Correlates of ART attrition among adults under antiretroviral therapy in Southern Ethiopia, retrospective cohort study.

High attrition rates from ART are the primary contributors to morbidity, death, hospitalisation, rising transmission rates, treatment failure, rising burden of opportunistic infections (OIs), and the evolution of HIV-virus resistance (HIVDR). In Sub-Saharan Africa, more than two-thirds of ART patients will not receive continuous care. There is little information about the correlates that contribute to attrition from ART services among ART patients in Southern Ethiopia. Hence, this study aims to identify correlates of attrition from antiretroviral therapy services for adults under antiretroviral therapy at Otona Teaching and Referral Hospital, Wolaita Zone, Southern Ethiopia. From 1 January 2013 to 31 December 2017, a retrospective cohort analysis was performed. The pre-determined 328 medical records were chosen using a simple random sampling technique using computer-generated random numbers. Epi Info version 3.5.3 was used to enter and clean the data, which were then exported to STATA version 11 for analysis. The Cox proportional hazards model, both bivariate and multivariable, was used. Variables with p-values less than 0.25 in bivariate analysis were considered candidates for multivariable analysis, and variables with p-values less than 0.05 were deemed statistically important in multivariable analysis. The intensity of the correlation and statistical significance were determined using the CHR, AHR, and 95 per cent confidence intervals. The magnitude of attrition from ART service was 21.60% (95% CI: 17.10, 26.10). The distance between home and hospital is more than five kilometres (AHR:3.84;95% CI: 1.99,7.38), no registered phone number (AHR:2.47;95%CI:1.32,4.09), have not taken isoniazid prophylaxis (AHR:2.23;95%CI:1.30,4.09), alcohol consumption (AHR: 1.77; 95% CI:1.01, 3.12), and had no caregiver (AHR: 2.11; 95% CI:1.23, 3.60) were statistically significant in the Cox proportional hazard model. Distance between home and hospital, phone number registration on follow-up chart, having a history of alcohol consumption, isoniazid prophylaxis provision, and having family support were independent correlates of attrition from antiretroviral treatment services.

Exploration of the individual and combined effects of predictors of engagement, dropout, and change from digital interventions for recurrent binge eating.

OBJECTIVE: Our ability to predict responsiveness to digital interventions for eating disorders has thus far been poor, potentially for three reasons: (1) there has been a narrow set of predictors explored; (2) prediction has mostly focused on symptom change, ignoring other aspects of the user journey (uptake, early engagement); and (3) there is an excessive focus on the unique effects of predictors rather than the combined contributions of a predictor set. We evaluated the univariate and multivariate effects of outcome predictors in the context of a randomized trial (n = 398) of digitally delivered interventions for recurrent binge eating. METHOD: Thirty baseline variables were selected as predictors, ranging from specific symptoms, to key protective factors, to technological acceptance, and to online treatment attitudes. Outcomes included uptake, early engagement, and remission. Univariate (d) and multivariate (D) standardized mean differences were calculated to estimate the individual and combined effects of predictors, respectively. RESULTS: At the univariate level, few predictors produced an effect size larger than what is considered small (d > .20) across outcomes. However, our multivariate approach enhanced prediction (Ds = .65 to 1.12), producing accuracy rates greater than chance (63%-71% accuracy). Less than half of the chosen variables proved to be useful in contributing to predictions in multivariate models. CONCLUSION: Findings suggest that accuracy in outcome prediction from digitally delivered interventions may be better driven by the aggregation of many small effects rather than one or several largely influential predictors. Replication with different data streams (sensor, neuroimaging) would be useful. PUBLIC SIGNIFICANCE: Our ability to predict who will and will not benefit from digital interventions for eating disorders has been poor. We highlight the viability of a multivariate approach to outcome prediction, whereby prediction may be better driven by the aggregation of many small effects rather than one or a few influential predictors.

Dropout From Exercise Interventions in Adults With Fibromyalgia: A Systematic Review and Meta-analysis.

