Handling missing data in clinical research

Mental health after lumbar spine surgery: cognitive appraisal processes and outcome in a longitudinal cohort study

BACKGROUND CONTEXT

A not uncommon finding following spine surgery is that many patients do not achieve mental health improvement up to population norms for their age cohort, despite improvement in pain and functioning.

PURPOSE

This study examined how patients who were categorized as depressed versus not depressed think about health-related quality of life as assessed by cognitive-appraisal processes. It examined cross-sectional and longitudinal differences over 12 months postsurgery.

DESIGN

Prospective longitudinal cohort study with data collected at presurgery and at ∼3- and ∼12-months postsurgery from August 2013 to August 2023.

PATIENT SAMPLE

We included 173 adults undergoing lumbar spine surgery for degenerative spinal conditions at an academic medical center. The study sample was 47% female, with a mean age of 61 (SD=15.0), and a median level of education of college graduate.

OUTCOME MEASURES

Depression was defined as a Mental Component Score (MCS)≤38 on the Rand-36, building on studies that equated MCS scores with significant depression as assessed by clinically validated depression scales. The Quality-of-Life Appraisal Profile assessed the cognitive-appraisal domains of Experience Sampling and Standards of Comparison.

METHODS

The analysis focused on two comparisons: cross-sectionally comparing those who were not depressed (n=82) to those who were depressed (n=77) at baseline; and comparing longitudinal trajectories among those depressed before surgery and improved (n=54) versus did not improve (n=23). T-tests characterized group differences in appraisal endorsement; analysis of variance evaluated appraisal items in terms of explained variance; and Pearson correlation coefficients assessed direction of association in predicting mental health.

RESULTS

There were presurgical and longitudinal differences in both cognitive appraisal domains. Before surgery, depressed patients were less likely than nondepressed patients to endorse emphasizing the positive; more likely to focus on worst moments, recent flare-ups, their spinal condition, and the future; and more likely to compare themselves to high aspirations (eg, perfect health). Over time, among those who were depressed before surgery, those who improved focused decreasingly on worst moments and on the time before their spinal condition, and increasingly on emphasizing the positive and balancing the positives/negatives. Appraisal explained more variance in mental health among those who did not improve as compared to those who did, at all timepoints. All appraisal items were more highly correlated with mental health among those who remained depressed as compared to those who improved, particularly over time.

CONCLUSIONS

Endorsement of cognitive appraisal processes was different for depressed versus nondepressed spine-surgery patients before surgery and distinguished those who were depressed before surgery and improved versus those who did not improve. These findings suggest that targeted interventions could be beneficial for addressing mental health concerns during the spine surgery recovery trajectory. These interventions might use appraisal measures to identify patients likely to remain depressed after surgery, and then focus on helping these patients shift their focus and standards of comparison.

Quality over quantity: powering neuroimaging samples in psychiatry

Neuroimaging has been widely adopted in psychiatric research, with hopes that these non-invasive methods will provide important clues to the underpinnings and prediction of various mental health symptoms and outcomes. However, the translational impact of neuroimaging has not yet reached its promise, despite the plethora of computational methods, tools, and datasets at our disposal. Some have lamented that too many psychiatric neuroimaging studies have been underpowered with respect to sample size. In this review, we encourage this discourse to shift from a focus on sheer increases in sample size to more thoughtful choices surrounding experimental study designs. We propose considerations at multiple decision points throughout the study design, data modeling and analysis process that may help researchers working in psychiatric neuroimaging boost power for their research questions of interest without necessarily increasing sample size. We also provide suggestions for leveraging multiple datasets to inform each other and strengthen our confidence in the generalization of findings to both population-level and clinical samples. Through a greater emphasis on improving the quality of brain-based and clinical measures rather than merely quantity, meaningful and potentially translational clinical associations with neuroimaging measures can be achieved with more modest sample sizes in psychiatry.

Assessing the feasibility and acceptability of a diabetes-specific nurse-led multicomponent smoking cessation intervention in diabetes education: study protocol for an open-label pragmatic randomised controlled trial

INTRODUCTION

Smoking cessation is an essential, but often overlooked aspect of diabetes management. Despite the need for tailored smoking cessation support for individuals with diabetes, evidence of effective interventions for this cohort is limited. Additionally, individuals with diabetes do not easily adopt such interventions, resulting in low uptake and abstinence rates. This protocol describes a study that aims to assess the feasibility and acceptability of a unique smoking cessation intervention, based on the best evidence, theory and the needs of individuals with diabetes, among patients and service providers, the diabetes nurse educators.

METHODS AND ANALYSIS

This is an open-label pragmatic randomised controlled trial. Between 80 and 100 individuals with type 1 or type 2 diabetes who smoke will be recruited from the diabetes outpatients at the main acute public hospital in Malta, starting in August 2023. Participants will be randomly assigned (1:1 ratio) to the intervention or control arm for 12 weeks. The experimental intervention will consist of three to four smoking cessation behavioural support sessions based on the 5As (Ask, Advise, Assess, Assist and Arrange) algorithm, and a 6-week supply of nicotine replacement therapy. The control intervention will consist of an active referral to the Maltese National Health Service's one-to-one smoking cessation support service, which is based on motivational interviewing. The primary feasibility and acceptability outcomes include the recruitment and participation rates, resources used, problems identified by the nurses, the nurses' perceived challenges and facilitators to implementation and the nurses' and patients' acceptability of the study intervention. Data analyses will be descriptive, with quantitative feasibility and acceptability outcomes reported with 95% confidence intervals.

ETHICS AND DISSEMINATION

Ethical clearance was obtained from the Faculty of Health Sciences Research Ethics Committee, University of Malta. The study results will be disseminated through conference presentations and a publication in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

NCT05920096.

Advancing equitable access to digital mental health in the Asia-Pacific region in the context of the COVID-19 pandemic and beyond: A modified Delphi consensus study

The COVID-19 pandemic had an unprecedented impact on global mental health and well-being, including across the Asia-Pacific. Efforts to mitigate virus spread led to far-reaching disruption in the delivery of health and social services. In response, there was a rapid shift to the use of digital mental health (DMH) approaches. Though these technologies helped to improve access to care for many, there was also substantial risk of access barriers leading to increased inequities in access to mental health care, particularly among at-risk and equity-deserving populations. The objective of this study was to conduct a needs assessment and identify priorities related to equitable DMH access among at-risk and equity-deserving populations in the Asia Pacific region during the first year of the COVID-19 pandemic. The study consisted of a modified Delphi consensus methodology including two rounds of online surveys and online consultations with stakeholders from across the region. Study participants included policy makers, clinicians and service providers, and people with lived experience of mental health conditions. Results demonstrate that vulnerabilities to negative mental health impacts and access barriers were compounded during the pandemic. Access barriers included a lack of linguistically and culturally appropriate DMH options, low mental health literacy and poor access to technological infrastructure and devices, low levels of awareness and trust of DMH options, and lack of policies and guidelines to support effective and equitable delivery of DMH. Recommendations to improve equitable access include ensuring that diverse people with lived experience are engaged in research, co-design and policy development, the development and implementation of evidence-based and equity-informed guidelines and frameworks, clear communication about DMH evidence and availability, and the integration of DMH into broader health systems. Study results can inform the development and implementation of equitable DMH as its use becomes more widespread across health systems.

Moderators of treatment effect of non-steroidal anti-inflammatory drugs for patients with (sub) acute low back pain: Protocol for a systematic review with individual participant data meta-analysis

A Cochrane review found that non-steroidal anti-inflammatory drugs (NSAIDs) are slightly more effective than placebo on acute and subacute low back pain (LBP) outcomes (pain intensity, disability, and global improvement). Our objectives are: (1) to assess the overall treatment effect of NSAIDs in adults with acute and subacute LBP; (2) to identify the moderation of baseline patients' characteristics on treatment effect. We will conduct a systematic search of RCTs on effectiveness of NSAIDs compared with placebo in adults with non-chronic LBP in Medline ALL, Embase, Cochrane Central Register of Controlled Trials*. We will screen the records after January 2020, and include eligible RCTs before January 2020 screened by the Cochrane review mentioned above. Our primary outcomes are pain intensity, disability, and health-related quality of life, secondary outcomes are adverse events. Our IPD dataset will consist of the information on each eligible trial characteristics and included variables according to a predefined coding scheme. We will assess risk-of-bias of included RCTs with the Cochrane Risk Of Bias (RoB)-2 assessment tool. We will perform power calculations with closed-form solutions and prioritize a one-stage approach for IPD-MA. For reporting the results, we will adhere to the PRISMA-IPD statement.

