart failure, Hypertension, Age, Diabetes, previous Stroke/transient ischemic attack–VAScular disease) scores among patients on anticoagulation (AC) therapy for atrial fibrillation (AF) who have evidence of cerebral amyloid angiopathy (CAA). Patients and Methods: Patients older than 55 years with a diagnosis of AF who had a nontraumatic intracerebral hemorrhage (ICH) while on AC therapy between 1995 and 2016 were identified using the Rochester Epidemiology Project Database. Medical records were reviewed, including imaging of the brain, to identify baseline characteristics, AC use, and outcomes. Results: A total of 65 patients were identified (mean age, 81.3 years); 35 (53.8%) had evidence of possible/probable CAA. Mean HAS-BLED score in the CAA group was significantly lower (2.1) than that of the non-CAA group (2.9; P<.001). Mortality after ICH, adjusted for HAS-BLED scores, was not significantly different among patients with and without CAA. Sixteen patients restarted on AC therapy after ICH; CHA2DS2-VASc scores were no different between this group and those who were not restarted. Among patients with CAA, the overall rate of ICH recurrence was 8.6% over 93.5 person-years of follow-up. Among patients with CAA, the rate of ICH recurrence was 3.2 per 100 patient-years, higher than their HAS-BLED scores would predict (1.9 bleeds/100 patient-years). Conclusion: HAS-BLED scores were lower in patients who had evidence of CAA compared with those without, suggesting underestimation of ICH risk in patients with CAA. CHA2DS2-VASc scores did not affect resumption of AC therapy. ICH recurrence was higher in patients with CAA than their HAS-BLED scores predicted. Current risk assessment scoring systems do not accurately account for CAA in patients with AF on AC.
Background: Road traffic injuries (RTIs) are the eighth leading cause of death worldwide, with an estimated 90% of RTIs occurring in low- and middle-income countries (LMICs) like Brazil. There has been minimal research in evaluation of delays in transport of RTI patients to trauma centers in LMICs. The objective of this study is to determine specific causes of delays in prehospital transport of road traffic injury patients to designated trauma centers in Maringá, Brazil. Methods: A qualitative method was used based on the Consolidated Criteria for Reporting Qualitative Research (COREQ) approach. Eleven health care providers employed at prehospital or hospital settings were interviewed with questions specific to delays in care for RTI patients. A thematic analysis was conducted. Results: Responses to primary causes of delay in treatment to RTI patients fell into the following categories: 1) lack of public education, 2) traffic, 3) insufficient personnel/ambulances, 4) bureaucracy, and 5) poor location of stations. Suggestions for improvement in delays fell into the categories of 1) need for centralized station/avoid traffic, 2) improving public education, 3) Increase personnel, 4) increase ambulances, 5) proper extrication/rapid treatment. Conclusion: Our study found varied responses between hospital and SAMU providers regarding specific causes of delay for RTI patients; SAMU providers cited primarily traffic, bureaucracy, and poor location as primary factors while hospital employees focused more on public health aspects. These results mirror prehospital system challenges in other developing countries, but also provide solutions for improvement with better infrastructure and public health campaigns.
by
Jonathan Beitler;
Qiang Zhang;
Karen K Fu;
Andy Trotti;
Sharon A Spencer;
Christopher U Jones;
Adam S Garden;
George Shenouda;
Jonathan Harris;
Kian K Ang
Purpose To test whether altered radiation fractionation schemes (hyperfractionation [HFX], accelerated fractionation, continuous [AFX-C], and accelerated fractionation with split [AFX-S]) improved local-regional control (LRC) rates for patients with squamous cell cancers (SCC) of the head and neck when compared with standard fractionation (SFX) of 70 Gy. Methods and Materials Patients with stage III or IV (or stage II base of tongue) SCC (n=1076) were randomized to 4 treatment arms: (1) SFX, 70 Gy/35 daily fractions/7 weeks; (2) HFX, 81.6 Gy/68 twice-daily fractions/7 weeks; (3) AFX-S, 67.2 Gy/42 fractions/6 weeks with a 2-week rest after 38.4 Gy; and (4) AFX-C, 72 Gy/42 fractions/6 weeks. The 3 experimental arms were to be compared with SFX. Results With patients censored for LRC at 5 years, only the comparison of HFX with SFX was significantly different: HFX, hazard ratio (HR) 0.79 (95% confidence interval 0.62-1.00), P=.05; AFX-C, 0.82 (95% confidence interval 0.65-1.05), P=.11. With patients censored at 5 years, HFX improved overall survival (HR 0.81, P=.05). Prevalence of any grade 3, 4, or 5 toxicity at 5 years; any feeding tube use after 180 days; or feeding tube use at 1 year did not differ significantly when the experimental arms were compared with SFX. When 7-week treatments were compared with 6-week treatments, accelerated fractionation appeared to increase grade 3, 4 or 5 toxicity at 5 years (P=.06). When the worst toxicity per patient was considered by treatment only, the AFX-C arm seemed to trend worse than the SFX arm when grade 0-2 was compared with grade 3-5 toxicity (P=.09). Conclusions At 5 years, only HFX improved LRC and overall survival for patients with locally advanced SCC without increasing late toxicity.