OBJECTIVE: To meta-analyze the prevalence and predictors of dropout rates among adults with fibromyalgia participating in exercise randomized controlled trials (RCTs). DATA SOURCES: Two authors searched Embase, CINAHL, PsycARTICLES, and Medline up to 01/21/2023. STUDY SELECTION: We included RCTs of exercise interventions in people with fibromyalgia that reported dropout rates. DATA EXTRACTION: Dropout rates from exercise and control conditions and exerciser/participant, provider, and design/implementation related predictors. DATA SYNTHESIS: A random effects meta-analysis and meta-regression were conducted. In total, 89 RCTs involving 122 exercise arms in 3.702 people with fibromyalgia were included. The trim-and-fill-adjusted prevalence of dropout across all RCTs was 19.2% (95% CI=16.9%-21.8%), which is comparable with the dropout observed in control conditions with the trim-and-fill-adjusted odds ratio being 0.31 (95% CI=0.92-1.86, P=.44). Body mass index (R2=0.16, P=.03) and higher effect of illness (R2=0.20, P=.02) predicted higher dropout. The lowest dropout was observed in exergaming, compared with other exercise types (P=.014), and in lower-intensity exercises, compared with high intensity exercise (P=.03). No differences in dropout were observed for the frequency or duration of the exercise intervention. Continuous supervision by an exercise expert (eg, physiotherapist) resulted in the lowest dropout rates (P<.001). CONCLUSIONS: Exercise dropout in RCTs is comparable with control conditions, suggesting that exercise is a feasible and accepted treatment modality; however, interventions are ideally supervised by an expert (eg, physiotherapist) to minimize the risk of dropout. Experts should consider a high BMI and the effect of the illness as risk factors for dropout.

Rate and reasons for peritoneal dialysis dropout following haemodialysis to peritoneal dialysis switch: a systematic review and meta-analysis.

BACKGROUND: Patient experiences and survival outcomes can be influenced by the circumstances related to dialysis initiation and subsequent modality choices. This systematic review and meta-analysis aimed to explore the rate and reasons for peritoneal dialysis (PD) dropout following haemodialysis (HD) to PD switch. METHOD: This systematic review conducted searches in four databases, including Medline, PubMed, Embase, and Cochrane. The protocol was registered on PROSPERO (study ID: CRD42023405718). Outcomes included factors leading to the switch from HD to PD, the rate and reasons for PD dropout and mortality difference in two groups (PD first group versus HD to PD group). The Critical Appraisal Skills Programme (CASP) checklist and the GRADE tool were used to assess quality. RESULTS: 4971 papers were detected, and 13 studies were included. On meta-analysis, there was no statistically significant difference in PD dropout in the PD first group (OR: 0.81; 95%CI: 0.61, 1.09; I2 = 83%; P = 0.16), however, there was a statistically significant reduction in the rate of mortality (OR: 0.48; 95%CI: 0.25, 0.92; I2 = 73%; P = 0.03) compared to the HD to PD group. The primary reasons for HD to PD switch, included vascular access failure, patient preference, social issues, and cardiovascular disease. Causes for PD dropout differed between the two groups, but inadequate dialysis and peritonitis were the main reasons for PD dropout in both groups. CONCLUSION: Compared to the PD first group, a previous HD history may not impact PD dropout rates for patients, but it could impact mortality in the HD to PD group. The reasons for PD dropout differed between the two groups, with no statistical differences. Psychosocial reasons for PD dropout are valuable to further research. Additionally, establishing a consensus on the definition of PD dropout is crucial for future studies.

Interpersonal sensitivity predicts slower change and less change in anxiety symptoms in cognitive behavioural therapy.

OBJECTIVES: Patients in cognitive behavioural therapy (CBT) who are high in interpersonal sensitivity may have difficulty fully engaging in treatment because therapy sessions require intimate interpersonal interactions that are especially uncomfortable for these individuals. The current study tests the hypotheses that patients who are high in interpersonal sensitivity benefit less from CBT for symptoms of depression and anxiety, show a slower rate of change in those symptoms, and are more likely to drop out of treatment. METHODS: Participants were 832 outpatients who received naturalistic CBT. We assessed interpersonal sensitivity before treatment began and depression and anxiety symptoms at every therapy session. We assessed early, premature, and uncollaborative termination after treatment ended. We constructed multilevel linear regression models and logistic regression models to assess the effects of baseline interpersonal sensitivity on the treatment outcome, the slope of change in depression and anxiety symptoms, and each type of dropout. RESULTS: Higher baseline interpersonal sensitivity was associated with a slower rate of change and less overall change in anxiety but not depressive symptoms. Baseline interpersonal sensitivity was not a predictor of dropout. CONCLUSIONS: Interpersonal sensitivity at baseline predicts less change and a slower rate of change in anxiety symptoms. Early detection of elevated interpersonal sensitivity can help therapists take action to address these barriers to successful treatment and help scientists build decision support tools that accurately predict the trajectory of change in anxiety symptoms for these patients.