Low socioeconomic status is associated with worse treatment outcomes in patients with Achilles tendinopathy

OBJECTIVE

To assess whether there is a difference in symptom severity at baseline and 24 weeks follow-up between conservatively managed patients with Achilles tendinopathy (AT) with low socioeconomic status (SES) compared with those with high SES.

METHODS

In this prospective cohort study, 200 patients with AT were included and treated according to current guidelines. We linked a neighbourhood SES indicator based on income, employment and education level and divided the patient population into quintiles, with Q1 being the highest SES and Q5 the lowest. Symptom severity at baseline and follow-up was assessed using the Victorian Institute of Sports Assessment-Achilles (VISA-A) score. Treatment adherence was not measured. We used a general linear model and the mean VISA-A scores at baseline and at 6, 12 and 24 weeks follow-up were compared between Q1 (n=45) and Q5 (n=39), while adjusting for age, sex, body mass index (BMI), Ankle Activity Score, symptom duration and baseline VISA-A score.

RESULTS

Patients had a median age of 51 years and median BMI of 25.4, 40% were female. 74%, 70% and 58% of the participants completed the VISA-A at 6, 12 and 24 weeks, respectively. VISA-A scores at baseline were similar for Q1 and Q5 (43.9 and 41.8, p=0.591). At 24 weeks, there was a mean (95% CI) difference of 11.2 (1.0 to 21.3, p=0.032) points in favour of Q1 on the VISA-A score.

CONCLUSION

AT patients with low SES may have worse outcomes when treated using the current guidelines. The difference in VISA-A score at 24 weeks is larger than the minimal clinically important difference and might be clinically relevant, but comes with uncertainty due to the large dispersion in the data. Clinicians need to consider the impact of social inequality when developing and implementing treatment plans.

The association between alcohol retail access and health care visits attributable to alcohol for individuals with and without a history of alcohol-related health-care use

BACKGROUND AND AIMS

Alcohol retail access is associated with alcohol use and related harms. This study measured whether this association differs for people with and without heavy and disordered patterns of alcohol use.

DESIGN

The study used a repeated cross-sectional analysis of health administrative databases.

SETTING, PARTICIPANTS/CASES

All residents of Ontario, Canada aged 10-105 years with universal health coverage (n = 10 677 604 in 2013) were included in the analysis.

MEASUREMENTS

Quarterly rates of emergency department (ED) and outpatient visits attributable to alcohol in 464 geographic regions between 2013 and 2019 were measured. Quarterly off-premises alcohol retail access scores were calculated (average drive to the closest seven stores) for each geographic region. Mixed-effect linear regression models adjusted for area-level socio-demographic covariates were used to examine associations between deciles of alcohol retail access and health-care visits attributable to alcohol. Stratified analyses were run for individuals with and without prior alcohol-attributable health-care use in the past 2 years.

FINDINGS

We included 437 707 ED visits and 505 271 outpatient visits attributable to alcohol. After adjustment, rates of ED visits were 39% higher [rate ratio (RR) = 1.39, 95% confidence interval (CI) = 1.20-1.61] and rates of outpatient visits were 49% higher (RR = 1.49, 95% CI = 1.26-1.75) in the highest versus lowest decile of alcohol access. There was a positive association between alcohol access and outpatient visits attributable to alcohol for individuals without prior health-care attributable to alcohol (RR = 1.65, 95% CI = 1.39-1.95 for the highest to lowest decile of alcohol access) but not for individuals with prior health-care attributable to alcohol (RR = 1.08, 95% CI = 0.90-1.30). There was a positive association between alcohol access and ED visits attributable to alcohol for individuals with and without prior health-care for alcohol for ED visits.

CONCLUSION

In Ontario, Canada, greater alcohol retail access appears to be associated with higher rates of emergency department (ED) and outpatient health-care visits attributable to alcohol. Individuals without prior health-care for alcohol may be more susceptible to greater alcohol retail access for outpatient but not ED visits attributable to alcohol.

A Principled Approach to Characterize and Analyze Partially Observed Confounder Data from Electronic Health Records

Objective

Partially observed confounder data pose challenges to the statistical analysis of electronic health records (EHR) and systematic assessments of potentially underlying missingness mechanisms are lacking. We aimed to provide a principled approach to empirically characterize missing data processes and investigate performance of analytic methods.

Methods

Three empirical sub-cohorts of diabetic SGLT2 or DPP4-inhibitor initiators with complete information on HbA1c, BMI and smoking as confounders of interest (COI) formed the basis of data simulation under a plasmode framework. A true null treatment effect, including the COI in the outcome generation model, and four missingness mechanisms for the COI were simulated: completely at random (MCAR), at random (MAR), and two not at random (MNAR) mechanisms, where missingness was dependent on an unmeasured confounder and on the value of the COI itself. We evaluated the ability of three groups of diagnostics to differentiate between mechanisms: 1)-differences in characteristics between patients with or without the observed COI (using averaged standardized mean differences [ASMD]), 2)-predictive ability of the missingness indicator based on observed covariates, and 3)-association of the missingness indicator with the outcome. We then compared analytic methods including "complete case", inverse probability weighting, single and multiple imputation in their ability to recover true treatment effects.

Results

The diagnostics successfully identified characteristic patterns of simulated missingness mechanisms. For MAR, but not MCAR, the patient characteristics showed substantial differences (median ASMD 0.20 vs 0.05) and consequently, discrimination of the prediction models for missingness was also higher (0.59 vs 0.50). For MNAR, but not MAR or MCAR, missingness was significantly associated with the outcome even in models adjusting for other observed covariates. Comparing analytic methods, multiple imputation using a random forest algorithm resulted in the lowest root-mean-squared-error.

Conclusion

Principled diagnostics provided reliable insights into missingness mechanisms. When assumptions allow, multiple imputation with nonparametric models could help reduce bias.

Maternal pre-pregnancy overweight or obesity and risk of birth defects in offspring: Population-based cohort study

INTRODUCTION

Maternal obesity, a health condition increasingly prevalent worldwide, has been suggested to be associated with a higher risk of birth defects in offspring, whereas evidence from population-based data from China was largely lacking. Additionally, the role of gestational diabetes in the association between maternal obesity and birth defects remains unclear. We aimed to investigate the association of maternal pre-pregnancy overweight or obesity with any and different types of birth defects in offspring and the interaction between pre-pregnancy overweight or obesity and gestational diabetes.

MATERIAL AND METHODS

We conducted a population-based cohort study including 257 107 singletons born between 2015 and 2021 in Longgang District, Shenzhen, China, using data from the Shenzhen Maternal and Child Health Management System. Poisson regression was conducted to estimate the associations of maternal pre-pregnancy overweight or obesity, as well as the interaction between pre-pregnancy overweight or obesity and gestational diabetes, with the risk of birth defects. Models were adjusted for maternal age at delivery, educational level, type of household registration, and gravidity.

RESULTS

Maternal pre-pregnancy overweight was associated with a higher risk of any birth defect (risk ratio [RR] 1.21, 95% confidence interval [CI] 1.12 to 1.31) as well as of congenital malformations of the circulatory system (RR 1.26, 95% CI 1.12 to 1.41), eye/ear/face/neck (RR 1.42, 95% CI 1.04 to 1.94), and musculoskeletal system (RR 1.21, 95% CI 1.01 to 1.44). Maternal pre-pregnancy obesity was associated with a higher risk of any birth defect (RR 1.38, 95% CI 1.18 to 1.63) and congenital malformations of the circulatory system (RR 1.61, 95% CI 1.30 to 1.98). Infants born to overweight or obese mothers with gestational diabetes had a higher risk of congenital malformations of the circulatory system than infants born to overweight or obese mothers without gestational diabetes.

CONCLUSIONS

Maternal pre-pregnancy overweight or obesity was associated with a higher risk of birth defects, particularly congenital malformations of the circulatory system, in offspring. Gestational diabetes interacts additively with pre-pregnancy overweight or obesity on modifying the risk of congenital malformations of the circulatory system. The importance of improving weight management and assessment of glucose and metabolic functions was emphasized among women planning for pregnancy who are overweight or obese.

