Analysis Of Treatment Effects Research Articles

The Impact of Double Pelvic Osteotomy on Dorsolateral Subluxation in 24 Dogs.

The aim of this study was to determine the effect of double pelvic osteotomy (DPO) on dorsolateral subluxation (DLS) of the femoral head in a weight-bearing position. Retrospective observational study with treatment effect analysis. Twenty-four client-owned dogs that underwent DPO due to hip dysplasia. Computed tomography (CT) studies were performed on 24 dogs that underwent a DPO between 2015 and 2021. The patients were positioned with the femora in a weight-bearing position. The DLS score was measured pre-DPO, immediately post-DPO, and at follow-up to determine if DPO resulted in an increase in the DLS score. A total of 21 dogs underwent single-stage bilateral DPO and 3 dogs underwent unilateral DPO resulting in 45 hip joints available for analysis. Follow-up CT was available for 29 of these at a median of 51 days (range: 35-482 days). The mean DLS score was 36.1% ± 14.6 preoperatively, 71.4% ± 12.5 post-DPO, and 70.0% ± 15.3 at follow-up. The increase between the pre- and postoperative measurement was significant (p < 0.001). DPO results in reduced subluxation of the femoral head in a weight-bearing position. The in vivo results suggest that DPO will result in reduced femoral subluxation during weight-bearing.

Female leaders as environmental saviors: Tackling urban pollution in Chinese cities

In the Chinese political context, local government officials have substantial influence over the implementation of policies. The approach to urban environmental management varies significantly between female and male officials, which in turn affects governance outcomes differently. Consequently, the gender of local officials plays a crucial role in shaping urban environmental conditions. This study investigates the impact of female officials on urban environmental pollution in China over the period from 2003 to 2018. Utilizing data from the China Urban Statistical Yearbook combined with individual profiles of officials at the prefecture level, the analysis reveals a notable decrease in urban environmental pollution associated with female leadership. Notably, the effect is more pronounced among younger female officials compared to their older counterparts, and those with higher education levels are particularly effective in curbing pollution emissions. The pollution abatement effect of female officials is found to be stronger in the central regions compared to the eastern and western regions. The robustness of these findings is confirmed through checks against alternative explanatory variables, permutation tests, and treatment effect analyses. Overall, this research contributes new perspectives on management strategies that can sisgnificantly improve urban environmental quality in China.

Do intensive specialized services prevent family separation in parents with intellectual disabilities? A treatment effects analysis

ABSTRACT The current study explores the effectiveness of Project IMPACT, an intensive, in-home, skills-based positive parenting program designed to prevent out-of-home placement for parents with intellectual disabilities. Families participating in Project IMPACT were compared with families in a similar jurisdiction who participated in non-specialized family preservation services using treatment effects analysis. Findings indicate that Project IMPACT is highly effective at keeping families intact. Project IMPACT reduces family separation throughout childhood, the most benefits are seen in early childhood, when the risk of family separation is generally the greatest. Parents with intellectual disability can learn skills to keep children safe at home.

Endovascular thrombectomy in patients with anterior circulation stroke: an emulated real-world comparison