Attrition in Conversational Agent-Delivered Mental Health Interventions: Systematic Review and Meta-Analysis.

BACKGROUND: Conversational agents (CAs) or chatbots are computer programs that mimic human conversation. They have the potential to improve access to mental health interventions through automated, scalable, and personalized delivery of psychotherapeutic content. However, digital health interventions, including those delivered by CAs, often have high attrition rates. Identifying the factors associated with attrition is critical to improving future clinical trials. OBJECTIVE: This review aims to estimate the overall and differential rates of attrition in CA-delivered mental health interventions (CA interventions), evaluate the impact of study design and intervention-related aspects on attrition, and describe study design features aimed at reducing or mitigating study attrition. METHODS: We searched PubMed, Embase (Ovid), PsycINFO (Ovid), Cochrane Central Register of Controlled Trials, and Web of Science, and conducted a gray literature search on Google Scholar in June 2022. We included randomized controlled trials that compared CA interventions against control groups and excluded studies that lasted for 1 session only and used Wizard of Oz interventions. We also assessed the risk of bias in the included studies using the Cochrane Risk of Bias Tool 2.0. Random-effects proportional meta-analysis was applied to calculate the pooled dropout rates in the intervention groups. Random-effects meta-analysis was used to compare the attrition rate in the intervention groups with that in the control groups. We used a narrative review to summarize the findings. RESULTS: The systematic search retrieved 4566 records from peer-reviewed databases and citation searches, of which 41 (0.90%) randomized controlled trials met the inclusion criteria. The meta-analytic overall attrition rate in the intervention group was 21.84% (95% CI 16.74%-27.36%; I2=94%). Short-term studies that lasted ≤8 weeks showed a lower attrition rate (18.05%, 95% CI 9.91%- 27.76%; I2=94.6%) than long-term studies that lasted >8 weeks (26.59%, 95% CI 20.09%-33.63%; I2=93.89%). Intervention group participants were more likely to attrit than control group participants for short-term (log odds ratio 1.22, 95% CI 0.99-1.50; I2=21.89%) and long-term studies (log odds ratio 1.33, 95% CI 1.08-1.65; I2=49.43%). Intervention-related characteristics associated with higher attrition include stand-alone CA interventions without human support, not having a symptom tracker feature, no visual representation of the CA, and comparing CA interventions with waitlist controls. No participant-level factor reliably predicted attrition. CONCLUSIONS: Our results indicated that approximately one-fifth of the participants will drop out from CA interventions in short-term studies. High heterogeneities made it difficult to generalize the findings. Our results suggested that future CA interventions should adopt a blended design with human support, use symptom tracking, compare CA intervention groups against active controls rather than waitlist controls, and include a visual representation of the CA to reduce the attrition rate. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42022341415; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341415.

Examining trauma, anxiety, and depression as predictors of dropout from residential treatment for substance use disorders.

Substance use disorders (SUDs) are highly prevalent and have deleterious effects on one's health and well-being. Inpatient treatment for SUDs reduces patient relapse, which subsequently ameliorates these negative effects on the individual and society. Additionally, those who complete treatment are less likely to relapse compared to those who do not complete treatment. Thus, maintaining patient engagement in treatment and reducing the rates of those leaving against medical advice (AMA) is particularly important. Examining the factors and comorbidities that may contribute to treatment dropout has the potential to identify at-risk patients in need of additional individualized intervention. The current study aimed to examine comorbid anxiety, depression, and posttraumatic stress disorder (PTSD) symptoms as predictors of dropout AMA in a residential substance use treatment population. Results showed that patients with social anxiety were more likely to leave treatment AMA, while those with PTSD were more likely to complete treatment. Findings suggest that PTSD-specific treatment, as offered in this facility, may help with patient retention, while group focused therapy may be distressing to those with social anxiety. Clinical implications of this research may include incorporating evidence-based practice for social anxiety early during inpatient treatment to reduce anxiety such that patients may better engage with SUDs treatment.