Did temporomandibular gap arthroplasty with temporalis interpositional flap improve function and pain in patients with end-stage joint disease? A 5-year retrospective follow-up

The primary aim of this study was to investigate whether patients with end-stage temporomandibular joint (TMJ) disease treated with gap arthroplasty with temporalis interpositional flap (GAT) had improved maximal interincisal opening (MIO) and TMJ pain in a long-term perspective. All patients with severe osteoarthritis, or fibrous or bony ankyloses, and subjected to GAT between 2008 and 2015 were included. The criteria of treatment success were TMJ pain VAS score ≤4 and MIO ≥30 mm. Reoperation was considered as a failure. Forty-four patients (mean age 47 years) were included in this retrospective descriptive case series and followed up for up to 7 years (mean 4.5). Comorbidities were frequent (n = 34) and most commonly rheumatic disease (n = 17). The indications for surgery were ankylosis (n = 32) or severe osteoarthritis (n = 12). Of the 44 included patients, 84% (n = 37) had a history of earlier TMJ surgery. The preoperative mean values for TMJ pain and MIO (VAS 7 and 23 mm, respectively) changed significantly (p < 0.001) to postoperative means of VAS 3 and 34 mm, respecitvely. The success rate was 59% (n = 26). When compared with a previous 2-year follow-up, the success rate was found to have decreased over time (p = 0.0097). The rate of successful treatment outcome in terms of MIO alone was 82% (n = 36). The most common reason for treatment failure was residual pain. In conclusion, the success-rate after GAT did not show long-term stability and continued to drop over time in this patient cohort. TMJ pain seems to be the main reason for failure.

Optimizing perinatal wellbeing in pregnancy with obesity: a clinical trial with a multi-component nutrition intervention for prevention of gestational diabetes and infant growth and neurodevelopment impairment

Pregnancy complicated by obesity represents an increased risk of unfavorable perinatal outcomes such as gestational diabetes mellitus (GDM), hypertensive disorders in pregnancy, preterm birth, and impaired fetal growth, among others. Obesity is associated with deficiencies of micronutrients, and pregnant women with obesity may have higher needs. The intrauterine environment in pregnancies complicated with obesity is characterized by inflammation and oxidative stress, where maternal nutrition and metabolic status have significant influence and are critical in maternal health and in fetal programming of health in the offspring later in life. Comprehensive lifestyle interventions, including intensive nutrition care, are associated with a lower risk of adverse perinatal outcomes. Routine supplementation during pregnancy includes folic acid and iron; other nutrient supplementation is recommended for high-risk women or women in low-middle income countries. This study is an open label randomized clinical trial of parallel groups (UMIN Clinical Trials Registry: UMIN000052753, https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000060194) to evaluate the effect of an intensive nutrition therapy and nutrient supplementation intervention (folic acid, iron, vitamin D, omega 3 fatty acids, myo-inositol and micronutrients) in pregnant women with obesity on the prevention of GDM, other perinatal outcomes, maternal and newborn nutritional status, and infant growth, adiposity, and neurodevelopment compared to usual care. Given the absence of established nutritional guidelines for managing obesity during pregnancy, there is a pressing need to develop and implement new nutritional programs to enhance perinatal outcomes.

Use of natural language processing method to identify regional anesthesia from clinical notes

INTRODUCTION

Accurate data capture is integral for research and quality improvement efforts. Unfortunately, limited guidance for defining and documenting regional anesthesia has resulted in wide variation in documentation practices, even within individual hospitals, which can lead to missing and inaccurate data. This cross-sectional study sought to evaluate the performance of a natural language processing (NLP)-based algorithm developed to identify regional anesthesia within unstructured clinical notes.

METHODS

We obtained postoperative clinical notes for all patients undergoing elective non-cardiac surgery with general anesthesia at one of six Veterans Health Administration hospitals in California between January 1, 2017, and December 31, 2022. After developing and executing our algorithm, we compared our results to a frequently used referent, the Corporate Data Warehouse structured data, to assess the completeness and accuracy of the currently available data. Measures of agreement included sensitivity, positive predictive value, false negative rate, and accuracy.

RESULTS

We identified 27,713 procedures, of which 9310 (33.6%) received regional anesthesia. 96.6% of all referent regional anesthesia cases were identified in the clinic notes with a very low false negative rate and good accuracy (false negative rate=0.8%, accuracy=82.5%). Surprisingly, the clinic notes documented more than two times the number of regional anesthesia cases that were documented in the referent (algorithm n=9154 vs referent n=4606).

DISCUSSION

While our algorithm identified nearly all regional anesthesia cases from the referent, it also identified more than two times as many regional anesthesia cases as the referent, raising concerns about the accuracy and completeness of regional anesthesia documentation in administrative and clinical databases. We found that NLP was a promising alternative for identifying clinical information when existing databases lack complete documentation.

Association between prenatal exposure to per- and polyfluoroalkyl substances and infant anthropometry: A prospective cohort study

BACKGROUND

Per- and polyfluoroalkyl substances (PFAS) are a group of synthetic organic chemicals with potential endocrine-disrupting effects, and have been found to impair the physical growth of offspring in both experimental and epidemiological studies. We aimed to investigate the effects of prenatal PFAS exposure on repeated measurements of multiple anthropometric indicators in infants.

METHOD

PFAS were measured in serum samples collected from pregnant women at 12-16 gestational weeks. We calculated z-scores for the weight-for-age (WAZ), weight-for-length (WLZ), head circumference-for-age (HCZ), arm circumference-for-age (ACZ), triceps skinfold-for-age (TSZ), and subscapular skinfold-for-age (SSZ) at birth, 6 months, and 12 months of age according to the child growth standards of the World Health Organization (WHO) for anthropometric indicators. A total of 964 mother-infant pairs were included. A multivariate linear regression was performed to examine the associations between prenatal PFAS concentrations and anthropometric indicators at each time point. A generalized estimating equation (GEE) model was used to examine the longitudinal effects of PFAS exposure on repeated measurements of anthropometric indicators. Ultimately, a Bayesian kernel machine regression (BKMR) model was used to assess the joint effects of the PFAS mixture on anthropometric indicators.

RESULTS

In GEE models, perfluorododecanoic acid (PFDoA) in the high tertile group was associated with increased WAZ/WLZ, with β values (95% confidence intervals (CI)) of 0.12 (0.00, 0.23) and 0.18 (0.03, 0.32), respectively. Perfluorononanoic acid (PFNA) was associated with increased ACZ in the middle and high tertile groups. The BKMR models also presented the associations of the PFAS mixture with increased WAZ/WLZ throughout infancy, with more profound effects in females. Meanwhile, a pattern of inverse associations was observed between the perfluorooctanoic acid (PFOA) concentrations in the high tertile group and decreased WAZ, WLZ, and HCZ in males. In addition, the associations between PFAS and increased TSZ/SSZ at birth were identified by both linear regression and BKMR models.

CONCLUSION

Prenatal PFAS exposure (PFNA and PFDoA) was associated with increased infant anthropometry, especially in female infants, while prenatal PFOA exposure was associated with decreased weight, and head and arm circumference in male infants. The findings indicate that prenatal PFAS exposure may impair the growth trajectory of offspring.

The impact of being overweight or obese on 12 month clinical recovery in patients following lumbar microdiscectomy for radiculopathy

BACKGROUND CONTEXT

The proportion of patients who undergo lumbar microdiscectomy due to lumbar radiculopathy who are also overweight or obese is high. However, whether high body mass index (BMI) affects clinical outcomes is not well-studied.

PURPOSE

To investigate the difference in the clinical course between normal weight, overweight, and obese patients with radiculopathy who underwent lumbar microdiscectomy followed by physical therapy and to evaluate whether high BMI is associated with poor recovery.

STUDY DESIGN/SETTING

A prospective cohort study with a 12-month follow-up was conducted in a multidisciplinary clinic.

PATIENT SAMPLE

We included 583 patients (median [IQR] age: 45 [35-52] years; 41% female) with clinical signs and symptoms of lumbar radiculopathy, consistent with magnetic resonance imaging findings, who underwent microdiscectomy followed by postoperative physical therapy.

OUTCOME MEASURES

Outcomes were leg pain and back pain intensity measured with a visual analogue scale, disability measured with the Roland Morris Disability Questionnaire at 3 and 12-month follow-ups, and complications.

METHODS

Patients were classified as being normal weight (46.9%), overweight (38.4%), or obese (14.7%). A linear mixed-effects model was used to assess the difference in the clinical course of pain and disability between the three BMI categories. The association between BMI and outcomes was evaluated using univariable and multivariable logistic regression analyses.