BackgroundEndovascular thrombectomy (EVT) has been proven effective in anterior circulation stroke due to large vessel occlusion (LVO). However, translation from randomized clinical trials (RCTs) with highly selected patients to real-world requires confirmation, particularly to identify associations outside of strict selection criteria.AimsThis study aims to compare functional outcomes after EVT in real-world with those reported in RCTs, and to identify associations with functional outcome after EVT outside RCT-criteria.MethodsThis study analyzed longitudinal German real-world data from the Stroke Research Consortium in Northern Bavaria (STAMINA) cohort from January, 2015 to June, 2019. We conducted a trial emulation, comparing patients with anterior circulation stroke and LVO meeting selection criteria for RCTs investigating EVT (1) predominantly within 6 hours with those from HERMES meta-analysis, and (2) within 6-24 hours with those from AURORA meta-analysis. We (3) analyzed treatment effects of EVT and association with functional outcome in patients treated outside RCT criteria.ResultsOf 598 patients, 281 (47.0%) met RCT-criteria for treatment within 6 hours (hereinafter STAMINA-HERMES), 74 (12.4%) met RCT-criteria for treatment within 6–24 hours (STAMINA-AURORA), and 277 (46.3%) patients received EVT outside RCT-criteria. We observed no difference in rates of functional independence or mortality, comparing STAMINA-HERMES with HERMES meta-analysis (mRS 0-1: n=120/281 [43%] vs. 291/633 [46%], p=0.36; mortality: n=34/281 [12%] vs. 97/633 [15%], p=0.20), and STAMINA-AURORA with AURORA meta-analysis (mRS 0-1: n=26/74 [35%] vs. 122/266 [46%], p=0.10, mortality: n=10/74 [14%] vs. 45/266 [17%], p=0.48). Patients treated outside RCT-criteria had worse outcome (mRS 0-1: n=38/277 [14%], mortality: n=90/277 [32%], both p<0.001); possibly driven by pre-existing functional dependence (n=172/277 [62%]). Compared to matched controls, EVT outside of RCT-criteria was associated with lower mortality (absolute treatment effect: -14%, 95% Confidence Interval [CI] -23 to -5, p<0.01), but not with recovery to functional independence or premorbid functional status (treatment effect: 4%, CI -4 to 11, p=0.34), which was associated with lower NIHSS (Odds ratio [OR] 0.86, CI 0.80-0.92, p<0.001) and age (OR 0.95, CI 0.93-0.98, p=0.002).ConclusionsTranslation of EVT outcomes reported in RCTs into real-world is possible, however, almost half of patients did not meet trial criteria. Identification of patients who functionally benefit from frequently performed EVT outside RCT-criteria requires further investigation.Trial registrationClinicaltrials.gov, NCT04357899.

Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods

BackgroundIn randomized clinical trials, treatment effects may vary, and this possibility is referred to as heterogeneity of treatment effect (HTE). One way to quantify HTE is to partition participants into subgroups based on individual’s risk of experiencing an outcome, then measuring treatment effect by subgroup. Given the limited availability of externally validated outcome risk prediction models, internal models (created using the same dataset in which heterogeneity of treatment analyses also will be performed) are commonly developed for subgroup identification. We aim to compare different methods for generating internally developed outcome risk prediction models for subject partitioning in HTE analysis.MethodsThree approaches were selected for generating subgroups for the 2,441 participants from the United States enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) randomized controlled trial. An extant proportional hazards-based outcomes predictive risk model developed on the overall ASPREE cohort of 19,114 participants was identified and was used to partition United States’ participants by risk of experiencing a composite outcome of death, dementia, or persistent physical disability. Next, two supervised non-parametric machine learning outcome classifiers, decision trees and random forests, were used to develop multivariable risk prediction models and partition participants into subgroups with varied risks of experiencing the composite outcome. Then, we assessed how the partitioning from the proportional hazard model compared to those generated by the machine learning models in an HTE analysis of the 5-year absolute risk reduction (ARR) and hazard ratio for aspirin vs. placebo in each subgroup. Cochran’s Q test was used to detect if ARR varied significantly by subgroup.ResultsThe proportional hazard model was used to generate 5 subgroups using the quintiles of the estimated risk scores; the decision tree model was used to generate 6 subgroups (6 automatically determined tree leaves); and the random forest model was used to generate 5 subgroups using the quintiles of the prediction probability as risk scores. Using the semi-parametric proportional hazards model, the ARR at 5 years was 15.1% (95% CI 4.0–26.3%) for participants with the highest 20% of predicted risk. Using the random forest model, the ARR at 5 years was 13.7% (95% CI 3.1–24.4%) for participants with the highest 20% of predicted risk. The highest outcome risk group in the decision tree model also exhibited a risk reduction, but the confidence interval was wider (5-year ARR = 17.0%, 95% CI= -5.4–39.4%). Cochran’s Q test indicated ARR varied significantly only by subgroups created using the proportional hazards model. The hazard ratio for aspirin vs. placebo therapy did not significantly vary by subgroup in any of the models. The highest risk groups for the proportional hazards model and random forest model contained 230 participants each, while the highest risk group in the decision tree model contained 41 participants.ConclusionsThe choice of technique for internally developed models for outcome risk subgroups influences HTE analyses. The rationale for the use of a particular subgroup determination model in HTE analyses needs to be explicitly defined based on desired levels of explainability (with features importance), uncertainty of prediction, chances of overfitting, and assumptions regarding the underlying data structure. Replication of these analyses using data from other mid-size clinical trials may help to establish guidance for selecting an outcomes risk prediction modelling technique for HTE analyses.

