Preoperative Prediction of Postoperative Infections Using Machine Learning and Electronic Health Record Data.

OBJECTIVE: To estimate preoperative risk of postoperative infections using structured electronic health record (EHR) data. BACKGROUND: Surveillance and reporting of postoperative infections is primarily done through costly, labor-intensive manual chart reviews on a small sample of patients. Automated methods using statistical models applied to postoperative EHR data have shown promise to augment manual review as they can cover all operations in a timely manner. However, there are no specific models for risk-adjusting infectious complication rates using EHR data. METHODS: Preoperative EHR data from 30,639 patients (2013-2019) were linked to the American College of Surgeons National Surgical Quality Improvement Program preoperative data and postoperative infection outcomes data from 5 hospitals in the University of Colorado Health System. EHR data included diagnoses, procedures, operative variables, patient characteristics, and medications. Lasso and the knockoff filter were used to perform controlled variable selection. Outcomes included surgical site infection, urinary tract infection, sepsis/septic shock, and pneumonia up to 30 days postoperatively. RESULTS: Among >15,000 candidate predictors, 7 were chosen for the surgical site infection model and 6 for each of the urinary tract infection, sepsis, and pneumonia models. Important variables included preoperative presence of the specific outcome, wound classification, comorbidities, and American Society of Anesthesiologists physical status classification. The area under the receiver operating characteristic curve for each model ranged from 0.73 to 0.89. CONCLUSIONS: Parsimonious preoperative models for predicting postoperative infection risk using EHR data were developed and showed comparable performance to existing American College of Surgeons National Surgical Quality Improvement Program risk models that use manual chart review. These models can be used to estimate risk-adjusted postoperative infection rates applied to large volumes of EHR data in a timely manner.

The deimplementation of laboratory testing in low-risk patients as recommended by the American society of anesthesiologists: An ACS-NSQIP longitudinal analysis.

BACKGROUND: In 2012, the American Society of Anesthesiologists (ASA) published guidelines recommending against routine preoperative laboratory testing for low-risk patients to reduce unnecessary medical expenditures. The aim of this study was to assess the change in routine preoperative laboratory testing in low-risk versus higher-risk patients before and after release of these guidelines. METHODS: The ACS-NSQIP database, 2005-2018, was separated into low-risk versus higher-risk patients based upon a previously published stratification. The guideline implementation date was defined as January 2013. Changes in preoperative laboratory testing over time were compared between low- and higher-risk patients. A difference-in-differences model was applied. The primary outcome included any laboratory test obtained ≤90 days prior to surgery. RESULTS: Of 7,507,991 patients, 972,431 (13.0%) were defined as low-risk and 6,535,560 (87.0%) higher-risk. Use of any preoperative laboratory test declined in low-risk patients from 66.5% before to 59.6% after guidelines, a 6.9 percentage point reduction, versus 93.0%-91.9% in higher-risk patients, a 1.1 percentage point reduction (p < 0.0001, comparing percentage point reductions). After risk-adjustment, the adjusted odds ratio for having any preoperative laboratory test after versus before the guidelines was 0.77 (95% CI 0.76-0.78) in low-risk versus 0.93 (0.92-0.94) in higher-risk patients. In low-risk patients, lack of any preoperative testing was not associated with worse outcomes. CONCLUSIONS: While a majority of low-risk patients continue to receive preoperative laboratory testing not recommended by the ASA, there has been a decline after implementation of guidelines. Continued effort should be directed at the deimplementation of routine preoperative laboratory testing for low-risk patients.

Preoperative Prediction of Unplanned Reoperation in a Broad Surgical Population.