RESULTS

All three patient groups experienced a significant improvement in leg pain, back pain, and disability over 3 and 12-month follow-up. Patients who were overweight, obese, or normal weight experienced comparable leg pain (p=.14) and disability (p=.06) over the clinical course (p=.14); however, obese patients experienced higher back pain (MD=-6.81 [95%CI: -13.50 to -0.14]; p=.03). The difference in back pain scores was not clinically relevant.

CONCLUSIONS

In the first year following lumbar microdiscectomy, patients demonstrated clinical improvements and complications that were unrelated to their preoperative BMI.

IDENTIFICATION OF POTENTIALLY MODIFIABLE FACTORS TO IMPROVE RECOGNITION AND OUTCOME OF NECROTIZING SOFT-TISSUE INFECTIONS

ABSTRACT

Background : Necrotizing soft-tissue infections (NSTIs) present a surgical emergency of increasing incidence, which is often misdiagnosed and associated with substantial mortality and morbidity. A retrospective multicenter (11 hospitals) cohort study was initiated to identify the early predictors of misdiagnosis, mortality, and morbidity (skin defect size and amputation). Methods : Patients of all ages who presented with symptoms and were admitted for acute treatment of NSTIs between January 2013 and December 2017 were included. Generalized estimating equation analysis was used to identify early predictors (available before or during the first debridement surgery), with a significance level of P < 0.05. Results : The median age of the cohort (N = 216) was 59.5 (interquartile range = 23.6) years, of which 138 patients (63.9%) were male. Necrotizing soft-tissue infections most frequently originated in the legs (31.0%) and anogenital area (30.5%). More than half of the patients (n = 114, 54.3%) were initially misdiagnosed. Thirty-day mortality was 22.9%. Amputation of an extremity was performed in 26 patients (12.5%). Misdiagnosis was more likely in patients with a higher Charlson Comorbidity Index (β = 0.20, P = 0.001), and less likely when symptoms started in the anogenital area (β = -1.20, P = 0.003). Besides the established risk factors for mortality (septic shock and age), misdiagnosis was identified as an independent predictor of 30-day mortality (β = 1.03, P = 0.01). The strongest predictors of the final skin defect size were septic shock (β = 2.88, P < 0.001) and a skin-sparing approach to debridement (β = -1.79, P = 0.002). Conclusion : Recognition of the disease is essential for the survival of patients affected by NSTI, as is adequate treatment of septic shock. The application of a skin-sparing approach to surgical debridement may decrease morbidity.

Estimating Costs Associated with Disease Model States Using Generalized Linear Models: A Tutorial

Estimates of costs associated with disease states are required to inform decision analytic disease models to evaluate interventions that modify disease trajectory. Increasingly, decision analytic models are developed using patient-level data with a focus on heterogeneity between patients, and there is a demand for costs informing such models to reflect individual patient costs. Statistical models of health care costs need to recognize the specific features of costs data which typically include a large number of zero observations for non-users, and a skewed and heavy right-hand tailed distribution due to a small number of heavy healthcare users. Different methods are available for modelling costs, such as generalized linear models (GLMs), extended estimating equations and latent class approaches. While there are tutorials addressing approaches to decision modelling, there is no practical guidance on the cost estimation to inform such models. Therefore, this tutorial aims to provide a general guidance on estimating healthcare costs associated with disease states in decision analytic models. Specifically, we present a step-by-step guide to how individual participant data can be used to estimate costs over discrete periods for participants with particular characteristics, based on the GLM framework. We focus on the practical aspects of cost modelling from the conceptualization of the research question to the derivation of costs for an individual in particular disease states. We provide a practical example with step-by-step R code illustrating the process of modelling the hospital costs associated with disease states for a cardiovascular disease model.

How do sports injury epidemiological outcomes vary depending on athletes' response rates to a weekly online questionnaire? An analysis of 39-week follow-up from 391 athletics (track and field) athletes

OBJECTIVE

To explore how sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) vary depending on the response rates to a weekly online self-reported questionnaire for athletes.

METHODS

Weekly information on athletics injuries and exposure from 391 athletics (track and field) athletes was prospectively collected over 39 weeks (control group of the PREVATHLE randomized controlled trial) using an online self-reported questionnaire. The data were used to calculate sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) for sub-groups with different minimum individual athletes' response rates (i.e., from at least 100%, at least 97%, at least 95%, … to at least 0% response rate). We then calculated the relative variation between each sub-group and the sub-group with a 100% response rate as a reference. A substantial variation was considered when the relative variation was greater than one SD or 95% CI of the respective epidemiological outcome calculated in the sub-group with a 100% response rate.

RESULTS

Of 15 249 expected weekly questionnaires, 7209 were completed and returned, resulting in an overall response rate of 47.3%. The individual athletes' response rates ranged from 0% (n = 51) to 100% (n = 100). The prevalence, average weekly prevalence, and time to first injury only varied substantially for the sub-groups below a 5%, 10% and 18% minimum individual response rate, respectively. The incidence and injury burden showed substantial variations for all sub-groups with a response rate below 100%.

CONCLUSIONS

Epidemiological outcomes varied depending on the minimum individual athletes' response rate, with injury prevalence, average weekly prevalence, and time to first injury varying less than injury incidence and injury burden. This highlights the need to take into account the individual response rate when calculating epidemiological outcomes, and determining the optimal study-specific cut-offs of the minimum individual response rate needed.

Decoding emotions: Exploring the validity of sentiment analysis in psychotherapy

OBJECTIVE

Given the importance of emotions in psychotherapy, valid measures are essential for research and practice. As emotions are expressed at different levels, multimodal measurements are needed for a nuanced assessment. Natural Language Processing (NLP) could augment the measurement of emotions. The study explores the validity of sentiment analysis in psychotherapy transcripts.

METHOD

We used a transformer-based NLP algorithm to analyze sentiments in 85 transcripts from 35 patients. Construct and criterion validity were evaluated using self- and therapist reports and process and outcome measures via correlational, multitrait-multimethod, and multilevel analyses.

RESULTS

The results provide indications in support of the sentiments' validity. For example, sentiments were significantly related to self- and therapist reports of emotions in the same session. Sentiments correlated significantly with in-session processes (e.g., coping experiences), and an increase in positive sentiments throughout therapy predicted better outcomes after treatment termination.

DISCUSSION

Sentiment analysis could serve as a valid approach to assessing the emotional tone of psychotherapy sessions and may contribute to the multimodal measurement of emotions. Future research could combine sentiment analysis with automatic emotion recognition in facial expressions and vocal cues via the Nonverbal Behavior Analyzer (NOVA). Limitations (e.g., exploratory study with numerous tests) and opportunities are discussed.

Comparison of the effects of imputation methods for missing data in predictive modelling of cohort study datasets

BACKGROUND

Missing data is frequently an inevitable issue in cohort studies and it can adversely affect the study's findings. We assess the effectiveness of eight frequently utilized statistical and machine learning (ML) imputation methods for dealing with missing data in predictive modelling of cohort study datasets. This evaluation is based on real data and predictive models for cardiovascular disease (CVD) risk.

METHODS

The data is from a real-world cohort study in Xinjiang, China. It includes personal information, physical examination data, questionnaires, and laboratory biochemical results from 10,164 subjects with a total of 37 variables. Simple imputation (Simple), regression imputation (Regression), expectation-maximization(EM), multiple imputation (MICE) , K nearest neighbor classification (KNN), clustering imputation (Cluster), random forest (RF), and decision tree (Cart) were the chosen imputation methods. Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) are utilised to assess the performance of different methods for missing data imputation at a missing rate of 20%. The datasets processed with different missing data imputation methods were employed to construct a CVD risk prediction model utilizing the support vector machine (SVM). The predictive performance was then compared using the area under the curve (AUC).

RESULTS

The most effective imputation results were attained by KNN (MAE: 0.2032, RMSE: 0.7438, AUC: 0.730, CI: 0.719-0.741) and RF (MAE: 0.3944, RMSE: 1.4866, AUC: 0.777, CI: 0.769-0.785). The subsequent best performances were achieved by EM, Cart, and MICE, while Simple, Regression, and Cluster attained the worst performances. The CVD risk prediction model was constructed using the complete data (AUC:0.804, CI:0.796-0.812) in comparison with all other models with p<0.05.

CONCLUSION

KNN and RF exhibit superior performance and are more adept at imputing missing data in predictive modelling of cohort study datasets.