Low-Dose Edoxaban in Very Elderly Patients with Atrial Fibrillation.

BACKGROUND: Implementation of appropriate oral anticoagulant treatment for the prevention of stroke in very elderly patients with atrial fibrillation is challenging because of concerns regarding bleeding. METHODS: We conducted a phase 3, multicenter, randomized, double-blind, placebo-controlled, event-driven trial to compare a once-daily 15-mg dose of edoxaban with placebo in elderly Japanese patients (≥80 years of age) with nonvalvular atrial fibrillation who were not considered to be appropriate candidates for oral anticoagulant therapy at doses approved for stroke prevention. The primary efficacy end point was the composite of stroke or systemic embolism, and the primary safety end point was major bleeding according to the definition of the International Society on Thrombosis and Haemostasis. RESULTS: A total of 984 patients were randomly assigned in a 1:1 ratio to receive a daily dose of 15 mg of edoxaban (492 patients) or placebo (492 patients). A total of 681 patients completed the trial, and 303 discontinued (158 withdrew, 135 died, and 10 had other reasons); the numbers of patients who discontinued the trial were similar in the two groups. The annualized rate of stroke or systemic embolism was 2.3% in the edoxaban group and 6.7% in the placebo group (hazard ratio, 0.34; 95% confidence interval [CI], 0.19 to 0.61; P<0.001), and the annualized rate of major bleeding was 3.3% in the edoxaban group and 1.8% in the placebo group (hazard ratio, 1.87; 95% CI, 0.90 to 3.89; P = 0.09). There were substantially more events of gastrointestinal bleeding in the edoxaban group than in the placebo group. There was no substantial between-group difference in death from any cause (9.9% in the edoxaban group and 10.2% in the placebo group; hazard ratio, 0.97; 95% CI, 0.69 to 1.36). CONCLUSIONS: In very elderly Japanese patients with nonvalvular atrial fibrillation who were not appropriate candidates for standard doses of oral anticoagulants, a once-daily 15-mg dose of edoxaban was superior to placebo in preventing stroke or systemic embolism and did not result in a significantly higher incidence of major bleeding than placebo. (Funded by Daiichi Sankyo; ELDERCARE-AF ClinicalTrials.gov number, NCT02801669.).

Absconding among admitted patients with bipolar affective disorder diagnosis in Uganda.

BACKGROUND: Hospitalization is often necessary for individuals with Bipolar affective Disorder (BAD) during severe manic or depressive episodes, as well as for stabilizing treatment regimens. However, a significant proportion of patients admitted for treatment of BAD abscond or leave the hospital without permission during their stay. In addition, patients managed for BAD may have unique characteristics that might force them into absconding. For example, the high prevalence of co-morbid substance use disorder - craving to use substances, suicidal behaviors - attempts to die by suicide, and cluster B personality disorders - characterized by impulsive acts. It is, therefore, essential to understand the factors contributing to absconding among patients with BAD, to facilitate designing strategies for preventing and managing this behavior. METHOD: This study was based on a retrospective chart review of the inpatients diagnosed with BAD at a tertiary psychiatry facility in Uganda from January 2018 to December 2021. RESULTS: Approximately 7.8% of those with BAD absconded from the hospital. The likelihood of absconding among those with BAD increased with the use of cannabis [adjusted odds ratio (aOR) = 4.00, 95% confidence interval (CI) = 1.22-13.09, p-value = 0.022] and having mood lability [aOR = 2.15, 95% CI = 1.10-4.21, p-value = 0.025]. However, receiving psychotherapy during the admission (aOR = 0.44, 95 CI = 0.26-0.74, p-value = 0.002) and treatment with haloperidol (aOR = 0.39, 95% CI = 0.18-0.83, p-value = 0.014) reduced the likelihood of absconding. CONCLUSION: Absconding among patients with BAD is common in Uganda. Those with symptoms of affective lability and those with comorbid cannabis use tend to abscond more, while those who receive haloperidol and psychotherapy are less likely to abscond.

An assessment of the effectiveness of an electronic wristband in improving routine immunization timeliness and reducing drop-out.