INTRODUCTION: Unplanned reoperation is an undesirable outcome with considerable risks and an increasingly assessed quality of care metric. There are no preoperative prediction models for reoperation after an index surgery in a broad surgical population in the literature. The Surgical Risk Preoperative Assessment System (SURPAS) preoperatively predicts 12 postoperative adverse events using 8 preoperative variables, but its ability to predict unplanned reoperation has not been assessed. This study's objective was to determine whether the SURPAS model could accurately predict unplanned reoperation. METHODS: This was a retrospective analysis of the American College of Surgeons' National Surgical Quality Improvement Program adult database, 2012-2018. An unplanned reoperation was defined as any unintended operation within 30 d of an initial scheduled operation. The 8-variable SURPAS model and a 29-variable "full" model, incorporating all available American College of Surgeons' National Surgical Quality Improvement Program nonlaboratory preoperative variables, were developed using multiple logistic regression and compared using discrimination and calibration metrics: C-indices (C), Hosmer-Lemeshow observed-to-expected plots, and Brier scores (BSs). The internal chronological validation of the SURPAS model was conducted using "training" (2012-2017) and "test" (2018) datasets. RESULTS: Of 5,777,108 patients, 162,387 (2.81%) underwent an unplanned reoperation. The SURPAS model's C-index of 0.748 was 99.20% of that for the full model (C = 0.754). Hosmer-Lemeshow plots showed good calibration for both models and BSs were similar (BS = 0.0264, full; BS = 0.0265, SURPAS). Internal chronological validation results were similar for the training (C = 0.749, BS = 0.0268) and test (C = 0.748, BS = 0.0250) datasets. CONCLUSIONS: The SURPAS model accurately predicted unplanned reoperation and was internally validated. Unplanned reoperation can be integrated into the SURPAS tool to provide preoperative risk assessment of this outcome, which could aid patient risk education.

Does Work Relative Value Unit Measure Surgical Complexity for Risk Adjustment of Surgical Outcomes?

INTRODUCTION: The purpose of this study was to determine whether the work relative value unit (workRVU) of a patient's operation can be useful as a measure of surgical complexity for the risk adjustment of surgical outcomes. METHODS: We retrospectively analyzed the American College of Surgeon's National Surgical Quality Improvement Program database (2005-2018). We examined the associations of workRVU of the patient's primary operation with preoperative patient characteristics and associations with postoperative complications. We performed forward selection multiple logistic regression analysis to determine the predictive importance of workRVU. We then generated prediction models using patient characteristics with and without workRVU and compared c-indexes to assess workRVU's additive predictive value. RESULTS: 7,507,991 operations were included. Patients who were underweight, functionally dependent, transferred from an acute care hospital, had higher American Society of Anesthesiologists class or who had medical comorbidities had operations with higher workRVU (all P < 0.0001). The subspecialties with the highest workRVU were neurosurgery (mean = 22.2), thoracic surgery (mean = 21.1), and vascular surgery (mean = 18.8) (P < 0.0001). For all postoperative complications, mean workRVU was higher for patients with the complication than those without (all P < 0.0001). For eight of 12 postoperative complications, workRVU entered the logistic regression models as a predictor variable in the 1st to 4th steps. Addition of workRVU as a preoperative predictive variable improved the c-index of the prediction models. CONCLUSIONS: WorkRVU was associated with sicker patients and patients experiencing postoperative complications and was an important predictor of postoperative complications. When added to a prediction model including patient characteristics, it only marginally improved prediction. This is possibly because workRVU is associated with patient characteristics.

Unmeasured factors are associated with the use of completion lymph node dissection (CLND) in melanoma.

BACKGROUND: Completion lymph node dissection (CLND) was the standard treatment for patients with melanoma with positive sentinel lymph nodes (SLN) until 2017 when data from the DeCOG-SLT and MLST-2 randomized trials challenged the survival benefit of this procedure. We assessed the contribution of patient, tumor and facility factors on the use of CLND in patients with surgically resected Stage III melanoma. METHODS: Using the National Cancer Database, patients who underwent surgical excision and were found to have a positive SLN from 2012 to 2017 were included. A multivariable mixed-effects logistic regression model with a random intercept for the facility was used to determine the effect of patient, tumor, and facility variables on the risk of CLND. Reference effect measures (REMs) were used to compare the contribution of contextual effects (unknown facility variables) versus measured variables on the variation in CLND use. RESULTS: From 2012 to 2017, the overall use of CLND decreased from 59.9% to 26.5% (p < 0.0001). Overall, older patients and patients with government-based insurance were less likely to undergo CLND. Tumor factors associated with a decreased rate of CLND included primary tumor location on the lower limb, decreasing depth, and mitotic rate <1. However, the contribution of contextual effects to the variation in CLND use exceeded that of the measured facility, tumor, time, and patient variables. CONCLUSIONS: There was a decrease in CLND use during the study period. However, there is still high variability in CLND use, mainly driven by unmeasured contextual effects.