Hippocampal Structures Among Japanese Adolescents Before and After the COVID-19 Pandemic

Importance

Few studies have used a large-sample, longitudinal, population-based cohort study to examine whether the COVID-19 pandemic as a global major life event is associated with structural plasticity of the adolescent hippocampus.

Objective

To examine whether Japan's first state of emergency (SoE) during the COVID-19 pandemic was associated with alterations in the macrostructures and microstructures of the hippocampus during its development.

Design, Setting, and Participants

The population-neuroscience Tokyo TEEN Cohort study is a prospective cohort study with 4 consecutive waves in Tokyo, Japan. Due to the SoE, data collection was suspended between March 27, 2020, and July 30, 2020. Analyzed data, comprising 1149 brain structural scans obtained from 479 participants, of whom 336 participants had undergone 2 or more scans, were collected between October 2013 and November 2021. Data were analyzed from August 2022 to December 2023.

Exposures

Japan's first SoE (April 7 to May 25, 2020).

Main Outcomes and Measures

Hippocampal volume, 12 hippocampal subfield volumes, and 7 microstructural measures of the hippocampus.

Results

A total of 1060 brain scans from 459 participants (214 female participants [47%]) including 246 participants from wave 1 (median [IQR] age, 11.3 [11.1-11.7] years), 358 from wave 2 (median [IQR] age, 13.8 [13.3-14.5] years), 304 from wave 3 (median [IQR] age, 15.9 [15.4-16.5] years), and 152 from wave 4 (median [IQR] age, 17.9 [17.5-18.4] years) were included in the final main analysis. The generalized additive mixed model showed a significant associations of the SoE with the mean hippocampal volume (β = 102.19; 95% CI, 0.61-203.77; P = .049). The generalized linear mixed models showed the main associations of the SoE with hippocampal subfield volume (granule cell and molecular layer of the dentate gyrus: β = 18.19; 95% CI, 2.97-33.41; uncorrected P = .02; CA4: β = 12.75; 95% CI, 0.38-25.12; uncorrected P = .04; hippocampus-amygdala transition area: β = 5.67; 95% CI, 1.18-10.17; uncorrected P = .01), and fractional anisotropy (β = 0.03; 95% CI, 0.00-0.06; uncorrected P = .04).

Conclusions and Relevance

After the first SoE, a volumetric increase in the hippocampus and trend increase in 3 subfield volumes and microstructural integration of the hippocampus were observed, suggesting that the transient plasticity of the adolescent hippocampus was affected by a major life event along with the typical developmental trajectory.

Specific and shared mechanisms associated with treatment for chronic neck pain: study protocol for the SS-MECH trial

BACKGROUND

Treatment mechanisms involve the steps or processes through which an intervention unfolds and produces change in an outcome variable. Treatment mechanisms can be specific to the intervention provided (i.e. pain modulation) or shared with other treatments (i.e. reduced fear of movement). Whether specific and shared treatment mechanisms are different across interventions and whether they lead to the outcomes seen in trials is largely unknown. The management of individuals with chronic neck pain routinely include manual therapy (MT) and resistance exercise (RE), as both approaches are included in clinical practice guidelines and both yield similar outcomes.

OBJECTIVES

Our study plans to answer two research questions: 1) what are the specific mechanisms associated with MT versus interventions (and are these different), and 2) what are the shared mechanisms associated with these interventions, and do specific or shared mechanisms mediate clinical outcomes?

METHODS

This study will involve a 2-group parallel (1:1) single-blinded randomized trial to compare the specific and potential shared treatment mechanisms between these two approaches. We will enroll individuals with a history of chronic neck pain and evaluate whether specific or shared mechanisms mediate clinical outcomes.

RESULTS

We hypothesize that MT and RE approaches will both exhibit different specific treatment mechanisms, and that both approaches will exhibit shared treatment mechanisms, which will notably influence outcomes at both discharge and 6-months.

CONCLUSIONS

This study is important because it will help identify what specific or shared treatment mechanisms are associated with different interventions and, how different treatment mechanisms influence clinical outcomes.

EvoImp: Multiple Imputation of Multi-label Classification data with a genetic algorithm

Missing data is a prevalent problem that requires attention, as most data analysis techniques are unable to handle it. This is particularly critical in Multi-Label Classification (MLC), where only a few studies have investigated missing data in this application domain. MLC differs from Single-Label Classification (SLC) by allowing an instance to be associated with multiple classes. Movie classification is a didactic example since it can be "drama" and "bibliography" simultaneously. One of the most usual missing data treatment methods is data imputation, which seeks plausible values to fill in the missing ones. In this scenario, we propose a novel imputation method based on a multi-objective genetic algorithm for optimizing multiple data imputations called Multiple Imputation of Multi-label Classification data with a genetic algorithm, or simply EvoImp. We applied the proposed method in multi-label learning and evaluated its performance using six synthetic databases, considering various missing values distribution scenarios. The method was compared with other state-of-the-art imputation strategies, such as K-Means Imputation (KMI) and weighted K-Nearest Neighbors Imputation (WKNNI). The results proved that the proposed method outperformed the baseline in all the scenarios by achieving the best evaluation measures considering the Exact Match, Accuracy, and Hamming Loss. The superior results were constant in different dataset domains and sizes, demonstrating the EvoImp robustness. Thus, EvoImp represents a feasible solution to missing data treatment for multi-label learning.

Exploring Reasons for Non-Engagement From a Peer-Led Diversionary Intervention for Veterans in Police Custody

UK veterans with complex needs arrested in police custody can access support through pre-charge diversion into treatment and ancillary services. We consider why veterans in police custody disengaged from a peer-led criminal justice diversionary support service in one UK region that adopted a continuous case management approach. Seven hundred and fifty-seven veterans were assessed to have high levels of comorbid health needs and socio-economic harms, with one-quarter (26.7%, n = 202) subsequently disengaging from the service. A logistic regression model using Multivariate Imputation by Chained Equations identified that veterans of a younger age, no-fixed-abode, a history of incarceration, and those from a Royal Navy background were likelier to disengage from the intervention. We conclude that this peer-based diversionary model has some efficacy in maintaining the engagement of a highly complex, comorbid segment of criminally-justice-exposed UK military veterans. The perceived benefits of an integrated peer-based model predicated on continuous case-management techniques are discussed.

Deep learning based decision tree ensembles for incomplete medical datasets

BACKGROUND

In practice, the collected datasets for data analysis are usually incomplete as some data contain missing attribute values. Many related works focus on constructing specific models to produce estimations to replace the missing values, to make the original incomplete datasets become complete. Another type of solution is to directly handle the incomplete datasets without missing value imputation, with decision trees being the major technique for this purpose.

OBJECTIVE

To introduce a novel approach, namely Deep Learning-based Decision Tree Ensembles (DLDTE), which borrows the bounding box and sliding window strategies used in deep learning techniques to divide an incomplete dataset into a number of subsets and learning from each subset by a decision tree, resulting in decision tree ensembles.

METHOD

Two medical domain problem datasets contain several hundred feature dimensions with the missing rates of 10% to 50% are used for performance comparison.

RESULTS

The proposed DLDTE provides the highest rate of classification accuracy when compared with the baseline decision tree method, as well as two missing value imputation methods (mean and k-nearest neighbor), and the case deletion method.

CONCLUSION

The results demonstrate the effectiveness of DLDTE for handling incomplete medical datasets with different missing rates.

Furosemide versus placebo for fluid overload in intensive care patients-The randomised GODIF trial second version: Statistical analysis plan

BACKGROUND

Fluid overload is associated with increased mortality in intensive care unit (ICU) patients. The GODIF trial aims to assess the benefits and harms of fluid removal with furosemide versus placebo in stable adult patients with moderate to severe fluid overload in the ICU. This article describes the detailed statistical analysis plan for the primary results of the second version of the GODIF trial.

METHODS

The GODIF trial is an international, multi-centre, randomised, stratified, blinded, parallel-group, pragmatic clinical trial, allocating 1000 adult ICU patients with moderate to severe fluid overload 1:1 to furosemide versus placebo. The primary outcome is days alive and out of hospital within 90 days post-randomisation. With a power of 90% and an alpha level of 5%, we may reject or detect an improvement of 8%. The primary analyses of all outcomes will be performed in the intention-to-treat population. For the primary outcome, the Kryger Jensen and Lange method will be used to compare the two treatment groups adjusted for stratification variables supplemented with sensitivity analyses in the per-protocol population and with further adjustments for prognostic variables. Secondary outcomes will be analysed with multiple linear regressions, logistic regressions or the Kryger Jensen and Lange method as suitable with adjustment for stratification variables.