Analyzing Treatment Effect by Integrating Existing Propensity Score and Outcome Regressions with Heterogeneous Covariate Sets

Analyzing treatment or exposure effect is a major research theme in scientific studies. In the current big-data era where multiple sources of data are available, it is of interest to perform a synthesized analysis of treatment effects by integrating information from different data sources or studies. However, studies may contain heterogeneous and incomplete covariate sets, and individual data therein may not be accessible. We apply and extend the generalized meta-analysis method to integrate summary results (e.g., regression coefficients) of outcome and treatment (propensity score, PS) regression analyses across different datasets that may contain heterogeneous covariate sets. The proposed integrated analysis utilizes a reference dataset, which contains data on the complete set of covariates. The asymptotic distribution for the proposed integrated estimator is established. Simulations reveal that the proposed estimator performs well. We apply the proposed method to obtain the causal effect of waist circumference on hypertension by integrating two existing outcomes and PS regression analyses with different sets of covariates.

Impact of linkage level on inferences from big data analyses in health and medical research: an empirical study

BackgroundLinkage errors that occur according to linkage levels can adversely affect the accuracy and reliability of analysis results. This study aimed to identify the differences in results according to personally identifiable information linkage level, sample size, and analysis methods through empirical analysis.MethodsThe difference between the results of linkage in directly identifiable information (DII) and indirectly identifiable information (III) linkage levels was set as III linkage based on name, date of birth, and sex and DII linkage based on resident registration number. The datasets linked at each level were named as databaseIII (DBIII) and databaseDII (DBDII), respectively. Considering the analysis results of the DII-linked dataset as the gold standard, descriptive statistics, group comparison, incidence estimation, treatment effect, and moderation effect analysis results were assessed.ResultsThe linkage rates for DBDII and DBIII were 71.1% and 99.7%, respectively. Regarding descriptive statistics and group comparison analysis, the difference in effect in most cases was “none” to “very little.” With respect to cervical cancer that had a relatively small sample size, analysis of DBIII resulted in an underestimation of the incidence in the control group and an overestimation of the incidence in the treatment group (hazard ratio [HR] = 2.62 [95% confidence interval (CI): 1.63–4.23] in DBIII vs. 1.80 [95% CI: 1.18–2.73] in DBDII). Regarding prostate cancer, there was a conflicting tendency with the treatment effect being over or underestimated according to the surveillance, epidemiology, and end results summary staging (HR = 2.27 [95% CI: 1.91–2.70] in DBIII vs. 1.92 [95% CI: 1.70–2.17] in DBDII for the localized stage; HR = 1.80 [95% CI: 1.37–2.36] in DBIII vs. 2.05 [95% CI: 1.67–2.52] in DBDII for the regional stage).ConclusionsTo prevent distortion of the analyses results in health and medical research, it is important to check that the patient population and sample size by each factor of interest (FOI) are sufficient when different data are linked using DBDII. In cases involving a rare disease or with a small sample size for FOI, there is a high likelihood that a DII linkage is unavoidable.

Using Palliative Care Needs Rounds in the UK for care home staff and residents: an implementation science study.