Inpatient Versus Outpatient Surgery: A Comparison of Postoperative Mortality and Morbidity in Elective Operations.

BACKGROUND: Operations performed outpatient offer several benefits. The prevalence of outpatient operations is growing. Consequently, the proportion of patients with multiple comorbidities undergoing outpatient surgery is increasing. We compared 30-day mortality and overall morbidity between outpatient and inpatient elective operations. METHODS: Using the 2005-2018 ACS-NSQIP database, we evaluated trends in percent of hospital outpatient operations performed over time, and the percent of operations done outpatient versus inpatient by CPT code. Patient characteristics were compared for outpatient versus inpatient operations. We compared unadjusted and risk-adjusted 30-day mortality and morbidity for inpatient and outpatient operations. RESULTS: A total of 6,494,298 patients were included. The proportion of outpatient operations increased over time, from 37.8% in 2005 to 48.2% in 2018. We analyzed the 50 most frequent operations performed outpatient versus inpatient 25-75% of the time (n = 1,743,097). Patients having outpatient operations were younger (51.6 vs 54.6 years), female (70.3% vs 67.3%), had fewer comorbidities, and lower ASA class (I-II, 69.3% vs. 59.9%). On both unadjusted and risk-adjusted analysis, 30-day mortality and overall morbidity were less likely in outpatient versus inpatient operations. CONCLUSION: In this large multi-specialty analysis, we found that patients undergoing outpatient surgery had lower risk of 30-day morbidity and mortality than those undergoing the same inpatient operation. Patients having outpatient surgery were generally healthier, suggesting careful patient selection occurred even with increasing outpatient operation frequency. Patients and providers can feel reassured that outpatient operations are a safe, reasonable option for selected patients.

A coordinated approach for managing polypharmacy among children with medical complexity: rationale and design of the Pediatric Medication Therapy Management (pMTM) randomized controlled trial.

BACKGROUND: Children with medical complexity (CMC) often rely upon the use of multiple medications to sustain quality of life and control substantial symptom burden. Pediatric polypharmacy (≥ 5 concurrent medications) is prevalent and increases the risk of medication-related problems (MRPs). Although MRPs are associated with pediatric morbidity and healthcare utilization, polypharmacy is infrequently assessed during routine clinical care for CMC. The aim of this randomized controlled trial is to determine if a structured pharmacist-led Pediatric Medication Therapy Management (pMTM) intervention reduces MRP counts, as well as the secondary outcomes of symptom burden and acute healthcare utilization. METHODS: This is a hybrid type 2 randomized controlled trial assessing the effectiveness of pMTM compared to usual care in a large, patient-centered medical home for CMC. Eligible patients include all children ages 2-18 years old, with ≥ 1 complex chronic condition, and with ≥ 5 active medications, as well as their English-speaking primary caregivers. Child participants and their primary parental caregivers will be randomized to pMTM or usual care before a non-acute primary care visit and followed for 90 days. Using generalized linear models, the overall effectiveness of the intervention will be evaluated using total MRP counts at 90 days following pMTM intervention or usual care visit. Following attrition, a total of 296 CMC will contribute measurements at 90 days, which provides > 90% power to detect a clinically significant 1.0 reduction in total MRPs with an alpha level of 0.05. Secondary outcomes include Parent-Reported Outcomes of Symptoms (PRO-Sx) symptom burden scores and acute healthcare visit counts. Program replication costs will be assessed using time-driven activity-based scoring. DISCUSSION: This pMTM trial aims to test hypotheses that a patient-centered medication optimization intervention delivered by pediatric pharmacists will result in lower MRP counts, stable or improved symptom burdens, and fewer cumulative acute healthcare encounters at 90 days following pMTM compared to usual care. The results of this trial will be used to quantify medication-related outcomes, safety, and value for a high-utilization group of CMC, and outcomes may elucidate the role of integrated pharmacist services as a key component of outpatient complex care programs for this priority pediatric population. TRIAL REGISTRATION: This trial was prospectively registered at clinicaltrials.gov (NCT05761847) on Feb 25, 2023.

Dissemination and Implementation of a Community Health Worker Intervention for Disparities in Palliative Care (DeCIDE PC): a study protocol for a hybrid type 1 randomized controlled trial.