Objectives:
To estimate the risk of post-vasectomy infections in various settings and across various surgical techniques and sanitization practices.
Patients and Methods:
Retrospective review of the records of 133,044 vasectomized patients from four large practices/network of practices using the no-scalpel vasectomy (NSV) technique in Canada (2011-2021), Colombia (2015-2020), New Zealand (2018-2021), and the United Kingdom (2006-2019). We defined infection as any mention in medical records of any antibiotics prescribed for a genital or urinary condition following vasectomy.
Results:
Post-vasectomy infection risks were 0.8% (219 infections/26,809 procedures), 2.1% (390/18,490), 1.0% (100/10,506), and 1.3% (1,007/77,239) in Canada, Colombia, New Zealand, and the UK, respectively. Audit period comparison suggests a limited effect on the risk of infection of excising a short vas segment, applying topical antibiotic on scrotal opening, wearing a surgical mask in Canada, type of skin disinfectant, and use of non-sterile gloves in New Zealand. Risk of infection was lower in Colombia when mucosal cautery and fascial interposition [FI] were used for vas occlusion compared to ligation, excision, and FI (0.9% vs. 2.1%, p<0.00001). Low level of infection certainty in 56% to 60% of patients who received antibiotics indicates that the true risk might be overestimated. Lack of information in medical records and patients not consulting their vasectomy providers might have led to underestimation of the risk.
Conclusion:
Risk of infection after vasectomy is low, about 1%, among international high-volume vasectomy practices performing NSV and various occlusion techniques. Apart from vasectomy occlusion technique, no other factor modified the risk of post-vasectomy infection.
Multimodal image registration is a key for many clinical image‐guided interventions. However, it is a challenging task because of complicated and unknown relationships between different modalities. Currently, deep supervised learning is the state‐of‐theart method at which the registration is conducted in end‐to‐end manner and one‐shot. Therefore, a huge ground‐truth data is required to improve the results of deep neural networks for registration. Moreover, supervised methods may yield models that bias towards annotated structures. Here, to deal with above challenges, an alternative approach is using unsupervised learning models. In this study, we have designed a novel deep unsupervised Convolutional Neural Network (CNN)‐based model based on computer tomography/magnetic resonance (CT/MR) co‐registration of brain images in an affine manner. For this purpose, we created a dataset consisting of 1100 pairs of CT/MR slices from the brain of 110 neuropsychic patients with/without tumor. At the next step, 12 landmarks were selected by a well‐experienced radiologist and annotated on each slice resulting in the computation of series of metrics evaluation, target registration error (TRE), Dice similarity, Hausdorff, and Jaccard coefficients. The proposed method could register the multimodal images with TRE 9.89, Dice similarity 0.79, Hausdorff 7.15, and Jaccard 0.75 that are appreciable for clinical applications. Moreover, the approach registered the images in an acceptable time 203 ms and can be appreciable for clinical usage due to the short registration time and high accuracy. Here, the results illustrated that our proposed method achieved competitive performance against other related approaches from both reasonable computation time and the metrics evaluation.
by
Christina M Theodorou;
Amit RT Joshi;
A. Alfred Chahine;
Sally A Boyd;
Jeffrey M Stern;
Rahul J Anand;
Mark Hickey;
Madison Bradley;
Sahil S Tilak;
Kerry B Barrett;
Mary E Klingensmith
Objective: The COVID-19 pandemic has disrupted graduate medical education, impacting Accreditation Council for Graduate Medical Education (ACGME)-mandated didactics. We aimed to study the utility of 2 methods of virtual learning: the daily National Surgery Resident Lecture Series (NSRLS), and weekly “SCORE School” educational webinars designed around the Surgical Council on Resident Education (SCORE) curriculum. Design and Setting: NSRLS: The National Surgery Resident Lecture Series was a daily virtual educational session initially led by faculty at an individual surgical residency program. Thirty-eight lectures were assessed for number of live viewings (March 23, 2020-May 15, 2020). SCORE School: Attendance at eleven weekly SCORE educational webinars was characterized into live and asynchronous viewings (May 13, 2020-August 5, 2020). Each 1-hour live webinar was produced by SCORE on a Wednesday evening and featured nationally recognized surgeon educators using an online platform that allowed for audience interaction. Results: NSRLS: There were a mean of 71 live viewers per NSRLS session (range 19-118). Participation began to decline in the final 2 weeks as elective case volumes increased, but sessions remained well-attended. SCORE School: There were a range of 164-3889 live viewers per SCORE School session. Sessions have most commonly been viewed asynchronously (89.8% of viewings). Live viewership decreased as the academic year ended and then rebounded with the start of the new academic year (range 4.9%-27%). Overall, the eight webinars were viewed 11,135 times. Each webinar continues to be viewed a mean of 43 times a day (range 0-102). Overall, the eleven webinars have been viewed a total of 22,722 times. Conclusions: Virtual didactics aimed at surgical residents are feasible, well-attended (both live and recorded), and have high levels of viewer engagement. We have observed that careful coordination of timing and topics is ideal. The ability for asynchronous viewing is particularly important for attendance. As the COVID-19 pandemic continues to disrupt healthcare systems, training programs must continue to adapt to education via virtual platforms.