Care home residents often lack access to end-of-life care from specialist palliative care providers. Palliative Care Needs Rounds, developed and tested in Australia, is a novel approach to addressing this. To co-design and implement a scalable UK model of Needs Rounds. A pragmatic implementation study using the integrated Promoting Action on Research Implementation in Health Services framework. Implementation was conducted in six case study sites (England, n = 4, and Scotland, n = 2) encompassing specialist palliative care service working with three to six care homes each. Phase 1: interviews (n = 28 care home staff, specialist palliative care staff, relatives, primary care, acute care and allied health practitioners) and four workshops (n = 43 care home staff, clinicians and managers from specialist palliative care teams and patient and public involvement and engagement representatives). Phase 2: interviews (n = 58 care home and specialist palliative care staff); family questionnaire (n = 13 relatives); staff questionnaire (n = 171 care home staff); quality of death/dying questionnaire (n = 81); patient and public involvement and engagement evaluation interviews (n = 11); fidelity assessment (n = 14 Needs Rounds recordings). (1) Monthly hour-long discussions of residents' physical, psychosocial and spiritual needs, alongside case-based learning, (2) clinical work and (3) relative/multidisciplinary team meetings. A programme theory describing what works for whom under what circumstances with UK Needs Rounds. Secondary outcomes focus on health service use and cost effectiveness, quality of death and dying, care home staff confidence and capability, and the use of patient and public involvement and engagement. Semistructured interviews and workshops with key stakeholders from the six sites; capability of adopting a palliative approach, quality of death and dying index, and Canadian Health Care Evaluation Project Lite questionnaires; recordings of Needs Rounds; care home data on resident demographics/health service use; assessments and interventions triggered by Needs Rounds; semistructured interviews with academic and patient and public involvement and engagement members. The programme theory: while care home staff experience workforce challenges such as high turnover, variable skills and confidence, Needs Rounds can provide care home and specialist palliative care staff the opportunity to collaborate during a protected time, to plan for residents' last months of life. Needs Rounds build care home staff confidence and can strengthen relationships and trust, while harnessing services' complementary expertise. Needs Rounds strengthen understandings of dying, symptom management, advance/anticipatory care planning and communication. This can improve resident care, enabling residents to be cared for and die in their preferred place, and may benefit relatives by increasing their confidence in care quality. COVID-19 restricted intervention and data collection. Due to an insufficient sample size, it was not possible to conduct a cost-benefit analysis of Needs Rounds or calculate the treatment effect or family perceptions of care. Our work suggests that Needs Rounds can improve the quality of life and death for care home residents, by enhancing staff skills and confidence, including symptom management, communications with general practitioners and relatives, and strengthen relationships between care home and specialist palliative care staff. Conduct analysis of costs-benefits and treatment effects. Engagement with commissioners and policy-makers could examine integration of Needs Rounds into care homes and primary care across the UK to ensure equitable access to specialist care. This study is registered as ISRCTN15863801. This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR128799) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 19. See the NIHR Funding and Awards website for further award information.

Predicting Benefit From FOLFOXIRI Plus Bevacizumab in Patients With Metastatic Colorectal Cancer.

Patient outcomes may differ from randomized trial averages. We aimed to predict benefit from FOLFOXIRI versus infusional fluorouracil, leucovorin, and oxaliplatin/fluorouracil, leucovorin, and irinotecan (FOLFOX/FOLFIRI), both plus bevacizumab, in patients with metastatic colorectal cancer (mCRC). A Cox model with prespecified clinical, molecular, and laboratory variables was developed in 639 patients from the TRIBE2 trial for predicting 2-year mortality. Data from the CHARTA (n = 232), TRIBE1 (n = 504), and CAIRO5 (liver-only mCRC, n = 287) trials were used for external validation and heterogeneity of treatment effects (HTE) analysis. This involves categorizing patients into risk groups and assessing treatment effects across these groups. Performance was assessed by the C-index and calibration plots. The C-for-benefit was calculated to assess evidence for HTE. The c-for-benefit is specifically designed for HTE analysis. Like the commonly known c-statistic, it summarizes the discrimination of a model. Values over 0.5 indicate evidence for HTE. In TRIBE2, the overoptimism-corrected C-index was 0.66 (95% CI, 0.63 to 0.69). At external validation, the C-index was 0.69 (95% CI, 0.64 to 0.75), 0.68 (95% CI, 0.64 to 0.72), and 0.65 (95% CI, 0.65 to 0.66), in CHARTA, TRIBE1, and CAIRO5, respectively. Calibration plots indicated slight underestimation of mortality. The c-for-benefit indicated evidence for HTE in CHARTA (0.56, 95% CI, 0.48 to 0.65), but not in TRIBE1 (0.49, 95% CI, 0.44 to 0.55) and CAIRO5 (0.40, 95% CI, 0.32 to 0.48). Although 2-year mortality could be reasonably estimated, the HTE analysis showed that clinically available variables did not reliably identify which patients with mCRC benefit from FOLFOXIRI versus FOLFOX/FOLFIRI, both plus bevacizumab, across the three studies.

