Female pediatric and adolescent genitalia trauma: a retrospective analysis of the National Trauma Data Bank.

PURPOSE: Pediatric genitalia injury represents 0.6% of all pediatric trauma. It is crucial for providers to understand whether pediatric patients are at risk for violent mechanisms, such as rape, assault, or other abuse. Therefore, we sought to perform a large database analysis of pediatric and adolescent female genitalia trauma, comparing mechanisms of injury (i.e., sexual abuse) and need for operative intervention between adolescent and pediatric cohorts. METHODS: The National Trauma Data Bank was queried (years 2007-2015) for female patients ≤ 16 years old with external genitalia (vaginal or vulvar) trauma. Two groups were compared: pediatrics (< 12 years old) and adolescents (12-16 years old). RESULTS: Out of 303,992 female patients, 3206 (1.1%) were identified to have genitalia trauma with the majority being pediatric patients (92.1%) and with injury to the vagina (62.6%). Pediatric patients with vaginal injury were less likely to be victims of rape (4.1% vs. 17.3%, p < 0.001) and assault (2.1% vs. 7.2%, p < 0.001) but more likely to be victims of other abuse (9.5% vs. 3.4%, p = 0.003). More of the adolescent patients with vaginal trauma required repair (58.7% vs. 43.2%, p < 0.001). Pediatric patients with injury to the vulva were less likely to be victims of rape (0.7% vs. 2.8%, p = 0.01) and motor vehicle accidents (4.2% vs. 11.0%, p < 0.001). CONCLUSION: Genitalia trauma occurs in 1.1% of pediatric and adolescent trauma cases with the vagina being more commonly injured compared to the vulva. Adolescent patients with vaginal injuries were more likely to be victims of rape and assault and required repair more often, while those with vulvar injuries were more likely due to motor vehicle accidents. Health care providers must be aware of these at-risk populations and the differences between them to identify female victims of violence and provide resources to assist with recovery.

Geriatric patients undergoing appendectomy have increased risk of intraoperative perforation and/or abscess.

BACKGROUND: The number of geriatric patients is expected to grow 3-fold over the next 30 years, and as many as 50% of the surgeries done in the United States may occur in geriatric patients. Geriatric patients often have increased comorbidities and more often present in a delayed manner for acute appendicitis. The aim of this study was to evaluate outcomes between geriatric patients and younger patients undergoing appendectomy, hypothesizing that geriatric patients will have a higher risk of abscess and/or perforation, conversion to open surgery, postoperative intra-abdominal abscess, and 30-day readmission. METHODS: The 2016 to 2017 American College of Surgeons National Surgical Quality Improvement Program Procedure Targeted Appendectomy database was queried for patients with preoperative image findings consistent with acute appendicitis. Geriatric patients (age ≥65 years old) were compared with younger patients (age <65 years old). A multivariable logistic regression model was used for analysis. RESULTS: From 21,586 patients undergoing appendectomy, 2,060 (9.5%) were geriatric patients. Compared with the younger cohort, geriatric patients were less likely to have leukocytosis (59.0% vs 65.8%, P < .001) and more likely to have a tumor and/or malignancy involving the appendix on final pathology (2.0% vs 0.8%, P < .001), an unplanned laparoscopic conversion to open surgery (4.2% vs 1.5%, P < .001), and 30-day readmission (7.0% vs 3.3%, P < .001). Geriatric patients had a longer median length of stay (2 vs 1 days, P < .001) and higher mortality rate (0.5% vs <0.1%, P < .001). After adjusting for covariates, there was an increased associated risk of intraoperative abscess and/or perforation (odds ratio 2.23, 2.01-2.48, P < .001) and postoperative intra-abdominal abscess (odds ratio 1.43, 1.12-1.83, P = .005) but no difference in associated risk for mortality (odds ratio 2.56, 0.79-8.25, P = .116), compared with the younger cohort. CONCLUSION: Nearly 10% of laparoscopic appendectomies are done on geriatric patients with geriatric patients having a higher rate of conversion to open surgery and tumor and/or malignancy on final pathology. Geriatric patients have an associated increased risk of intraoperative perforation and/or abscess and postoperative intra-abdominal abscess but have similar risk for mortality compared with nongeriatric patients undergoing laparoscopic appendectomy.

Characteristics of Atrial Fibrillation Patients with a Family History of Atrial Fibrillation.

