39 research outputs found
Unraveling reactionary care: the experience of mother-caregivers of adults with severe mental disorders in Catalonia
In most Mediterranean countries, people diagnosed with severe mental disorders (SMDs) are typically cared for by the mother, causing a significant burden on people in this family role. Based on a broader mental health participatory action and qualitative research carried out in Catalonia (Spain) of 12 in-depth interviews and 3 focus groups, this article analyses the mother-caregivers' experience in the domestic space. The results show that patients and caregivers are engaged in a relationship of 'nested dependencies', which create social isolation. This produces the conditions of 'reactionary care', practices that limit the autonomy of those affected and that reproduce forms of disciplinary psychiatric institutions. We conclude that both institutional violence derived from economic rationality and that which stems from the gender mandate feed off each other into the domestic sphere. This research argues for placing care at the center of clinical practice and shows the need to consider the structural forces shaping it
The collaborative management of antipsychotic medication and its obstacles: A qualitative study
Antipsychotic medication is the primary treatment for psychotic conditions such as schizophrenia and schizoaffective disorders; nevertheless, its administration is not free from conflicts. Despite taking their medication regularly, 25-50% of patients report no benefits or perceive this type of treatment as an imposition. Following in the footsteps of a previous initiative in Quebec (Canada), the Gestion Autonome de la Médication en Santé Mentale (GAM), this article ethnographically analyses the main obstacles to the collaborative management of antipsychotics in Catalonia (Spain) as a previous step for the implementation of this initiative in the Catalan mental healthcare network. We conducted in-depth interviews with patients (38), family caregivers (18) and mental health professionals (19), as well as ten focus groups, in two public mental health services, and patients' and caregivers' associations. Data were collected between February and December 2018. We detected three main obstacles to collaboration among participants. First, different understanding of the patient's distress, either as deriving from the symptoms of the disorder (professionals) or the adverse effects of the medication (patients). Second, differences in the definition of (un)awareness of the disorder. Whereas professionals associated disorder awareness with treatment compliance, caregivers understood it as synonymous with self-care, and among patients 'awareness of suffering' emerged as a comprehensive category of a set of discomforts (i.e., symptoms, adverse effects of medication, previous admissions, stigma). Third, discordant expectations regarding clinical communication that can be condensed in the differences in meaning between the Spanish words 'trato' and 'tratamiento', where the first denotes having a pleasant manner and agreement, and the second handling and management. We conclude that these three obstacles pave the way for coercive practices and promote patients' de-subjectivation, named here as the 'total patient' effect. This study is the first GAM initiative in Europe
Seven microaneurysms: Description of an experimental rodent model for neurovascular training
AIM: To demonstrate the microsurgical procedures, and to evaluate the feasibility of living models of experimental neurovascular
training by developing new complex vascular exercises mimicking the most common intracranial aneurysms.
MATERIAL and METHODS: The procedures were performed under a Zeiss (OPMI pico f170) microscope using basic microsurgery
instruments, 10/0 Nylon and blue Polypropylene micro-sutures. We selected adult albino Wistar rats weighing between 258 and
471g each. Seven different aneurysm types were created using carotid, jugular, cava, aorta and femoral vessels.
RESULTS: Seven types of aneurysm were designed and created in the rat with a high-medium successful rate. There are differences
in terms of realism and the difficulty of performance, according to the different types: lateral wall, bifurcation, top of the basilar,
fusiform, fusiform + involved branch, Anterior Communicating Artery (ACoA) and giant. The steps and technical issues to produce
these exercises are described.