Effects of electroacupuncture on cognitive symptoms in major depressive disorder: a pilot study and randomized controlled trial

Objectives To investigate the impact of electroacupuncture on cognitive function, quality of life (QoL), and depression severity in patients with major depressive disorder (MDD). Methods This double-blinded randomized controlled trial included 60 participants aged 18-55 with cognitive symptoms related to MDD at Thammasat University Hospital. Participants were divided into two groups: the electroacupuncture group combined with standard antidepressant treatment (EG; n=30) and the control group receiving standard care with placebo acupuncture (CG; n=30). The study assessed 1) executive functions using the Trail making test- B and Stroop Color and Word Test, 2) delayed recall, and 3) subjective cognitive complaint and Quality of life (QoL) using WHODAS 2.0. Depressive symptoms were measured using the Thai version of the Patient Health Questionnaire (PHQ-9). Baseline and post-intervention assessments were conducted over 10 weeks. Mann-Whitney U test analyzed treatment effects by comparing median differences between groups. Results Both groups exhibited similar demographics and cognitive traits. Cognitive improvement was observed in both groups at the endpoint. Intention-to-treat analysis revealed significantly higher median scores for subjective cognitive complaints in the EG compared to the CG (EG: Median = 5.5, CG: Median = 0.0, p=0.049). No serious side effects were identified from either electroacupuncture or placebo acupuncture. Conclusions Electroacupuncture improved subjective complaints in MDD patients with cognitive symptoms, but did not show effects on specific cognitive functions, QoL, or depressive symptoms. This study provides initial evidence supporting the potential of electroacupuncture in MDD patients with cognitive symptoms, suggesting opportunities for further research. Trial registration NCT06239740, February 2, 2024, ClinicalTrials.gov.

The effects of Title IX enforcement on sexual assaults on college campuses

AbstractThis study investigates the impact of U.S. Department of Education's Office of Civil Rights (OCR) investigations, prompted by the “Dear Colleague Letter” (DCL) in 2011, on sexual assaults in educational institutions. While previous research has primarily focused on the effects of OCR investigations on enrollments and reputation, using a potential outcome model (POM) and an event study, we analyze treatment effects across different school types, considering factors like endowments. We find the strongest treatment effect in private baccalaureate schools, underscoring the importance of school‐specific factors in understanding the role played by OCR investigations in addressing sexual assaults on campuses.

Primary care payment models and avoidable hospitalizations in Ontario, Canada: A multivalued treatment effects analysis.

Improving access to primary care physicians' services may help reduce hospitalizations due to Ambulatory Care Sensitive Conditions (ACSCs). Ontario, Canada's most populous province, introduced blended payment models for primary care physicians in the early- to mid-2000s to increase access to primary care, preventive care, and better chronic disease management. We study the impact of payment models on avoidable hospitalizations due to two incentivized ACSCs (diabetes and congestive heart failure) and two non-incentivized ACSCs (angina and asthma). The data for our study came from health administrative data on practicing primary care physicians in Ontario between 2006 and 2015. We employ a two-stage estimation strategy on a balanced panel of 3710 primary care physicians (1158 blended-fee-for-service (FFS), 1388 blended-capitation models, and 1164 interprofessional team-based practices). First, we account for the differences in physician practices using a generalized propensity score based on a multinomial logit regression model, corresponding to three primary care payment models. Second, we use fractional regression models to estimate the average treatment effects on the treated outcome (i.e., avoidable hospitalizations). The capitation-based model sometimes increases avoidable hospitalizations due to angina (by 7 per 100,000 patients) and congestive heart failure (40 per 100,000) relative to the blended-FFS-based model. Switching capitation physicians into interprofessional teams mitigates this effect, reducing avoidable hospitalizations from congestive heart failure by 30 per 100,000 patients and suggesting better access to primary care and chronic disease management in team-based practices.

