The complex care of a torture survivor in the United States: The case of “Joshua”

Introduction: Torture is an assault on the physical and mental health of an individual, impacting the lives of survivors and their families.The survivor’s interpersonal relationships, social life, and vocational functioning may be affected, and spiritual and other existential questions may intrude. Cultural and historical context will shape the meaning of torture experiences and the aftermath. To effectively treat torture survivors, providers must understand and address these factors. The Complex Care Model (CCM) aims to transform daily care for those with chronic illnesses and improve health outcomes through effective team care. Methods: We conduct a literature review of the CCM and present an adapted Complex Care Approach (CCA) that draws on the Harvard Program in RefugeeTrauma’s five-domain model covering the Trauma Story, Bio-medical, Psychological, Social, and Spiritual domains.We apply the CCA to the case of “Joshua,” a former tortured child soldier, and discuss the diagnosis and treatment across the five domains of care. Findings: The CCA is described as an effective approach for working with torture survivors. We articulate how a CCA can be adapted to the unique historical and cultural contexts experienced by torture survivors and how its five domains serve to integrate the approach to diagnosis and treatment. The benefits of communication and coordination of care among treatment providers is emphasized. Discussion / Conclusions: Torture survivors’ needs are well suited to the application of a CCA delivered by a team of providers who effectively communicate and integrate care holistically across all domains of the survivor’s life

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Provision of surgical care in Ethiopia: Challenges and solutions

With the lowest measured rate of surgery in the world, Ethiopia is faced with a number of challenges in providing surgical care. The aim of this study was to elucidate challenges in providing safe surgical care in Ethiopia, and solutions providers have created to overcome them. Semi-structured interviews were conducted with 10 practicing surgeons in Ethiopia. Following de-identification and immersion into field notes, topical coding was completed with an existing coding manual. Codes were adapted and expanded as necessary, and the primary data analyst confirmed reproducibility with a secondary analyst. Qualitative analysis revealed topics in access to care, in-hospital care delivery, and health policy. Patient financial constraints were identified as a challenge to accessing care. Surgeons were overwhelmed by patient volume and frustrated by lack of material resources and equipment. Numerous surgeons commented on the inadequacy of training and felt that medical education is not a government priority. They reported an insufficient number of anaesthesiologists, nurses, and support staff. Perceived inadequate financial compensation and high workload led to low morale among surgeons. Our study describes specific challenges surgeons encounter in Ethiopia and demonstrates the need for prioritisation of surgical care in the Ethiopian health agenda. Abbreviations: LCoGS: The Lancet Commission on Global Surgery; LMIC: low- and middle-income countr

The rapid scale up of medical education in Ethiopia: Medical student experiences and the role of e-learning at Addis Ababa University.

BackgroundIn response to a physician shortage in Ethiopia, the number of medical students admitted to public universities was rapidly increased through a "flooding" policy.ObjectivesTo assess medical student perceptions on the impact of the "flooding" policy on medical education and e-learning initiatives, as well as plans for future emigration.DesignA cross-sectional survey of medical students at AAU was implemented in 2014. Attitude and practice items were assessed using a Likert scale. Logistic regression analysis was performed to identify characteristics associated with an interest in future emigration.Results673 (99.6%) of 676 students approached completed the survey, representing 39.5% of all 1705 medical students enrolled at AAU in 2014. Most students felt the "flooding" policy had a negative impact on their medical education and >90% felt there was not adequate infrastructure to support the increased student body. E-learning activities to accommodate increased class size included distribution of electronic tablets, but at the time of the survey only 34.8% of students still had a working tablet and 82.3% reported problems with internet connectivity. Most preclinical students (85.1%) who had attended live-streamed lectures preferred traditional classroom lectures. Half of the students (49.5%) intended to practice medicine in Ethiopia. Independent risk factors for planning to emigrate included age ConclusionsThe "flooding" policy lead to significant educational challenges that were not fully alleviated by e-learning initiatives. Concomitant increases in resources for infrastructure development and faculty expansion are needed to maintain quality medical education. Additional research is needed on factors that influence medical graduates decision to emigrate

Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids

Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering similar to 2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids