Second-generation antipsychotics for Parkinson's disease psychosis: A systematic review and network meta-analysis

OBJECTIVE

This network meta-analysis assessed the efficacy, tolerability, and acceptability of second-generation antipsychotics (SGAs) for Parkinson's disease psychosis (PDP).

METHODS

We searched PubMed, Embase, Cochrane Library, and ClinicalTrials.gov for randomized controlled trials investigating SGAs for PDP up to October 26, 2023.

RESULTS

We included 16 trials (N = 1252) investigating clozapine, melperone, olanzapine, pimavanserin, quetiapine, ulotaront, and placebo. In comparisons between SGAs and placebo, the findings were: i) Standardized mean differences, 95% confidence intervals (SMDs, 95%CIs), for psychotic-symptom reduction revealed the first rank of clozapine (-1.31, -1.73 to -0.89), the second rank of pimavanserin, with significant inferiority of quetiapine (SMD = 0.47, 0.02 to 0.92); ii) Mean differences (MDs, 95%CIs) for abnormal movement, as assessed by the Unified Parkinson's Disease Rating Scale - Part III, indicated that clozapine had the least motor side effects (-0.92, -2.75 to 0.91); iii) Risk ratios (RRs, 95% CIs) for adverse-effect dropout rates were lowest for melperone (1.02, 0.20 to 5.24); and iv) RRs (95% CIs) for all-cause dropout rates were lowest for clozapine (0.73, 0.42 to 1.25).

CONCLUSIONS

For patients with PDP, clozapine may substantially reduce psychotic symptoms with minimal abnormal movement, high acceptability, and moderate overall tolerability. Pimavanserin, not quetiapine, could be an alternative.

Digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-Tracker data below one-year children in Bangladesh during-COVID and pre-COVID period

Background

With an impressive track record in expanding childhood immunization and an inclination to adopt digitalization in healthcare service delivery, Expanded Program on Immunization (EPI) Bangladesh piloted the e-Tracker intervention in Moulvibazar district and Dhaka South City Corporation (Zone-5) from 2019 till the end of 2021.

Methods

We retrieved and analyzed the digitalized e-Tracker data of 114,194 infants born between January 1, 2019 and December 31, 2020, with help from Health Management Information System (HMIS) and UNICEF Bangladesh. Childhood vaccination coverage and dropout rates were determined using a 'Traditional approach' traditionally used by WHO and a 'Conditional technique' with a modified denominator. Using a multiple logistic regression model, we examined the effects of COVID-19, birth-cohorts, mother education, and location on vaccination rates (coverages & dropouts) to aid with informed decision-making by the policymakers.

Findings

The conditional estimation method yielded a lower full vaccination coverage during pre-COVID period than the national and global reported coverage derived using the 'traditional method' (73.4% vs. 89.0% & 81.0%). As expected, while the coverage has decreased, the dropout rate increased "during-COVID" compared to the "pre-COVID" period. However, dropouts were estimated lower in the 'conditional method.' The average age (in months) for getting BCG was higher in Moulvibazar (∼2.5 months) than that in Dhaka (∼1.4 months). All birth-cohorts from 'the during-COVID period had about 30% lower odds of getting fully vaccinated than those from the 'pre-COVID' period.

Interpretations

Age-cohort-specific analysis showed a decline in coverage rates before and during COVID, but e-Tracker didn't have enough data to draw additional conclusions. The server only stored the child's gender, the caregiver's monthly salary, and the mother's education. It didn't track any other factors related to dropout rates. The e-Tracker is an excellent tool for measuring real coverage and should be scaled nationwide.

Funding

UNICEF, Bangladesh.

Exploring the relationship between mental health-related problems and undergraduate student dropout: A case study within a civil engineering program

Dropout has always been a concerning issue within higher education. This research explores the relationship between mental health-related problems and undergraduate students' dropout rates amid the COVID-19 pandemic and within a civil engineering program. The study is quantitative descriptive, with a non-experimental and longitudinal design. Results show that the dropout rates of civil engineering students from a private university have increased, comparing before and after the COVID-19 pandemic, primarily due to mental health-related problems. Three strong tendencies within these rates have been detected, directly related to the COVID-19 pandemic. It was concluded that undergraduate students' mental health had been undermined due to the pandemics, which has had an immediate impact on the increase of dropout rates.

Guided internet interventions for depression: impact of sociodemographic factors on treatment outcome in Indonesia

Depression is the leading cause of disability worldwide, but an alarming treatment gap exists, especially in lower- and middle income countries (LMIC), where people are exposed to many societal and sociodemographic risk factors. As internet access increases in LMIC, online interventions could decrease this gap, especially when shown suitable for all demographics, including vulnerable groups with low socioeconomic status (SES). We used mixed-model analysis to explore moderating effects of sociodemographic factors (age, sex, education level, SES and urbanicity) on treatment effect in a recent trial in Indonesia, comparing guided online behavioral activation versus online psychoeducation only for depression, in 313 participants from (sub)urban areas. Outcome measures were self-reported Patient Health Questionnaire 9 (PHQ-9) and Inventory of Depressive Symptomatology (IDS-SR). Without correction for multiple testing, we found urbanicity to moderate treatment effect, with stronger treatment effect in suburban relative to urban participants (IDS-SR 24 weeks past baseline, p = 0.04) and a trend towards moderation by SES, with stronger treatment effect in low SES groups (PHQ-9 10 weeks past baseline, p = 0.07). These exploratory results suggest online treatments are a promising mental health intervention for all demographics in a (sub)urban LMIC setting, but hypothesis-testing studies including rural participants are warranted.

Comparative efficacy of five long-term weight loss drugs: quantitative information for medication guidelines

Quantitative information is scarce in current obesity medication guidelines, and they do not clearly reflect the differences in the efficacy characteristics among various drugs. This study quantitatively assessed the efficacy characteristics of five FDA-approved long-term weight loss drugs. Potentially eligible studies were obtained from public databases. Using the differences in the weight change from baseline between the drug group and the corresponding placebo group as the major indicator of efficacy, a time-effect model was established, and crucial pharmacodynamic parameters, such as the maximal efficacy, drug onset time and rate of body weight regain after the maximal efficacy point, were used to reflect the differences in efficacy among the five drugs. Finally, 50 reports (involving 43,443 participants) were included. After deducting the placebo effects, the maximal efficacies (95% CI) of orlistat (120 mg), lorcaserin, naltrexone-bupropion, phentermine-topiramate (PT, 7.5/46 mg) and liraglutide were -2.94 (-5.82, -1.27), -3.06 (-4.39, -1.71), -6.15 (-9.78, -3.25), -7.45 (-9.76, -3.88) and -5.50 (-10.62, -2.97) kg at weeks 60, 54, 67, 59 and 65 respectively, and their rates of body weight regain were 0.51, 0.48, 0.91, 1.27and 0.43 kg per year respectively. The 1-year dropout rates of orlistat, lorcaserin, naltrexone-bupropion, PT and liraglutide were 29.0, 40.9, 49.1, 34.9 and 24.3% respectively. In addition, a significant dose-effect correlation was observed for orlistat and PT. This study provides valid quantitative information for medication guidelines.