CONCLUSION: We show the feasibility of creating several types of aneurysm using different vessels in a rodent model. Training on
these models help to improve microsurgical skills, allowing safe practice for neurosurgeons in all stages of their caree
Serum amyloid a1/toll-like receptor-4 Axis, an important link between inflammation and outcome of TBI patients
Traumatic brain injury (TBI) is one of the leading causes of mortality and disability world-wide without any validated biomarker or set of biomarkers to help the diagnosis and evaluation of the evolution/prognosis of TBI patients. To achieve this aim, a deeper knowledge of the biochemical and pathophysiological processes triggered after the trauma is essential. Here, we identified the serum amyloid A1 protein-Toll-like receptor 4 (SAA1-TLR4) axis as an important link between inflammation and the outcome of TBI patients. Using serum and mRNA from white blood cells (WBC) of TBI patients, we found a positive correlation between serum SAA1 levels and injury severity, as well as with the 6-month outcome of TBI patients. SAA1 levels also correlate with the presence of TLR4 mRNA in WBC. In vitro, we found that SAA1 contributes to inflammation via TLR4 activation that releases inflammatory cytokines, which in turn increases SAA1 levels, establishing a positive proinflammatory loop. In vivo, post-TBI treatment with the TLR4-antagonist TAK242 reduces SAA1 levels, improves neurobehavioral outcome, and prevents blood–brain barrier disruption. Our data support further evaluation of (i) post-TBI treatment in the presence of TLR4 inhibition for limiting TBI-induced damage and (ii) SAA1-TLR4 as a biomarker of injury progression in TBI patientsThis work was supported by grants from Fundación Mutua Madrileña and Fondo de
Investigaciones Sanitarias (FIS) (ISCIII/FEDER) (Programa Miguel Servet CP14/00008; CPII19/00005;
PI16/00735; PI19/00082) to JE, RYC2019-026870-I to JMR and PI18/01387 to A
A genome-wide association study follow-up suggests a possible role for PPARG in systemic sclerosis susceptibility
Introduction:
A recent genome-wide association study (GWAS) comprising a French cohort of systemic sclerosis (SSc) reported several non-HLA single-nucleotide polymorphisms (SNPs) showing a nominal association in the discovery phase. We aimed to identify previously overlooked susceptibility variants by using a follow-up strategy.<p></p>
Methods:
Sixty-six non-HLA SNPs showing a P value <10-4 in the discovery phase of the French SSc GWAS were analyzed in the first step of this study, performing a meta-analysis that combined data from the two published SSc GWASs. A total of 2,921 SSc patients and 6,963 healthy controls were included in this first phase. Two SNPs, PPARG rs310746 and CHRNA9 rs6832151, were selected for genotyping in the replication cohort (1,068 SSc patients and 6,762 healthy controls) based on the results of the first step. Genotyping was performed by using TaqMan SNP genotyping assays.
Results:
We observed nominal associations for both PPARG rs310746 (PMH = 1.90 × 10-6, OR, 1.28) and CHRNA9 rs6832151 (PMH = 4.30 × 10-6, OR, 1.17) genetic variants with SSc in the first step of our study. In the replication phase, we observed a trend of association for PPARG rs310746 (P value = 0.066; OR, 1.17). The combined overall Mantel-Haenszel meta-analysis of all the cohorts included in the present study revealed that PPARG rs310746 remained associated with SSc with a nominal non-genome-wide significant P value (PMH = 5.00 × 10-7; OR, 1.25). No evidence of association was observed for CHRNA9 rs6832151 either in the replication phase or in the overall pooled analysis.<p></p>
Conclusion:
Our results suggest a role of PPARG gene in the development of SSc
Cross-disease Meta-analysis of Genome-wide Association Studies for Systemic Sclerosis and Rheumatoid Arthritis Reveals IRF4 as a New Common Susceptibility Locus