BACKGROUND: To assess the effectiveness of a wristband for immunization alert (WIA) as a reminder device to caregivers to improve immunization timeliness and reduce drop-outs. METHODS: Eight health facilities, selected from two local government areas in Kano state, Northwestern Nigeria, were clustered in a two-arm study involving an intervention group and a control group. Only the caregivers (757) from the intervention group received WIA as an immunization reminder device. Immunization timeliness data were then collected from the control and intervention groups for the period of intervention and analyzed using Microsoft Excel and IBM SPSS version 21. RESULTS: A cohort analysis of caregivers who received WIA at their second visit showed an increase in immunization timeliness from 10% at the second visit to 86% at the third visit and maintained at 66% for the fifth visit. A difference-in-difference analysis of the effect of WIA on immunization timeliness from baseline to end-line in the control and intervention groups showed a positive 30% increase in immunization timeliness associated with the introduction of WIA. INTERPRETATION: Given that immunization timeliness and drop-outs are reported issues of concern in Northwestern Nigeria, the use of the WIA device is a recommended intervention.

Mediators of Ethnic Differences in Dropout Rates From a Randomized Controlled Treatment Trial Among Latinx and Non-Latinx White Primary Care Patients With Anxiety Disorders.

ABSTRACT: Disparities in treatment engagement and adherence based on ethnicity have been widely recognized but are inadequately understood. Few studies have examined treatment dropout among Latinx and non-Latinx White (NLW) individuals. Using Andersen's Behavioral Model of Health Service Use (A behavioral model of families' use of health services. 1968; J Health Soc Behav. 1995; 36:1-10) as a framework, we examine whether pretreatment variables (categorized as predisposing, enabling, and need factors) mediate the relationship between ethnicity and premature dropout in a sample of Latinx and NLW primary care patients with anxiety disorders who participated in a randomized controlled trial (RCT) of cognitive behavioral therapy. Data from a total of 353 primary care patients were examined; 96 Latinx and 257 NLW patients participated. Results indicated that Latinx patients dropped out of treatment more often than NLW patients, resulting in roughly 58% of Latinx patients failing to complete treatment compared with 42% of NLW, and approximately 29% of Latinx patients dropping out before engaging in modules related to cognitive restructuring or exposure, relative to 11% of NLW patients. Mediation analyses suggest that social support and somatization partially explained the relationship between ethnicity and treatment dropout, highlighting the importance of these variables in understanding treatment disparities.

Closing the health gap in Central Australia: reduction in Indigenous Australian inpatient self-discharge rates following routine collaboration with Aboriginal Health Workers.

BACKGROUND: Indigenous Australians experience significant socioeconomic disadvantage and healthcare disparity compared to non-Indigenous Australians. A retrospective cohort study to describe the association between rates of self-discharge in Indigenous orthopaedic patients and the introduction of routine Aboriginal Liaison Officers (ALO) within the Orthopaedic multi-disciplinary team (MDT) was performed. METHODS: ALO were introduced within our routine Orthopaedic MDT on the 22nd of February 2021. Two patient cohorts were analysed, Group 1; patients admitted in the 9-months prior to inclusion of ALO, and Group 2; patients admitted within 9-months thereafter. The primary outcome of interest was the rate of self-discharge among Indigenous patients. Secondary outcomes of interest were the stage of treatment when patients self-discharged, recurrent self-discharge, risk factors for self-discharge and association between self-discharge and length of hospital stay. RESULTS: Introduction of ALO within routine Orthopaedic MDT was associated with a significant 37% reduced risk of self-discharge among Indigenous patients (p = 0·009), and significantly fewer self-discharges before their definitive surgical and medical treatment (p = 0·0024), or before completion of postoperative intravenous antibiotic treatment (p = 0·030). There was no significant change in the risk of recurrent self-discharge (p = 0·557). Risk factors for self-discharge were younger age; pensioners or unemployed; residents of Alice Springs Town-Camps or of communities within 51 to 100 km of Alice Springs; and those diagnosed with lacerations of the upper limb, but without tendon injury, wound and soft tissue infections or osteomyelitis. In Group 2, the odds of self-discharge decreased with increased length of hospital stay (p = 0·040). CONCLUSIONS: Routine inclusion of ALO within the Orthopaedic MDT reduced the risk of self-discharge in Indigenous patients. Those who self-discharged did so only after critical aspects of their care were met.