CONCLUSION

The GODIF trial data will increase the certainty about the effects of fluid removal using furosemide in adult ICU patients with fluid overload.

TRIAL REGISTRATIONS

EudraCT identifier: 2019-004292-40 and ClinicalTrials.org: NCT04180397.

Statistical Methods for Pre-Post Intervention Design

The author provides an overview of options for statistical tests in pre-post analysis.

Effectiveness of Cognitive Functional Therapy Versus Core Exercises and Manual Therapy in Patients With Chronic Low Back Pain After Spinal Surgery: Randomized Controlled Trial

OBJECTIVE

Our aim was to investigate whether cognitive functional therapy (CFT) was more effective than core exercises and manual therapy (CORE-MT) in improving pain and function for patients with chronic low back pain after spinal surgery.

METHODS

This study was a randomized controlled superiority trial in a university hospital and a private physical therapist clinic in Santa Catarina, Brazil. Eighty participants who were 18 to 75 years old and had chronic low back pain after spinal surgery received 4 to 12 treatment sessions of CFT or CORE-MT once per week for a maximum period of 12 weeks. Primary outcomes were pain intensity (numeric pain rating scale, scored from 0 to 10) and function (Patient-Specific Functional Scale, scored from 0 to 10) after intervention.

RESULTS

We obtained primary outcome data for 75 participants (93.7%). CFT was more effective, with a large effect size, than CORE-MT in reducing pain intensity (mean difference [MD] = 2.42; 95% CI = 1.69-3.14; effect size [d] = 0.85) and improving function (MD = -2.47; 95% CI = -3.08 to -1.87; effect size = 0.95) after intervention (mean = 10.4 weeks [standard deviation = 2.17] after the beginning of treatment). The differences were maintained at 22 weeks for pain intensity (MD = 1.64; 95% CI = 0.98-2.3; effect size = 0.68) and function (MD = -2.01; 95% CI = -2.6 to -1.41; effect size = 0.81).

CONCLUSION

CFT was more effective than CORE-MT, with large effect sizes, and may be an option for patients with chronic low back pain after spinal surgery.

IMPACT

CFT reduces pain and improves function, with large effect sizes, compared with CORE-MT. The difference between CFT and CORE-MT was sustained at the midterm follow-up. Treatment with CFT may be an option for patients with chronic low back pain after spinal surgery.

The Joint Awareness Score: A Shortened, Simplified, Improved Alternative to the Forgotten Joint Score

Background

The Forgotten Joint Score (FJS) is a 12-question patient-reported outcomes measure created to measure a patient's awareness of their artificial joint. The FJS has attained wide usage, though it is not without weaknesses. Our patients report that the semantics of the English translation are flawed and that the 5 answer options for each question are poorly differentiated. Additionally, the FJS will result in no score if 3 or more questions are unanswered. This prompted the development of an alternative patient-reported outcomes measure, the Joint Awareness Score (JAS), that builds upon the core concept of joint awareness underlying the FJS, but that is easier to understand and shorter to complete. We completed an exploratory, pilot study to evaluate this outcomes instrument. Our hypothesis is that the JAS will correlate strongly with the FJS and could be used as a substitute.

Methods

Knee arthroplasty patients in a prospective registry were administered the FJS and the JAS. Internal consistency and correlation were calculated with Cronbach's alpha and Pearson's correlation coefficient, respectively.

Results

This study included 174 patients. Cronbach's alpha for FJS was 0.97 for 6 months and 0.97 for 12 months, whereas JAS was 0.89 at 6 months and 0.85 at 12 months. Pearson correlation comparing FJS and JAS at 6 months was 0.88 (95% confidence interval: 0.83, 0.92) and 0.86 (95% confidence interval: 0.78, 0.92) at 12 months.

Conclusions

The Joint Awareness Score is a new patient-reported outcomes measure that is a substitute for the FJS, with half the number of questions, improved semantics, and simplified answers.

External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact

BACKGROUND

Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value of a previously described phenotyping system (FEN-COVID-19) and to assess the reproducibility of phenotypes development as a secondary analysis.

METHODS

Patients were classified in phenotypes A, B or C according to the severity of oxygenation impairment, inflammatory response, hemodynamic and laboratory tests according to the FEN-COVID-19 method.

RESULTS

Overall, 992 patients were included in the study, and 181 (18%), 757 (76%) and 54 (6%) of them were assigned to the FEN-COVID-19 phenotypes A, B, and C, respectively. An association with mortality was observed for phenotype C vs. A (hazard ratio [HR] 3.10, 95% confidence interval [CI] 1.81-5.30, p < 0.001) and for phenotype C vs. B (HR 2.20, 95% CI 1.50-3.23, p < 0.001). A non-statistically significant trend towards higher mortality was also observed for phenotype B vs. A (HR 1.41; 95% CI 0.92-2.15, p = 0.115). By means of cluster analysis, three different phenotypes were also identified in our cohort, with an overall similar gradient in terms of prognostic impact to that observed when patients were assigned to FEN-COVID-19 phenotypes.

CONCLUSIONS

The prognostic impact of FEN-COVID-19 phenotypes was confirmed in our external cohort, although with less difference in mortality between phenotypes A and B than in the original study.

Incidence of Intraoperative Vasoplegic Syndrome in Lung Transplantation

OBJECTIVES

Severe hypotension and low systemic vascular resistance in the setting of adequate cardiac output, known as "vasoplegic syndrome" (VS), is a physiologic disturbance reported in 9% to 44% of cardiac surgery patients. Although this phenomenon is well-documented in cardiac surgery, there are few studies on its occurrence in lung transplantation. The goal of this study was to characterize the incidence of VS in lung transplantation, as well as identify associated risk factors and outcomes.

DESIGN

Retrospective study of single and bilateral lung transplants from April 2013 to September 2021.

SETTING

The study was conducted at an academic hospital.

PARTICIPANTS

Patients ≥18 years of age who underwent lung transplantation.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The authors defined VS as mean arterial pressure <65 mmHg, cardiac index ≥2.2 L/min/m2, and ≥30 minutes of vasopressor administration after organ reperfusion. The association between VS and risk factors or outcomes was assessed using t tests, Mann-Whitney U, and chi-square tests. The authors ran multivariate logistic regression models to determine factors independently associated with VS. The incidence of VS was 13.9% (CI 10.4%-18.4%). In the multivariate model, male sex (odds ratio 2.85, CI 1.07-7.58, p = 0.04) and cystic fibrosis (odds ratio 5.76, CI 1.43-23.09, p = 0.01) were associated with VS.

CONCLUSIONS

The incidence of VS in lung transplantation is comparable to that of cardiac surgery. Interestingly, male sex and cystic fibrosis are strong risk factors. Identifying lung transplant recipients at increased risk of VS may be crucial to anticipating intraoperative complications.

Post-Implantation Syndrome Incidence is Higher After Complex Endovascular Aortic Procedures Than After Standard Infrarenal Repair

OBJECTIVE

Post-implantation syndrome (PIS), characterised by malaise, fever, and increased inflammatory markers, is a common occurrence after endovascular aneurysm repair (EVAR), causing prolonged hospitalisation and increased cost. This study aimed to determine the incidence and short-term outcomes of PIS after fenestrated or branched procedures in aorto-iliac aneurysms compared with standard EVAR.

METHODS

A retrospective, comparative study from a tertiary academic institution was undertaken. All patients who underwent elective EVAR with polyester stent grafts from January 2015 to June 2021 were considered. Two groups were defined: standard EVAR (sEVAR) and complex EVAR (cEVAR). The latter included visceral fenestrated and branched or iliac branch and chimney stent grafts. The primary outcome was the incidence of PIS within three days of the index procedure. Secondary outcomes were short-term complications and risk factors for PIS. A multivariable model was constructed to correct for confounders.

RESULTS

Overall, 253 patients were included: 165 (65.2%) sEVAR and 88 (34.8%) cEVAR. Complex EVAR patients were younger, with larger aneurysms, had longer procedures, and were more likely to have intra-operative complications. The PIS incidence was 23.7% (n = 60), significantly higher in cEVAR (34.1% vs. 18.2%; p = .005) and increased with the complexity of the procedure (EVAR: 18.2% vs. EVAR + iliac branch device: 25.0% vs. fenestrated and branched EVAR: 36.2%; p = .030). On multivariable analysis, cEVAR (OR 2.833, 95% CI 1.295 - 6.198; p = .009) was associated with a significantly increased risk of PIS. No differences in short term outcomes according to PIS status were noted. Group sub-analysis for cEVAR patients did not reveal any statistically significantly different outcomes according to PIS occurrence.