BACKGROUND: There are persistent racial and ethnic health disparities in end-of-life health outcomes in the United States. African American patients are less likely than White patients to access palliative care, enroll in hospice care, have documented goals of care discussions with their healthcare providers, receive adequate symptom control, or die at home. We developed Community Health Worker Intervention for Disparities in Palliative Care (DeCIDE PC) to address these disparities. DeCIDE PC is an integrated community health worker (CHW) palliative care intervention that uses community health workers (CHWs) as care team members to enhance the receipt of palliative care for African Americans with advanced cancer. The overall objectives of this study are to (1) assess the effectiveness of the DeCIDE PC intervention in improving palliative care outcomes amongst African American patients with advanced solid organ malignancy and their informal caregivers, and (2) develop generalizable knowledge on how contextual factors influence implementation to facilitate dissemination, uptake, and sustainability of the intervention. METHODS: We will conduct a multicenter, randomized, assessor-blind, parallel-group, pragmatic, hybrid type 1 effectiveness-implementation trial at three cancer centers across the United States. The DeCIDE PC intervention will be delivered over 6 months with CHW support tailored to the individual needs of the patient and caregiver. The primary outcome will be advance care planning. The treatment effect will be modeled using logistic regression. The secondary outcomes are quality of life, quality of communication, hospice care utilization, and patient symptoms. DISCUSSION: We expect the DeCIDE PC intervention to improve integration of palliative care, reduce multilevel barriers to care, enhance clinic and patient linkage to resources, and ultimately improve palliative care outcomes for African American patients with advanced cancer. If found to be effective, the DeCIDE PC intervention may be a transformative model with the potential to guide large-scale adoption of promising strategies to improve palliative care use and decrease disparities in end-of-life care for African American patients with advanced cancer in the United States. TRIAL REGISTRATION: Registered on ClinicalTrials.gov (NCT05407844). First posted on June 7, 2022.

Comparing neoadjuvant chemotherapy with or without radiation therapy for pancreatic ductal adenocarcinoma: National Cancer Database cohort analysis.

BACKGROUND: Neoadjuvant treatment is important for improving the rate of R0 surgical resection and overall survival outcome in treating patients with pancreatic ductal adenocarcinoma (PDAC). However, the true efficacy of radiotherapy (RT) for neoadjuvant treatment of PDAC is uncertain. This retrospective study evaluated the treatment outcome of neoadjuvant RT in the treatment of PDAC. METHODS: Collected from the National Cancer Database, information on patients with PDAC who underwent neoadjuvant chemotherapy (NAC) and pancreatectomy between 2010 to 2016 was used in this study. Short- and long-term outcomes were compared between patients who received neoadjuvant chemoradiotherapy (NACRT) and NAC. RESULTS: The study included 6936 patients, of whom 3185 received NACRT and 3751 NAC. The groups showed no difference in overall survival (NACRT 16.1 months versus NAC 17.4 months; P = 0.054). NACRT is associated with more frequent margin negative resection (86.1 versus 80.0 per cent; P < 0.001) but a more unfavourable 90-day mortality than NAC (6.4 versus 3.6 per cent; P < 0.001). The odds of 90-day mortality were higher in the radiotherapy group (odds ratio 1.81; P < 0.001), even after adjusting for significant covariates. Patients who received NACRT received single-agent chemotherapy more often than those who received NAC (31.5 versus 10.7 per cent; P < 0.001). CONCLUSION: This study failed to show a survival benefit for NACRT over NAC alone, despite its association with negative margin resection. The significantly higher mortality in NACRT warrants further investigation into its efficacy in the treatment of pancreatic cancer.

Using the Surgical Risk Preoperative Assessment System to Define the "High Risk" Surgical Patient.