From data to decision: integrated approach to pavement preservation in Iowa through treatment effectiveness analysis

ABSTRACT This investigation seeks to enhance ‘Iowa's Pavement Preservation Guide’ with a data-informed decision-making framework. Iowa DOT's databases were used as the data source for evaluating pavement performances under different preservation treatment regimens and determining the effectiveness of those strategies. Five preservation treatment methods for flexible and composite pavements, namely, crack sealing-and-filling, microsurfacing, slurry sealing, patching, and thin hot mix asphalt (HMA) overlays were evaluated using historic data from about 7000 road segments between 1998 and 2020. The data included various attributes describing pavement, road, and traffic characteristics required for analysing condition-based performance and treatment impacts. Two key indicators, service life extension (LE) and index benefit (IB), were defined and used to quantify treatment effectiveness in terms of pavement condition improvement and impact on deterioration rate. The treatment-effectiveness indicators were then factored into the cost analyses to assess the cost-effectiveness of preservation strategies. The results of the treatment effectiveness analysis were used to develop decision matrices that provide insights for selecting preservation treatments based on benefit–cost analysis considering both the overall condition and the dominant distress. This approach to treatment effectiveness highlighted the distinction between an optimum pavement preservation strategy and one that targets maximum service life extension.

Analysis of related factors and treatment effect of chylothorax after lung surgery.

Chylothorax is a seldom encountered complication following lung surgery. However, due to the widespread practice of lung surgery, postoperative complications have inevitably arisen. Chylothorax significantly affects a patient's discharge and recovery. This study investigates the risk factors for postoperative chylothorax at our center and analyzes various treatment modalities and prognostic outcomes. A retrospective analysis was conducted on all postoperative lung resections performed between January 2018 to August 2021 that met the inclusion criteria. Inclusion criteria covered patients undergoing various thoracic surgeries for lung conditions, while exclusion criteria included postoperative referrals for surgeries unrelated to lung tumors. Postoperative chylothorax occurred in 42 of 5,706 patients after lung surgery. General information and disease-related data of the chylothorax and control group were analyzed by univariate and multivariate analyses. Multivariate analysis showed that serum albumin before surgery [odds ratio (OR) =0.86, 95% confidence interval (CI): 0.81-0.91, P<0.001], γ-glutamyl transferase level before surgery (after logarithmic transformation, OR =1.01, 95% CI: 1.00-1.01, P=0.01), squamous cell carcinoma (OR =2.77, 95% CI: 1.37-5.6, P=0.008), right mediastinal lymph node dissection (OR =3.15, 95% CI: 1.62-6.14, P<0.001) were independent risk factors for postoperative chylothorax. Among the 42 cases of postoperative chylothorax, 26 patients were improved with conservative treatments, and 6 patients were improved with chemical pleurodesis. Eight patients with postoperative chylothorax underwent thoracoscopic thoracic duct ligation. Three patients experienced severe postoperative complications: one was discharged after prolonged treatment, while the remaining two either succumbed or were discharged against medical advice. The incidence of chylothorax after lung surgery closely correlates with the intraoperative trauma and nutritional status of patients during the perioperative period. The majority of patients with postoperative chylothorax experienced relief through conservative measures, somatostatin administration, and chemical pleurodesis. Nevertheless, substantial postoperative chylothorax necessitated surgical intervention, involving thoracic duct ligation or drug pleurodesis.