Predicting the drop out from the maternal, newborn and child healthcare continuum in three East African Community countries: application of machine learning models.

BACKGROUND: For optimal health, the maternal, newborn, and child healthcare (MNCH) continuum necessitates that the mother/child receive the full package of antenatal, intrapartum, and postnatal care. In sub-Saharan Africa, dropping out from the MNCH continuum remains a challenge. Using machine learning, the study sought to forecast the MNCH continuum drop out and determine important predictors in three East African Community (EAC) countries. METHODS: The study utilised Demographic Health Surveys data from the Democratic Republic of Congo (DRC) (2013/14), Kenya (2014) and Tanzania (2015/16). STATA 17 was used to perform the multivariate logistic regression. Python 3.0 was used to build five machine learning classification models namely the Logistic Regression, Random Forest, Decision Tree, Support Vector Machine and Artificial Neural Network. Performance of the models was assessed using Accuracy, Precision, Recall, Specificity, F1 score and area under the Receiver Operating Characteristics (AUROC). RESULTS: The prevalence of the drop out from the MNCH continuum was 91.0% in the DRC, 72.4% in Kenya and 93.6% in Tanzania. Living in the rural areas significantly increased the odds of dropping out from the MNCH continuum in the DRC (AOR:1.76;95%CI:1.30-2.38), Kenya (AOR:1.23;95%CI:1.03-1.47) and Tanzania (AOR:1.41;95%CI:1.01-1.97). Lower maternal education also conferred a significant increase in the DRC (AOR:2.16;95%CI:1.67-2.79), Kenya (AOR:1.56;95%CI:1.30-1.84) and Tanzania (AOR:1.70;95%CI:1.24-2.34). Non exposure to mass media also conferred a significant positive influence in the DRC (AOR:1.49;95%CI:1.15-1.95), Kenya (AOR:1.46;95%CI:1.19-1.80) and Tanzania (AOR:1.65;95%CI:1.13-2.40). The Random Forest exhibited superior predictive accuracy (Accuracy = 75.7%, Precision = 79.1%, Recall = 92.1%, Specificity = 51.6%, F1 score = 85.1%, AUROC = 70%). The top four predictors with the greatest influence were household wealth, place of residence, maternal education and exposure to mass media. CONCLUSIONS: The MNCH continuum dropout rate is very high in the EAC countries. Maternal education, place of residence, and mass media exposure were common contributing factors to the drop out from MNCH continuum. The Random Forest had the highest predictive accuracy. Household wealth, place of residence, maternal education and exposure to mass media were ranked among the top four features with significant influence. The findings of this study can be used to support evidence-based decisions in MNCH interventions and to develop web-based services to improve continuity of care retention.

Predictors of psychotherapy dropout in patients with borderline personality disorder: A systematic review.

INTRODUCTION: Borderline personality disorder (BPD) is a highly debilitating psychiatric condition. Despite the expansion of new BPD specific forms of psychotherapy in the last few decades, high dropout rates have been reported in these treatments. Treatment discontinuation is associated with poor patient outcomes, inefficient resource utilization and the demoralization of healthcare providers. METHODS: In order to identify predictors of psychotherapy dropout among patients with BPD, a systematic search of Medline, the Cochrane Library, PsycInfo and PsycArticles was conducted. Studies included were randomized-controlled trials in which patients diagnosed with BPD were exposed to a therapeutic intervention consisted of an evidence-based psychotherapy. The quality of evidence in the studies was assessed through the use of revised Cochrane risk of bias tool. RESULTS: Six articles, incorporating four types of psychotherapy programmes, were included. Overall, the studies present low risk of attrition and reporting bias and unclear risk of selection, performance and detection bias. Patients with weaker therapeutic alliance scores and higher hostility presented with higher dropout rates. In contrast, better mindfulness skills and greater performance in specific neuropsychological domains, such as memory and executive control, were identified as predictive of lower risk of dropout. Sociodemographic variables and treatment history did not influence treatment retention. CONCLUSIONS: Factors that influence discontinuation should be taken into consideration in future treatment programmes, in an effort to optimize retention. Qualitative assessments of patients' reasons for dropping out may also help guide adjustments.