Continuous glucose monitoring (CGM) systems are small medical devices used to measure blood glucose continuously over the course of a person’s day and, importantly, also throughout the night. More than with A1C or fingerstick blood glucose monitoring (BGM), the data gained from CGM offer tremendous insights into glycemic control and enable both clinicians and people with diabetes to make informed adjustments to treatment plans through shared decision-making. Most CGM devices can be applied and started by the patient independently.
This article is intended to serve as an executive summary for a series of short videos available now on the Clinical Diabetes website. The authors discuss the limitations of relying solely on A1C to guide patients’ daily decision-making, the advantages of using CGM for both patients and clinicians, the role of the ambulatory glucose profile (AGP) report and time in range (TIR) metric as actionable formats for presenting and interpreting CGM data, strategies to modify patient treatment plans based on CGM data, patient access to and affordability of CGM equipment, and relevant insurance billing codes and other clinician resources. The video series described below is available in its entirety at https://diabetesjournals.org/clinical/pages/continuous_glucose_monitoring.
Planned interventions and/or natural conditions often effect change on an ordinal categorical outcome (e.g., symptom severity). In such scenarios, it is sometimes desirable to assign a priori scores to observed changes in status, typically giving higher weight to changes of greater magnitude. We define change indices for such data based upon a multinomial model for each row of a c × c table, where the rows represent the baseline status categories. We distinguish an index designed to assess conditional changes within each baseline category from two others designed to capture overall change. One of these overall indices measures expected change across a target population. The other is scaled to capture the proportion of total possible change in the direction indicated by the data, so that it ranges from -1 (when all subjects finish in the least favorable category) to +1 (when all finish in the most favorable category). The conditional assessment of change can be informative regardless of how subjects are sampled into the baseline categories. In contrast, the overall indices become relevant when subjects are randomly sampled at baseline from the target population of interest, or when the investigator is able to make certain assumptions about the baseline status distribution in that population. We use a Dirichlet-multinomial model to obtain Bayesian credible intervals for the conditional change index that exhibit favorable small-sample frequentist properties. Simulation studies illustrate the methods, and we apply them to examples involving changes in ordinal responses for studies of sleep deprivation and activities of daily living.
The number of immunosuppressed patients is growing remarkably. Currently, there is no guideline on how treatment of noninvasive sinusitis in these patients may differ from that of the general population, and practice patterns vary widely across the country. The purpose of this survey was to examine practice patterns and management for this patient population. A survey and literature review were performed. The survey was sent to the membership list serve of the American Rhinologic Society. Twelve questions were asked. Four demographic questions were asked about the physicians and their practices. Four questions were asked about the type of immunocompromised patients they saw. Two questions were asked about management in the setting of significant acute and chronic sinusitis. The responses were collected and analyzed using Pearson independent chi-square testing. Of 871 members on the list serve only 89 physicians responded. The majority of responders were sinus and skull base surgeons practicing in an academic setting. There was a large range of geographic location, years in practice, and patient population. Two significant findings related years in practice to management of chronic sinus immunocompromised patients (p = 0.012) and correlated the choice of management option in acute and chronic sinus immunocompromised patients (p = 0.006). There is no standardized method of treating the vulnerable patient population of immunocompromised patients with noninvasive acute and chronic sinusitis and this survey shows the wide range of practice. Clinical research is needed to standardize and optimize treatment for these patients.
Although the American Academy of Pediatrics recommends breastfeeding for at least 2 years,1 lactating physicians encounter multiple barriers preventing personal attainment of this goal.2,3 Physician leaders recently issued a call to action to support lactating physicians4; but to our knowledge, no studies have systematically examined the current state of lactation-support policies. This study aims to examine lactation-support policies at leading US schools of medicine (SOMs).