BACKGROUND: Defining a "high risk" surgical population remains challenging. Using the Surgical Risk Preoperative Assessment System (SURPAS), we sought to define "high risk" groups for adverse postoperative outcomes. MATERIALS AND METHODS: We retrospectively analyzed the 2009-2018 American College of Surgeons National Surgical Quality Improvement Program database. SURPAS calculated probabilities of 12 postoperative adverse events. The Hosmer Lemeshow graphs of deciles of risk and maximum Youden index were compared to define "high risk." RESULTS: Hosmer-Lemeshow plots suggested the "high risk" patient could be defined by the 10th decile of risk. Maximum Youden index found lower cutoff points for defining "high risk" patients and included more patients with events. This resulted in more patients classified as "high risk" and higher number needed to treat to prevent one complication. Some specialties (thoracic, vascular, general) had more "high risk" patients, while others (otolaryngology, plastic) had lower proportions. CONCLUSIONS: SURPAS can define the "high risk" surgical population that may benefit from risk-mitigating interventions.

Associations Between Preoperative Risk, Postoperative Complications, and 30-Day Mortality.

BACKGROUND: Comorbidities and postoperative complications increase mortality, making early recognition and management critical. It is useful to understand how they are associated with one another. This study assesses associations between comorbidities, complications, and mortality. METHODS: We calculated associations between comorbidities, complications, and 30-day mortality using the 2012-2018 ACS-NSQIP database. We examined the association between mortality and number of complications which complications were most associated with mortality. RESULTS: 5,777,108 patients were included. 30-day mortality was 0.95%. For most comorbidities or postoperative complications, patients with these had higher mortality than patients without. Having ≥ 1 complication increased mortality risk by 32.5-fold (6.5% vs. 0.2%). Mortality rate significantly increased with increasing number of complications, particularly after two or more complications. Bleeding and sepsis were associated with the most deaths. CONCLUSION: The 30-day mortality rate was < 1% but was 32-fold higher in patients with complications and increased rapidly for patients with ≥ 2 complications. Bleeding and sepsis were the most prominent complications associated with mortality.

Open Chest Duration Following Congenital Cardiac Surgery Increases Risk for Surgical Site Infection.

Surgical site infections (SSI) following congenital heart surgery (CHS) remain a significant source of morbidity. Delayed sternal closure (DSC) is often required to minimize the potential for hemodynamic instability. The purpose of this study was to determine the incidence of SSI among patients undergoing DSC versus primary chest closure (PCC) and to define a potential inflection point for increased risk of SSI as a function of open chest duration (OCD).A retrospective review of our institutional Society of Thoracic Surgeons dataset is to identify patients undergoing CHS at our institution between 2015 and 2020. Incidences of SSI were compared between DSC and PCC patients. DSC patients were evaluated to determine the association of OCD and the incidence of SSI.2582 operations were performed at our institution between 2015 and 2020, including 195 DSC and 2387 PCC cases. The incidence of SSI within the cohort was 1.8% (47/2,582). DSC patients had significantly higher incidences of SSI (17/195, 8.7%) than PCC patients (30/2387, 1.3%, p < 0.001). Further, patients with an OCD of four or more days had a significantly higher incidence of SSI (11/62, 17.7%, p = 0.006) than patients with an OCD less than 4 days (6/115, 5.3%).The incidence of SSI following CHS is higher in DSC patients compared to PCC patients. Prolonged OCD of 4 days or more significantly increases the risk of SSI and represents a potentially modifiable risk factor for SSI predisposition. These data support dedicated, daily post-operative assessment of candidacy for chest closure to minimize the risk of SSI.

Development and Validation of a Predictive Model of the Risk of Pediatric Septic Shock Using Data Known at the Time of Hospital Arrival.

OBJECTIVE: To derive and validate a model of risk of septic shock among children with suspected sepsis, using data known in the electronic health record at hospital arrival. STUDY DESIGN: This observational cohort study at 6 pediatric emergency department and urgent care sites used a training dataset (5 sites, April 1, 2013, to December 31, 2016), a temporal test set (5 sites, January 1, 2017 to June 30, 2018), and a geographic test set (a sixth site, April 1, 2013, to December 31, 2018). Patients 60 days to 18 years of age in whom clinicians suspected sepsis were included; patients with septic shock on arrival were excluded. The outcome, septic shock, was systolic hypotension with vasoactive medication or ≥30 mL/kg of isotonic crystalloid within 24 hours of arrival. Elastic net regularization, a penalized regression technique, was used to develop a model in the training set. RESULTS: Of 2464 included visits, septic shock occurred in 282 (11.4%). The model had an area under the curve of 0.79 (0.76-0.83) in the training set, 0.75 (0.69-0.81) in the temporal test set, and 0.87 (0.73-1.00) in the geographic test set. With a threshold set to 90% sensitivity in the training set, the model yielded 82% (72%-90%) sensitivity and 48% (44%-52%) specificity in the temporal test set, and 90% (55%-100%) sensitivity and 32% (21%-46%) specificity in the geographic test set. CONCLUSIONS: This model estimated the risk of septic shock in children at hospital arrival earlier than existing models. It leveraged the predictive value of routine electronic health record data through a modern predictive algorithm and has the potential to enhance clinical risk stratification in the critical moments before deterioration.

Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data.

BACKGROUND: With cardiovascular disease increasing, substantial research has focused on the development of prediction tools. We compare deep learning and machine learning models to a baseline logistic regression using only 'known' risk factors in predicting incident myocardial infarction (MI) from harmonized EHR data. METHODS: Large-scale case-control study with outcome of 6-month incident MI, conducted using the top 800, from an initial 52 k procedures, diagnoses, and medications within the UCHealth system, harmonized to the Observational Medical Outcomes Partnership common data model, performed on 2.27 million patients. We compared several over- and under- sampling techniques to address the imbalance in the dataset. We compared regularized logistics regression, random forest, boosted gradient machines, and shallow and deep neural networks. A baseline model for comparison was a logistic regression using a limited set of 'known' risk factors for MI. Hyper-parameters were identified using 10-fold cross-validation. RESULTS: Twenty thousand Five hundred and ninety-one patients were diagnosed with MI compared with 2.25 million who did not. A deep neural network with random undersampling provided superior classification compared with other methods. However, the benefit of the deep neural network was only moderate, showing an F1 Score of 0.092 and AUC of 0.835, compared to a logistic regression model using only 'known' risk factors. Calibration for all models was poor despite adequate discrimination, due to overfitting from low frequency of the event of interest. CONCLUSIONS: Our study suggests that DNN may not offer substantial benefit when trained on harmonized data, compared to traditional methods using established risk factors for MI.

Differences in the Epstein-Barr Virus gp350 IgA Antibody Response Are Associated With Increased Risk for Coinfection With a Second Strain of Epstein-Barr Virus.

BACKGROUND: The Epstein-Barr virus (EBV) viral glycoprotein gp350 has been proposed as a candidate antigen for an EBV vaccine. However, the proposed formulations of these vaccines have not taken into account the presence of 2 unique EBV strains (EBV-1 and EBV-2) present in areas of high incidence of the EBV-associated cancer, Burkitt lymphoma. METHODS: In this study, we analyze the kinetics of EBV-1 and EBV-2 infection in an asymptomatic infant cohort from Kisumu, Kenya. We also analyzed the kinetics of the antibody response against 5 EBV antigens, gp350 (IgG and IgA), VCA (IgG), EBNA-1 (IgG), EAd (IgG), and Zta (IgG). RESULTS: We observed a high frequency of coinfection with both EBV types over time, with the only observable defect in the antibody response in infants coinfected being a significantly lower level of anti-gp350 IgA at peak response. Gp350 IgA levels were also significantly lower in coinfected infants 2.5 months postinfection and at the time of coinfection. CONCLUSIONS: These results suggest that anti-gp350 IgA antibodies may be important for sterilizing immunity against secondary infection. These findings have implications for the development of an efficacious EBV vaccine to prevent both EBV-1 and EBV-2 infection in a population at high risk for Burkitt lymphoma.

Duration of use of oral cannabis extract in a cohort of pediatric epilepsy patients.