Understanding dropout and non-participation in follow-up evaluation for the benefit of patients and research: evidence from a longitudinal observational study on patients with eating disorders.

Treatment outcomes in eating disorders (EDs) are still an open field for clinicians and researchers. Besides difficulties in egosyntonic-linked treatment engagements, dropout is one of the most crucial elements that cause a reduction in the treatment efficacy. Thus, the aim of this study is to evaluate factors that could contribute to high dropout rates and non-participation in follow-up evaluation in patients with ED. This study used a large sample of patients from a specialized ED ward and day hospital (DH). A sample of 428 individuals was recruited for this study. Psychological and demographic data were collected at the time of hospitalization and discharge from the facilities. These data were used to explore a possible link between dropout and follow-up non-participation. Specially, the random forest was used to rank demographic and psychological features in importance and evaluate the top results with regression analyses for statistical significance. A dropout rate of 12.14% during inpatient and DH treatment was found. Anger-hostility and general psychopathology were found to be predictors of dropout during treatment, while the duration of the hospitalization predicted non-participation at the six-month follow-up. Specific psychological features should be considered before and during treatments for patients with EDs to reduce dropout rates. The duration of the hospitalization should also be evaluated as a relevant healthcare element that could affect engagement and, accordingly, outcome.

The feasibility of daily monitoring in adolescents and young adults with mild intellectual disability or borderline intellectual functioning.

BACKGROUND: It is unclear whether the limitations of young persons with a mild intellectual disability or borderline intellectual functioning preclude feasibility of the daily diary method. METHOD: For 60 consecutive days, 50 participants (Mage = 21.4, 56% male) who receive care in an ambulatory, residential, or juvenile detention setting, self-rated both standardised and personalised diary questions through an app. Diary entries were used for feedback in treatment. Interviews were used to explore acceptability. RESULTS: Average compliance was 70.4%, while 26% of participants dropped out. Compliance was good in ambulatory (88.9%) and residential care (75.6%), but not in the juvenile detention setting (19.4%). The content of self-selected diary items varied widely. Participants deemed the method acceptable. CONCLUSIONS: Daily monitoring is feasible for individuals with a mild intellectual disability or borderline intellectual functioning receiving ambulatory or residential care, and can provide scientists and practitioners with important insights into day-to-day behavioural patterns.

Downstaging Outcomes for Hepatocellular Carcinoma: Results From the Multicenter Evaluation of Reduction in Tumor Size before Liver Transplantation (MERITS-LT) Consortium.

BACKGROUND & AIMS: United Network of Organ Sharing (UNOS) has adopted uniform criteria for downstaging (UNOS-DS) of hepatocellular carcinoma (HCC) before liver transplantation (LT), but the downstaging success rate and intention-to-treat outcomes across broad geographic regions are unknown. METHODS: In this first multiregional study (7 centers, 4 UNOS regions), 209 consecutive patients with HCC undergoing downstaging based on UNOS-DS criteria were prospectively evaluated from 2016 to 2019. RESULTS: Probability of successful downstaging to Milan criteria and dropout at 2 years from the initial downstaging procedure was 87.7% and 37.3%, respectively. Pretreatment with lectin-reactive α-fetoprotein ≥10% (hazard ratio, 3.7; P = .02) was associated with increased dropout risk. When chemoembolization (n = 132) and yttrium-90 radioembolization (n = 62) were compared as the initial downstaging treatment, there were no differences in Modified Response Evaluation Criteria In Solid Tumors response, probability of or time to successful downstaging, waiting list dropout, or LT. Probability of LT at 3 years was 46.6% after a median of 17.2 months. In the explant, 17.5% had vascular invasion, and 42.8% exceeded Milan criteria (understaging). The only factor associated with understaging was the sum of the number of lesions plus largest tumor diameter on the last pre-LT imaging, and the odds of understaging increased by 35% per 1-unit increase in this sum. Post-LT survival at 2 years was 95%, and HCC recurrence occurred in 7.9%. CONCLUSION: In this first prospective multiregional study based on UNOS-DS criteria, we observed a successful downstaging rate of >80% and similar efficacy of chemoembolization and yttrium-90 radioembolization as the initial downstaging treatment. A high rate of tumor understaging was observed despite excellent 2-year post-LT survival of 95%. Additional LRT to reduce viable tumor burden may reduce tumor understaging.