Effects of electroacupuncture on cognitive symptoms in major depressive disorder: a pilot study and randomized controlled trial

Objectives To investigate the impact of electroacupuncture on cognitive function, quality of life (QoL), and depression severity in patients with major depressive disorder (MDD). Methods This double-blinded randomized controlled trial included 60 participants aged 18-55 with cognitive symptoms related to MDD at Thammasat University Hospital. Participants were divided into two groups: the electroacupuncture group combined with standard antidepressant treatment (EG; n=30) and the control group receiving standard care with placebo acupuncture (CG; n=30). The study assessed 1) executive functions using the Trail making test- B and Stroop Color and Word Test, 2) delayed recall, and 3) subjective cognitive complaint and Quality of life (QoL) using WHODAS 2.0. Depressive symptoms were measured using the Thai version of the Patient Health Questionnaire (PHQ-9). Baseline and post-intervention assessments were conducted over 10 weeks. Mann-Whitney U test analyzed treatment effects by comparing median differences between groups. Results Both groups exhibited similar demographics and cognitive traits. Cognitive improvement was observed in both groups at the endpoint. Intention-to-treat analysis revealed significantly higher median scores for subjective cognitive complaints in the EG compared to the CG (EG: Median = 5.5, CG: Median = 0.0, p=0.049). No serious side effects were identified from either electroacupuncture or placebo acupuncture. Conclusions Electroacupuncture improved subjective complaints in MDD patients with cognitive symptoms, but did not show effects on specific cognitive functions, QoL, or depressive symptoms. This study provides initial evidence supporting the potential of electroacupuncture in MDD patients with cognitive symptoms, suggesting opportunities for further research. Trial registration NCT06239740, February 2, 2024, ClinicalTrials.gov.

The Effect of an Obesity Prevention Intervention Among Specific Subpopulations: A Heterogeneity of Treatment Effect Analysis of the Greenlight Trial.

Background: Understanding how different populations respond to a childhood obesity intervention could help optimize personalized treatment strategies, especially with the goal to reduce disparities in obesity. Methods: We conducted a secondary analysis of the Greenlight Cluster Randomized Controlled Trial, a health communication focused pediatric obesity prevention trial, to evaluate for heterogeneity of treatment effect (HTE) by child biological sex, caregiver BMI, caregiver reported race and ethnicity, primary language, and health literacy. To examine HTE on BMI z-score from 2 to 24 months of age, we fit linear mixed effects models. Results: We analyzed 802 caregiver-child pairs, of which 52% of children were female, 58% of households reported annual family income of <$20,000, and 83% did not have a college degree. We observed evidence to suggest HTE by primary language (p = 0.047 for Spanish vs. English) and the combination of primary language and health literacy (p = 0.01). There was insufficient evidence to suggest that the Greenlight intervention effect differed by biological sex, caregiver BMI, or by race/ethnicity. Conclusions: This HTE analysis found that the Greenlight obesity prevention intervention had a more beneficial effect on child BMI z-score over 2 years for children of caregivers with limited health literacy and for caregivers for whom Spanish was the primary language.

On the side effects of fiscal policy: Fiscal rules and income inequality

Contributing to an important literature on the side effects of fiscal policy, this paper employs a treatment effect analysis to show that fiscal rules (FR) have significant side effects on income inequality (IQ). Economically meaningful, this favorable causal direct effect is robust to many alternative specifications. Nevertheless, not all FR are alike: balanced budget and debt rules decrease IQ, contrary to expenditure rules that increase it. Finally, the effect of FR on IQ is found to be subject to heterogeneity related to various factors. Given the current upward global IQ trends, our results provide insightful evidence for governments of countries aiming at reducing IQ.

Analysis of sewage treatment process and effect Take Maidao sewage plant in Qingdao as an example

The purpose of this paper is to analyze the current situation of urban sewage treatment, understand the process of sewage treatment, conduct in-depth analysis of it combined with actual cases, and put forward effective suggestions for improvement. Nowadays, with the development of science and technology, many cities have built advanced sewage plants, as an example as Qingdao, which is a serious water shortage city in Shandong Province of China. More specifically, a field interview and a field trip in Mai Dao sewage plant provide the actual treatment process and real data of the plant. It provides with a comprehensive process and actual removal rate of the plant, so we can have a deeper understanding of the current status of urban sewage treatment processes. Additionally, an analysis of the effect of every devices in the process supports the effectiveness of the plant. Furthermore, this paper gives information about current situations of reuse water process and offers some suggestions to the current treatment process and the use of outflow water.