OBJECTIVE: Oral cannabis extracts (OCEs) are being used in the treatment of epilepsy with increasing rates in the United States following product legalization; however, no studies demonstrate clear efficacy. We evaluated the duration of use of OCEs as a measure of perceived benefit in a cohort of patients with pediatric epilepsy. METHODS: Retrospective chart review was performed of children and adolescents who were given OCEs for treatment of epilepsy. RESULTS: Of the 119 patients included in the analysis, 71% terminated use of their OCE product during the study period. The average length of use of OCE was 11.7 months (range 0.3-57 months). Perceived seizure benefit was the only factor associated with longer duration of treatment with OCE (p < 0.01). Relocation to Colorado was associated with perceived benefit of OCEs for seizures (65% vs. 38%, p = 0.01), but was not independently associated with longer OCE use. Factors associated with shorter use included adverse effects (p = 0.03) and a diagnosis of Dravet syndrome (p = 0.02). Twenty-four percent of patients were considered OCE responders, which was defined by a parent's report of a > 50% reduction in seizures while on this therapy. Adverse events (AEs) were reported in 19% of patients, with the most common side effects being somnolence and worsening of seizures. SIGNIFICANCE: Parental report of OCE use in refractory pediatric epilepsy suggests that some families perceive benefit from this therapy; however, discontinuation of these products is common. Duration appears to be affected by logical factors, such as perceived benefit and side effect profile. Surprisingly, families of patients with Dravet syndrome terminated use of OCEs more quickly than patients with other epilepsy syndromes. Results from this study highlight the need for rigorous clinical studies to characterize the efficacy and safety of OCEs, which can inform discussions with patients and families.

Video studies of passage by Anopheles gambiae mosquitoes through holes in a simulated bed net: effects of hole size, hole orientation and net environment.

BACKGROUND: Holes in netting provide potential routes for mosquitoes to enter ITNs. Despite this, there is little information on how mosquitoes respond to holes in bed nets and how their responses are affected by hole size, shape and orientation or by ambient conditions around the net. METHODS: Female Anopheles gambiae (G3) were recorded in a simulated bed net consisting of two sizes of untreated netting-covered behavioural arenas placed above and beside (to simulate the bed net roof and sides respectively) the experimenter who was a source of host cues from 'inside' the net. A round hole of 9 mm or 13 mm diameter was cut into the centre of the netting of each arena. Videos of unfed female mosquitoes in arenas were analysed for time spent flying, walking and standing still and for exit through the hole. The effects of the experimenter on temperature and relative humidity around the simulated net were also measured. RESULTS: Mosquitoes were significantly more active in overhead arenas than in arenas to the side. Hole passage was significantly more likely in smaller arenas than larger ones and for larger holes than smaller ones. In arenas to the side, hole passage rate through small holes was about 50% less likely than what could be explained by area alone. Passage rate through holes in overhead arenas was consistent with hole area. Temperature in arenas did not strongly reflect the experimenter's presence in the simulated net. Relative humidity and absolute humidity in overhead arenas, but not in arenas to the side, were immediately affected by experimenter presence. CONCLUSIONS: Higher levels of activity in overhead arenas than in arenas to the side were likely due to the rising heat and humidity plume from the experimenter. Lower than expected passage rates through smaller vertically oriented holes may have been be due to an edge effect that does not apply to horizontally oriented holes. Results suggest that current methods of assessing the importance of physical damage to ITNs may not accurately reflect mosquito entry risk in all cases.

Primary Author Characteristics Associated With Publication in the Journal of Pain and Symptom Management.

CONTEXT: Scientific journals are the primary source for dissemination of research findings, and this process relies on rigorous editorial and peer-review. As part of continuing efforts by the Journal of Pain and Symptom Management (JPSM) to advance equity, diversity, and inclusion, JPSM's leadership requested an external evaluation of their publication decisions. OBJECTIVES: 1) Describe primary author characteristics associated with final decisions to accept or reject manuscripts submitted for publication; 2) Report on whether there are potential publication biases in the JPSM editorial or peer-review processes. METHODS: Data consisted of self-reported primary author demographic characteristics associated with manuscript submissions between June 18, 2020, and December 31, 2022. Characteristics included region of residence, race, gender, and ethnicity. A multiple logistic regression model was used to estimate adjusted odds of rejection for each author characteristic. RESULTS: A total of 1940 submissions were evaluated. Compared to authors residing in North America, authors residing in Asia had six-fold greater odds of rejection, authors residing in Europe had four-fold greater odds of rejection, and authors residing in other regions had two-fold greater odds of rejection. Female authors submitted 1.7 times more papers than males, but there was no difference in acceptance rates of their papers in adjusted analysis. CONCLUSION: In this analysis of publication decisions by the JPSM, there were differences in acceptance rates by region of residence, ethnicity, and race but not by gender. Asian authors and authors residing in regions outside of North America had greater odds of rejection compared to White or North American authors.