Performance of pre-transplant criteria in prediction of hepatocellular carcinoma progression and waitlist dropout.

BACKGROUND & AIM: Liver transplantation (LT) selection models for hepatocellular carcinoma (HCC) have not been proposed to predict waitlist dropout because of tumour progression. The aim of this study was to compare the alpha-foetoprotein (AFP) model and other pre-LT models in their prediction of HCC dropout. METHODS: A multicentre cohort study was conducted in 20 Latin American transplant centres, including 994 listed patients for LT with HCC from 2012 to 2018. Longitudinal tumour characteristics, and patterns of progression were recorded at time of listing, after treatments and at last follow-up over the waitlist period. Competing risk regression models were performed, and model's discrimination was compared estimating Harrell's adapted c-statistics. RESULTS: HCC dropout rate was significantly higher in patients beyond (24% [95% CI 16-28]) compared to those within Milan criteria (8% [95% IC 5%-12%]; p < .0001), with a SHR of 3.01 [95% CI 2.03-4.47]), adjusted for waiting list time and bridging therapies (c-index 0.63 [95% CI 0.57; 0.69). HCC dropout rates were higher in patients with AFP scores >2 (adjusted SHR of 3.17 [CI 2.13-4.71]), c-index of 0.71 (95% CI 0.65-0.77; p = .09 vs Milan). Similar discrimination power for HCC dropout was observed between the AFP score and the Metroticket 2.0 model. In patients within Milan, an AFP score >2 points discriminated two populations with a higher risk of HCC dropout (SHR 1.68 [95% CI 1.08-2.61]). CONCLUSIONS: Pre-transplant selection models similarly predicted HCC dropout. However, the AFP model can discriminate a higher risk of dropout among patients within Milan criteria.

Biased estimation with shared parameter models in the presence of competing dropout mechanisms.

Recently, Thomadakis et al. quantified potential sources of bias that can occur when shared parameter (SP) models are used to jointly model longitudinal trends of a biomarker over time (e.g., a slope) and time-to-dropout in an effort to address concerns over possible informative censoring. Although SP models induce no bias under a missingness completely at random dropout mechanism, the authors demonstrate that bias can occur under a missingness at random (MAR) dropout mechanism wherein dropout depends on the observed biomarker data. To address this, the authors propose including the most recent observed marker value within the hazard function for the time-to-dropout portion of an SP model. They demonstrate via a limited simulation that the proposed model minimizes bias under a specific MAR dropout mechanism and a specific missingness not-at-random dropout mechanism. In the present article, we compare and contrast their work with that of previous authors by illustrating via simulation and an example the degree of bias or lack thereof that can occur when applying SP models, particularly, in the presence of competing dropout mechanisms. We propose the use of a competing risk SP model as a means to minimize bias whenever competing dropout mechanisms are suspected assuming the competing mechanisms result from distinct observable causes of dropout.

Sensitivity to missing not at random dropout in clinical trials: Use and interpretation of the trimmed means estimator.

Outcome values in randomized controlled trials (RCTs) may be missing not at random (MNAR), if patients with extreme outcome values are more likely to drop out (eg, due to perceived ineffectiveness of treatment, or adverse effects). In such scenarios, estimates from complete case analysis (CCA) and multiple imputation (MI) will be biased. We investigate the use of the trimmed means (TM) estimator for the case of univariable missingness in one continuous outcome. The TM estimator operates by setting missing values to the most extreme value, and then "trimming" away equal fractions of both groups, estimating the treatment effect using the remaining data. The TM estimator relies on two assumptions, which we term the "strong MNAR" and "location shift" assumptions. We derive formulae for the TM estimator bias resulting from the violation of these assumptions for normally distributed outcomes. We propose an adjusted TM estimator, which relaxes the location shift assumption and detail how our bias formulae can be used to establish the direction of bias of CCA and TM estimates, to inform sensitivity analyses. The TM approach is illustrated in a sensitivity analysis of the CoBalT RCT of cognitive behavioral therapy (CBT) in 469 individuals with 46 months follow-up. Results were consistent with a beneficial CBT treatment effect, with MI estimates closer to the null and TM estimates further from the null than the CCA estimate. We propose using the TM estimator as a sensitivity analysis for data where extreme outcome value dropout is plausible.