CONCLUSION

In this cohort, cEVAR procedures were associated with a significantly increased risk of developing PIS compared with standard infrarenal repair. Post-implantation syndrome also appears to have a benign course with no major impact on peri-operative outcomes after cEVAR. Further research to confirm these findings is required.

Early diagnosis of candidemia with explainable machine learning on automatically extracted laboratory and microbiological data: results of the AUTO-CAND project

BACKGROUND

Candidemia is associated with a heavy burden of morbidity and mortality in hospitalized patients. The availability of blood culture results could require up to 48-72 h after blood draw; thus, early treatment decisions are made in the absence of a definite diagnosis.

METHODS

In this retrospective study, we assessed the performance of different supervised machine learning algorithms for the early differential diagnosis of candidemia and bacteremia in adult patients on a large dataset automatically extracted within the AUTO-CAND project.

RESULTS

Overall, 12,483 episodes of candidemia (1275; 10%) or bacteremia (11,208; 90%) were included in the analysis. A random forest classifier achieved the best diagnostic performance for candidemia, with sensitivity 0.98 and specificity 0.65 on the training set (true skill statistic [TSS] = 0.63) and sensitivity 0.74 and specificity 0.57 on the test set (TSS = 0.31). Then, the random classifier was trained in the subgroup of patients with available serum β-D-glucan (BDG) and procalcitonin (PCT) values by exploiting the feature ranking learned in the entire dataset. Although no statistically significant differences were observed from the performance measures obtained by employing BDG and PCT alone, the performance measures of the classifier that included the features selected in the entire dataset, plus BDG and PCT, were the highest in most cases.

CONCLUSIONS

Random forest classifiers trained on large datasets of automatically extracted data have the potential to improve current diagnostic algorithms for candidemia. However, further development through implementation of automatically extracted clinical features may be necessary to achieve crucial improvements.

Laparoscopic rectal cancer resection yields comparable clinical and oncological results with shorter hospital stay compared to open access: a 5-year national cohort

PURPOSE

Although widely applied, the results following laparoscopic rectal resection (LRR) compared to open rectal resection (ORR) are still debated. The aim of this study was to assess clinical short- and long-term results as well as oncological resection quality following LRR or ORR for cancer in a 5-year national cohort.

METHODS

Data from the Norwegian Registry for Gastrointestinal Surgery and the Norwegian Colorectal Cancer Registry were retrieved from January 2014 to December 2018 for patients who underwent elective resection for rectal cancer. Primary end point was 5-year overall survival. Secondary end points were local recurrence rates within 5 years, oncological resection quality, and short-term outcome measures.

RESULTS

A total of 1796 patients were included, of whom 1284 had undergone LRR and 512 ORR. There was no difference in 5-year survival rates between the groups after adjusting for relevant covariates with Cox regression analyses. Crude 5-year survival was 77.1% following LRR compared to 74.8% following ORR (p = 0.015). The 5-year local recurrence rates were 3.1% following LRR and 4.1% following ORR (p = 0.249). Length of hospital stay was median 8.0 days (quartiles 7.0-13.0) after ORR compared to 6.0 (quartiles 4.0-8.0) days after LRR. After adjusting for relevant covariates, estimated additional length of stay after ORR was 3.1 days (p < 0.001, 95% CI 2.3-3.9). Rates of positive resection margins and number of harvested lymph nodes were similar. There were no other significant differences in short-term outcomes between the groups.

CONCLUSION

LRR was performed with clinical and oncological outcomes similar to ORR, but with shorter hospital stay.

Digital phenotyping: An equal opportunity approach to reducing disparities in Alzheimer's disease and related dementia research

A rapidly aging world population is fueling a concomitant increase in Alzheimer's disease (AD) and related dementias (ADRD). Scientific inquiry, however, has largely focused on White populations in Australia, the European Union, and North America. As such, there is an incomplete understanding of AD in other populations. In this perspective, we describe research efforts and challenges of cohort studies from three regions of the world: Central America, East Africa, and East Asia. These cohorts are engaging with the Davos Alzheimer's Collaborative (DAC), a global partnership that brings together cohorts from around the world to advance understanding of AD. Each cohort is poised to leverage the widespread use of mobile devices to integrate digital phenotyping into current methodologies and mitigate the lack of representativeness in AD research of racial and ethnic minorities across the globe. In addition to methods that these three cohorts are already using, DAC has developed a digital phenotyping protocol that can collect ADRD-related data remotely via smartphone and/or in clinic via a tablet to generate a common data elements digital dataset that can be harmonized with additional clinical and molecular data being collected at each cohort site and when combined across cohorts and made accessible can provide a global data resource that is more racially/ethnically represented of the world population.

Clinical outcomes of medication abortion using misoprostol-only: A retrospective chart review at an abortion provider organization in the United States

OBJECTIVES

This study aimed to evaluate the effectiveness and safety of medication abortion with misoprostol-only among patients treated by an abortion provider organization in the United States during the COVID-19 pandemic.

STUDY DESIGN

We abstracted data from patients receiving misoprostol-only for abortion from December 2020 to December 2021. Two regimens were used, both allowing three to four doses of misoprostol 800 mcg every 3 hours but differing in the recommended administration routes (vaginal, buccal, or sublingual). We estimated the proportions of patients who had complete abortion and ongoing pregnancy in the two regimen groups in complete case analyses and after imputing missing outcomes based on pretreatment characteristics. We also estimated maximum effectiveness, assuming that all patients without known treatment failures had complete abortions. We tabulated serious adverse events.

RESULTS

We ascertained abortion outcomes for 476 (52%) of the total 911 treated patients. Of the 476 patients, 389 (82%) had complete abortion confirmed by test or history, and 45 (9%) had ongoing pregnancies detected after the provision of treatment. These proportions did not differ significantly between the two regimen groups in adjusted complete case analyses (p > 0.44). The results of imputed analyses were similar. Of the total 911 patients, at most 90% (95% confidence interval 88%, 92%) had complete abortion, and at least 5% (95% confidence interval 4%, 7%) had ongoing pregnancy. Serious adverse events were reported in three patients (0.6% of 487 patients with data for this outcome).

CONCLUSIONS

Our analysis suggests that the misoprostol-only regimens studied were safe and effective for most patients. Due to high loss to follow-up, observations from patients contacted after treatment likely somewhat underestimate true effectiveness.

IMPLICATIONS

Medication abortion with misoprostol-only was safe and produced complete abortion in most patients with follow-up. If loss to follow-up is high, effectiveness observed by clinics may misestimate true treatment efficacy.

Investigating the factor structure and measurement invariance of the eating disorder examination questionnaire (EDE-Q) among cisgender gay men and lesbian women from the United States

BACKGROUND

Although the Eating Disorder Examination-Questionnaire (EDE-Q) is one of the most widely used self-report assessments of eating disorder symptoms, evidence indicates potential limitations with its original factor structure and associated psychometric properties in a variety of populations, including sexual minority populations. The aims of the current investigation were to explore several previously published EDE-Q factor structures and to examine internal consistency and measurement invariance of the best-fitting EDE-Q model in a large community sample of cisgender gay men and cisgender lesbian women.

METHODS

Data were drawn from 1624 adults (1060 cisgender gay men, 564 cisgender lesbian women) who participated in The PRIDE Study, a large-scale longitudinal cohort study of sexual and gender minorities from the United States. A series of confirmatory factor analyses (CFAs) were conducted to explore the fit of eight proposed EDE-Q models; internal consistency (Cronbach's alphas, Omega coefficients) and measurement invariance (multi-group CFA) were subsequently evaluated.

RESULTS

A brief seven-item, three-factor (dietary restraint, shape/weight overvaluation, body dissatisfaction) model of the EDE-Q from Grilo et al. (Obes Surg. 23:657-662, 2013), consistently evidenced the best fit across cisgender gay men and lesbian women. The internal consistencies of the three subscales were adequate in both groups, and measurement invariance across the groups was supported.