Dynamic fluctuations of salivary CGRP levels during migraine attacks: association with clinical variables and phenotypic characterization

BackgroundMigraine is a complex neurological disorder with significant heterogeneity in its clinical presentation and molecular mechanisms. Calcitonin gene-related peptide (CGRP) has emerged as a key player in migraine pathophysiology, but challenges remain in its utilization as a biomarker. This study aimed to investigate salivary CGRP levels during migraine attacks across the frequency spectrum and explore associations with clinical variables.MethodsA prospective longitudinal pilot study was conducted, recruiting migraine patients from an outpatient headache clinic. Salivary CGRP levels were measured at interictal, onset, post-2 h of onset and end-of-attack. Using generalized linear mixed models, we explored the effect of CGRP changes over the attack in presence of depressive symptoms (DS), acute attack treatment, and after three-months of erenumab treatment. Finally, patients were classified and compared according to their CGRP phenotype.ResultsA total of 44 migraine patients were included (90.9% women), with 80 migraine attacks analyzed. Salivary CGRP levels increased at the onset of migraine attacks. We observed statistically significant interactions between DS and both the linear (Est. [SE]: 19.4 [5.8], p = 0.001) and quadratic terms of time (-19.1 [6.0], p = 0.002). Additionally, a significant three-way interaction within the use of acute treated attack (linear-term: -18.5 [6.2], p = 0.005; quadratic-term: 19.2 [6.8], p = 0.005) was also found. Molecular phenotyping revealed that 72.7% (32/44) of patients presented only CGRP-dependent attacks, while 27.3% (12/44) presented non-CGRP-dependent migraine attacks. Patients with only CGRP-dependent attacks were associated with younger age, shorter disease evolution time, a higher proportion of aura, and fewer monthly headache days (p < 0.05). Exploratory analysis of erenumab treatment effects did not result in changes in CGRP levels during migraine attacks.ConclusionsOur study underscores the dynamic nature of migraine at a molecular level and emphasizes the importance of integrating clinical variables, such as depressive symptoms, in understanding its pathophysiology. The identification of distinct migraine subtypes based on CGRP dependence suggests potential opportunities for personalized treatment approaches.

318 Discovering Subgroups with Supervised Machine Learning Models for Heterogeneity of Treatment Effect Analysis

OBJECTIVES/GOALS: The goal of the study is to provide insights into the use of machine learning methods as a means to predict heterogeneity of treatment effect (HTE) in participants of randomized clinical trials. METHODS/STUDY POPULATION: Using data from 2,441 participants enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) randomized controlled trial of daily low-dose aspirin vs placebo in the United States, we developed multivariable risk prediction models for the composite outcome of dementia, disability, or death. We used two machine learning techniques, decision trees and random forests, to develop novel non-parametric outcomes classifiers and generate risk-based subgroups. The comparator method was an extant semi-parametric proportional hazards predictive risk model. We then assessed HTE by examining the 5-year absolute risk reduction (ARR) of aspirin vs placebo in each risk subgroup. RESULTS/ANTICIPATED RESULTS: In the random forest classifier, the ARR at 5 years in the highest risk quintile was 13.7% (95% CI 3.1% to 24.4%). For the semi-parametric proportional hazards model, the ARR in the highest risk quintile was 15.1% (95% CI 4.0% to 26.3%). These results were comparable and provide evidence of the viability of internally developed parsimonious non-parametric machine learning models for HTE analysis. The decision tree model results (5-year ARR = 17.0%, 95% CI= -5.4% to 39.4% in the highest risk subgroup) exhibited more uncertainty in the results. DISCUSSION/SIGNIFICANCE: None of the models detected significant HTE on the relative scale; there was substantial HTE on the absolute scale in three of the models. Treatment benefit on the absolute scale may be regarded as bearing greater clinical importance and may be present even in the absence of benefit on the relative scale.