Chronic kidney disease (CKD) arises due to uncontrolled hypertension (HTN). HTN significantly increases the risk of complications in vital organs, mainly the kidneys. If hypertensive individuals receive early intervention, the majority of these complications and deaths from CKD can be avoided. Having a clinically applicable tool to predict the future risk of those complications can prevent early disability and premature mortality. However, to this day, there is a lack of a validated risk prediction model specifically designed for CKD of hypertensive patients in Ethiopia. We aimed to develop a risk prediction model for CKD among hypertensive patients at the University of Gondar Comprehensive Specialised Hospital (UoGCSH), Ethiopia.

A retrospective follow-up study was conducted from 1 January 2012 to 30 December 2021. The Least Absolute Shrinkage and Selection Operator regression methods were used to select predictors. The performance of the models was assessed using the Area Under the Curve and calibration plots. The internal validity of the model was evaluated using bootstrapping methods, and the model was presented as a nomogram. Decision curve analysis was conducted to assess the net benefit of the prediction model in clinical and public health contexts.

Data from patients’ medical records were collected via the Kobo Toolbox in the UoGCSH.

We followed a total of 1120 Patients diagnosed with HTN.

The incidence of CKD among adult hypertensive patients was 19.82% (95% CI 17.59% to 22.26%). In the multivariable logistic regression analysis, age, residency, baseline blood pressure status, type of HTN, family history of HTN, baseline serum creatinine levels, proteinuria at baseline and dyslipidaemia were identified as statistically significant predictors of CKD. The nomogram demonstrated a discriminatory power of 91.98% (95% CI 90.09% to 93.88%) and a calibration p value of 0.327. The sensitivity and specificity of the prediction model were 80.63% (95% CI 74.81% to 85.61%) and 87.97% (95% CI 85.66% to 90.03%), respectively. The developed nomogram has a greater net benefit than using the treat-all or treat-none strategies when the threshold probability of the patient is increased.

The nomogram demonstrated excellent discrimination and calibration in identifying hypertensive patients at high risk of CKD. This predictive model offers clinicians a valuable tool for early identification of high-risk individuals, enabling timely interventions, personalised counselling and optimised management through close monitoring to prevent disease progression.

Children from refugee families resettled in the USA face higher risks of serious mental health challenges compared with their native-born peers. Research shows that refugee youth in high-income countries frequently suffer from trauma-associated disorders such as post-traumatic stress disorder (PTSD), depression and anxiety. The high prevalence of trauma-associated mental health problems among these youth may be attributed to their own trauma exposure, especially if born in conflict zones, and post-resettlement challenges like poverty, acculturation difficulties, racism and discrimination. However, they may also suffer from the effects of intergenerational trauma, where parental war trauma impacts them. This study aims to adapt and test an intervention addressing intergenerational trauma-related emotional and behavioural health outcomes among US-born children of refugee parents in Omaha and Lincoln, Nebraska.

This is a two-arm cluster randomised type I hybrid effectiveness-implementation trial. Guided by the Social Action and Family Systems theories and applying them to the intergenerational transmission of trauma framework, the combination intervention consists of family strengthening model delivered through multiple family groups+peer mentoring programme called TeenAge Health Consultants (TAHC) adapted for delivery in virtual environment (Virtual TAHC). A total of 154 US-born adolescents of parent resettled as refugees (77 per study arm), ages 14–17 and at least one biological parent per youth (dyads) will be recruited from four comparable communities utilising community-based participatory research approach and randomised to usual care or intervention group. The intervention will be implemented for up to 16 weeks, with assessments at baseline, after intervention completion and 6 months follow-up. To determine study feasibility, we will use binary metrics of participant enrolment of 70% or more and retention of 80% or more at 12 months. To assess study acceptability, we will determine participant satisfaction with the study based on the Client Satisfaction Questionnaire (CSQ-8). To maximise rigour, our analyses will follow an intention-to-treat (ITT) approach. For primary inferential analyses, we will fit two-level generalised linear mixed models to continuous primary outcomes. The models will include fixed effects for study arm, time and their interaction terms. We will perform time-averaged comparisons of post-baseline repeatedly measured observations across study arms to examine intervention effects over the duration of the postintervention study period. To delineate barriers and facilitators to implementation and implementation strategies, we will apply a more integrative approach, using both inductive and deductive approaches guided by the grounded theory and integrative theory that combines both deductive and inductive approaches. Finally, we will integrate findings from the quantitative and qualitative analysis to provide additional explanation and context for our quantitative findings.

Voluntary written informed assent and consent will be obtained from all participants, adolescents and their parents, respectively. All study procedures received approval from Washington University in St. Louis Institutional Review Board (IRB #202307081).

Study findings will be disseminated through publications in scientific journals and presentations at national and international conferences. We also plan to provide community education about the study through a dissemination conference at the end of the study.

NCT06176638.