CONCLUSIONS

Taken together, these findings support the use of the seven-item, three-factor version of the EDE-Q for assessing eating disorder symptomatology in cisgender gay men and lesbian women. Future studies can confirm the current findings in focused examinations of the seven-item, three-factor EDE-Q in diverse sexual minority samples across race, ethnicity, socioeconomic status, and age ranges.

Investigating the factor structure and measurement invariance of the Eating Disorder Examination-Questionnaire (EDE-Q) in a community sample of gender minority adults from the United States

OBJECTIVE

The Eating Disorder Examination-Questionnaire (EDE-Q) is one of the most widely used self-report assessments of eating disorder symptoms. However, evidence indicates potential problems with its original factor structure and associated psychometric properties in a variety of populations, including gender minority populations. The aim of the current investigation was to explore several previously published EDE-Q factor structures and to examine internal consistency and measurement invariance of the best-fitting EDE-Q model in a large community sample of gender minority adults.

METHODS

Data were drawn from 1567 adults (337 transgender men, 180 transgender women, and 1050 gender-expansive individuals) who participated in The PRIDE Study, a large-scale longitudinal cohort study of sexual and gender minorities from the United States. A series of confirmatory factor analyses (CFAs) were conducted to explore the fit of eight proposed EDE-Q models; internal consistency (Cronbach's alphas, Omega coefficients) and measurement invariance (multi-group CFA) were subsequently evaluated.

RESULTS

A brief seven-item, three-factor (dietary restraint, shape/weight overvaluation, body dissatisfaction) model of the EDE-Q consistently evidenced the best fit across gender minority groups (transgender men, transgender women, gender-expansive individuals). The internal consistencies of the three subscales were adequate in all groups, and measurement invariance across the groups was supported.

DISCUSSION

Taken together, these findings support the use of the seven-item, three-factor version of the EDE-Q for assessing eating disorder symptomatology in gender minority populations. Future studies can confirm the current findings in focused examinations of the seven-item, three-factor EDE-Q in diverse gender minority samples across race, ethnicity, socioeconomic status, and age ranges.

PUBLIC SIGNIFICANCE STATEMENT

Although transgender individuals have greater risk of developing an eating disorder, the factor structure of the Eating Disorder Examination-Questionnaire, one of the most widely used eating disorder assessment measures, has not been explored in transgender adults. We found that a seven-item model including three factors of dietary restraint, shape and weight overvaluation, and body dissatisfaction had the best fit among transgender and nonbinary adults.

Analysis of News Media-Reported Snakebite Envenoming in Nepal during 2010-2022

BACKGROUND

Snakebite envenoming is a well-known medical emergency in the Terai of Nepal in particular. However, there is an epidemiological knowledge gap. The news media data available online provide substantial information on envenomings. Assessing this information can be a pristine approach for understanding snakebite epidemiology and conducting knowledge-based interventions. We firstly analyzed news media-reported quantitative information on conditions under which bites occur, treatment-seeking behavior of victims, and outcomes of snakebite envenomings in Nepal.

METHODOLOGY/PRINCIPAL FINDINGS

We analyzed 308 Nepalese snakebite envenomed cases reported in 199 news media articles published between 2010 and 2022 using descriptive statistics, Wilcoxon, and Chi-square tests to know why and how victims were bitten, their treatment-seeking behavior, and the outcomes. These envenomated cases known with substantial information represented 48 districts (mostly located in the Terai region) of Nepal. These envenomings mostly occurred in residential areas affecting children. Generally, envenomings among males and females were not significantly different. But, in residential areas, females were more envenomed than males. Further, victims' extremities were often exposed to venomous snakebites while their active status and these episodes often occurred at night while victims were passive during snakebites indoors and immediate surroundings of houses. Snakebite deaths were less among referred than non-referred cases, males than females, and while active than passive conditions of victims.

CONCLUSION/SIGNIFICANCE

The most of reported envenomed patients were children, and most envenomings were due to cobra bites. Consultation with traditional healers complicated snakebite management. In most cases, deaths that occur without medical interventions are a severe snakebite consequence in Nepal. Further, several deaths in urban areas and mountains and higher hills of Nepal suggest immediate need of snakebite management interventions in the most affected districts. Therefore, there is an urgent need to immediately admit Nepalese snakebite victims to nearby snakebite treatment centers without adopting non-recommended prehospital interventions. The strategies for preventing snakebite and controlling venom effects should also include hilly and mountain districts where snakebite-associated deaths are reported.

Development of a Prediction Model for Cranioplasty Implant Survival Following Craniectomy

BACKGROUND

Cranioplasty after craniectomy can result in high rates of postoperative complications. Although determinants of postoperative outcomes have been identified, a prediction model for predicting cranioplasty implant survival does not exist. Thus, we sought to develop a prediction model for cranioplasty implant survival after craniectomy.

METHODS

We performed a retrospective cohort study of patients who underwent cranioplasty following craniectomy between 2014 and 2020. Missing data were imputed using multiple imputation. For model development, multivariable Cox proportional hazards regression analysis was performed. To test whether candidate determinants contributed to the model, we performed backward selection using the Akaike information criterion. We corrected for overfitting using bootstrapping techniques. The performance of the model was assessed using discrimination and calibration.

RESULTS

A total of 182 patients were included (mean age, 43.0 ± 19.7 years). Independent determinants of cranioplasty implant survival included the indication for craniectomy (compared with trauma-vascular disease: hazard ratio [HR], 0.65 [95% confidence interval (CI), 0.36-1.17]; infection: HR, 0.76 [95% CI, 0.32-1.80]; tumor: HR, 1.40 [95% CI, 0.29-6.79]), cranial defect size (HR, 1.01 per cm2 [95% CI, 0.73-1.38]), use of an autologous bone flap (HR, 1.63 [95% CI, 0.82-3.24]), and skin closure using staples (HR, 1.42 [95% CI, 0.79-2.56]). The concordance index of the model was 0.60 (95% CI, 0.47-0.73).

CONCLUSIONS

We have developed the first prediction model for cranioplasty implant survival after craniectomy. The findings from our study require external validation and deserve further exploration in future studies.

Physical activity and physical fitness in children with heritable connective tissue disorders

Objectives

Health problems in patients with heritable connective tissue disorders (HCTD) are diverse and complex and might lead to lower physical activity (PA) and physical fitness (PF). This study aimed to investigate the PA and PF of children with heritable connective tissue disorders (HCTD).

Methods

PA was assessed using an accelerometer-based activity monitor (ActivPAL) and the mobility subscale of the Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT). PF was measured in terms of cardiovascular endurance using the Fitkids Treadmill Test (FTT); maximal hand grip strength, using hand grip dynamometry (HGD) as an indicator of muscle strength; and motor proficiency, using the Bruininks-Oseretsky Test of Motor Proficiency-2 (BOTMP-2).

Results

A total of 56 children, with a median age of 11.6 (interquartile range [IQR], 8.8-15.8) years, diagnosed with Marfan syndrome (MFS), n = 37, Loeys-Dietz syndrome (LDS), n = 6, and genetically confirmed Ehlers-Danlos (EDS) syndromes, n = 13 (including classical EDS n = 10, vascular EDS n = 1, dermatosparaxis EDS n = 1, arthrochalasia EDS n = 1), participated. Regarding PA, children with HCTD were active for 4.5 (IQR 3.5-5.2) hours/day, spent 9.2 (IQR 7.6-10.4) hours/day sedentary, slept 11.2 (IQR 9.5-11.5) hours/day, and performed 8,351.7 (IQR 6,456.9-1,0484.6) steps/day. They scored below average (mean (standard deviation [SD]) z-score -1.4 (1.6)) on the PEDI-CAT mobility subscale. Regarding PF, children with HCTD scored well below average on the FFT (mean (SD) z-score -3.3 (3.2)) and below average on the HGD (mean (SD) z-score -1.1 (1.2)) compared to normative data. Contradictory, the BOTMP-2 score was classified as average (mean (SD) z-score.02 (.98)). Moderate positive correlations were found between PA and PF (r(39) = .378, p < .001). Moderately sized negative correlations were found between pain intensity and fatigue and time spent actively (r(35) = .408, p < .001 and r(24) = .395 p < .001, respectively).

Conclusion

This study is the first to demonstrate reduced PA and PF in children with HCTD. PF was moderately positively correlated with PA and negatively correlated with pain intensity and fatigue. Reduced cardiovascular endurance, muscle strength, and deconditioning, combined with disorder-specific cardiovascular and musculoskeletal features, are hypothesized to be causal. Identifying the limitations in PA and PF provides a starting point for tailor-made interventions.