BACKGROUND: Family history has been shown to be associated with increased risk of atrial fibrillation (AF). However, the specific AF characteristics that travel with a family history have not yet been elucidated. The purpose of this study was to determine whether a family history of AF is associated with specific patient characteristics in a worldwide, remote cohort. METHODS: From the Health eHeart Study, an internet-based prospective cohort, we performed a cross-sectional analysis of AF participants who reported their family history and completed questionnaires regarding their medical conditions and AF symptoms. We assessed demographics, cardiovascular comorbidities, and AF symptom characteristics in AF participants with and without a family history of AF. RESULTS: In multivariable analysis of 5,884 participants with AF (mean age 59.9 ± 14.5, 59% male, 92% white), female sex (odds ratio [OR]=1.35, 95% CI, 1.17-1.54, p<0.0001) and birth in the U.S. (OR=2.54, 95% CI, 2.12-3.05, p<0.0001) were independently associated with having a family history of AF. Having a family history of AF was also more commonly associated with symptoms of shortness of breath (OR=1.40, 95% CI, 1.07-1.82, p=0.014), chest pain, pressure, or discomfort (OR=1.95, 95% CI, 1.22-3.13, p=0.0052), and feeling generally "off" about oneself (OR=1.84, 95% CI, 1.27-2.67, p=0.0013). CONCLUSIONS: Patients with a family history of AF are more likely to be female, be US-born, and experience symptoms of AF, suggesting underlying mechanistic differences between those with and without family history of AF.

Does cannabis legalisation change healthcare utilisation? A population-based study using the healthcare cost and utilisation project in Colorado, USA.

OBJECTIVE: To assess the effect of cannabis legalisation on health effects and healthcare utilisation in Colorado (CO), the first state to legalise recreational cannabis, when compared with two control states, New York (NY) and Oklahoma (OK). DESIGN: We used the 2010 to 2014 Healthcare Cost and Utilisation Project (HCUP) inpatient databases to compare changes in rates of healthcare utilisation and diagnoses in CO versus NY and OK. SETTING: Population-based, inpatient. PARTICIPANTS: HCUP state-wide data comprising over 28 million individuals and over 16 million hospitalisations across three states. MAIN OUTCOME MEASURES: We used International Classification of Diseases-Ninth Edition codes to assess changes in healthcare utilisation specific to various medical diagnoses potentially treated by or exacerbated by cannabis. Diagnoses were classified based on weight of evidence from the National Academy of Science (NAS). Negative binomial models were used to compare rates of admissions between states. RESULTS: In CO compared with NY and OK, respectively, cannabis abuse hospitalisations increased (risk ratio (RR) 1.27, 95% CI 1.26 to 1.28 and RR 1.16, 95% CI 1.15 to 1.17; both p<0.0005) post-legalisation. In CO, there was a reduction in total admissions but only when compared with OK (RR 0.97, 95% CI 0.96 to 0.98, p<0.0005). Length of stay and costs did not change significantly in CO compared with NY or OK. Post-legalisation changes most consistent with NAS included an increase in motor vehicle accidents, alcohol abuse, overdose injury and a reduction in chronic pain admissions (all p<0.05 compared with each control state). CONCLUSIONS: Recreational cannabis legalisation is associated with neutral effects on healthcare utilisation. In line with previous evidence, cannabis liberalisation is linked to an increase in motor vehicle accidents, alcohol abuse, overdose injuries and a decrease in chronic pain admissions. Such population-level effects may help guide future decisions regarding cannabis use, prescription and policy.

Passive Detection of Atrial Fibrillation Using a Commercially Available Smartwatch.

Importance: Atrial fibrillation (AF) affects 34 million people worldwide and is a leading cause of stroke. A readily accessible means to continuously monitor for AF could prevent large numbers of strokes and death. Objective: To develop and validate a deep neural network to detect AF using smartwatch data. Design, Setting, and Participants: In this multinational cardiovascular remote cohort study coordinated at the University of California, San Francisco, smartwatches were used to obtain heart rate and step count data for algorithm development. A total of 9750 participants enrolled in the Health eHeart Study and 51 patients undergoing cardioversion at the University of California, San Francisco, were enrolled between February 2016 and March 2017. A deep neural network was trained using a method called heuristic pretraining in which the network approximated representations of the R-R interval (ie, time between heartbeats) without manual labeling of training data. Validation was performed against the reference standard 12-lead electrocardiography (ECG) in a separate cohort of patients undergoing cardioversion. A second exploratory validation was performed using smartwatch data from ambulatory individuals against the reference standard of self-reported history of persistent AF. Data were analyzed from March 2017 to September 2017. Main Outcomes and Measures: The sensitivity, specificity, and receiver operating characteristic C statistic for the algorithm to detect AF were generated based on the reference standard of 12-lead ECG-diagnosed AF. Results: Of the 9750 participants enrolled in the remote cohort, including 347 participants with AF, 6143 (63.0%) were male, and the mean (SD) age was 42 (12) years. There were more than 139 million heart rate measurements on which the deep neural network was trained. The deep neural network exhibited a C statistic of 0.97 (95% CI, 0.94-1.00; P < .001) to detect AF against the reference standard 12-lead ECG-diagnosed AF in the external validation cohort of 51 patients undergoing cardioversion; sensitivity was 98.0% and specificity was 90.2%. In an exploratory analysis relying on self-report of persistent AF in ambulatory participants, the C statistic was 0.72 (95% CI, 0.64-0.78); sensitivity was 67.7% and specificity was 67.6%. Conclusions and Relevance: This proof-of-concept study found that smartwatch photoplethysmography coupled with a deep neural network can passively detect AF but with some loss of sensitivity and specificity against a criterion-standard ECG. Further studies will help identify the optimal role for smartwatch-guided rhythm assessment.