Objectives: Systemic sclerosis (SSc) and rheumatoid arthritis (RA) are autoimmune diseases that share clinical and immunological characteristics. To date, several shared SSc- RA loci have been identified independently. In this study, we aimed to systematically search for new common SSc-RA loci through an inter-disease meta-GWAS strategy. Methods: We performed a meta-analysis combining GWAS datasets of SSc and RA using a strategy that allowed identification of loci with both same-direction and opposingdirection allelic effects. The top single-nucleotide polymorphisms (SNPs) were followed-up in independent SSc and RA case-control cohorts. This allowed us to increase the sample size to a total of 8,830 SSc patients, 16,870 RA patients and 43,393 controls. Results: The cross-disease meta-analysis of the GWAS datasets identified several loci with nominal association signals (P-value < 5 x 10-6), which also showed evidence of association in the disease-specific GWAS scan. These loci included several genomic regions not previously reported as shared loci, besides risk factors associated with both diseases in previous studies. The follow-up of the putatively new SSc-RA loci identified IRF4 as a shared risk factor for these two diseases (Pcombined = 3.29 x 10-12). In addition, the analysis of the biological relevance of the known SSc-RA shared loci pointed to the type I interferon and the interleukin 12 signaling pathways as the main common etiopathogenic factors. Conclusions: Our study has identified a novel shared locus, IRF4, for SSc and RA and highlighted the usefulness of cross-disease GWAS meta-analysis in the identification of common risk loci
Analysis of the common genetic component of large-vessel vasculitides through a meta- Immunochip strategy
Giant cell arteritis (GCA) and Takayasu's arteritis (TAK) are major forms of large-vessel vasculitis (LVV) that share clinical features. To evaluate their genetic similarities, we analysed Immunochip genotyping data from 1,434 LVV patients and 3,814 unaffected controls. Genetic pleiotropy was also estimated. The HLA region harboured the main disease-specific associations. GCA was mostly associated with class II genes (HLA-DRB1/HLA-DQA1) whereas TAK was mostly associated with class I genes (HLA-B/MICA). Both the statistical significance and effect size of the HLA signals were considerably reduced in the cross-disease meta-analysis in comparison with the analysis of GCA and TAK separately. Consequently, no significant genetic correlation between these two diseases was observed when HLA variants were tested. Outside the HLA region, only one polymorphism located nearby the IL12B gene surpassed the study-wide significance threshold in the meta-analysis of the discovery datasets (rs755374, P?=?7.54E-07; ORGCA?=?1.19, ORTAK?=?1.50). This marker was confirmed as novel GCA risk factor using four additional cohorts (PGCA?=?5.52E-04, ORGCA?=?1.16). Taken together, our results provide evidence of strong genetic differences between GCA and TAK in the HLA. Outside this region, common susceptibility factors were suggested, especially within the IL12B locus
A Large-Scale Genetic Analysis Reveals a Strong Contribution of the HLA Class II Region to Giant Cell Arteritis Susceptibility
We conducted a large-scale genetic analysis on giant cell arteritis (GCA), a polygenic immune-mediated vasculitis. A case-control cohort, comprising 1,651 case subjects with GCA and 15,306 unrelated control subjects from six different countries of European ancestry, was genotyped by the Immunochip array. We also imputed HLA data with a previously validated imputation method to perform a more comprehensive analysis of this genomic region. The strongest association signals were observed in the HLA region, with rs477515 representing the highest peak (p = 4.05 × 10−40, OR = 1.73). A multivariate model including class II amino acids of HLA-DRβ1 and HLA-DQα1 and one class I amino acid of HLA-B explained most of the HLA association with GCA, consistent with previously reported associations of classical HLA alleles like HLA-DRB1∗04. An omnibus test on polymorphic amino acid positions highlighted DRβ1 13 (p = 4.08 × 10−43) and HLA-DQα1 47 (p = 4.02 × 10−46), 56, and 76 (both p = 1.84 × 10−45) as relevant positions for disease susceptibility. Outside the HLA region, the most significant loci included PTPN22 (rs2476601, p = 1.73 × 10−6, OR = 1.38), LRRC32 (rs10160518, p = 4.39 × 10−6, OR = 1.20), and REL (rs115674477, p = 1.10 × 10−5, OR = 1.63). Our study provides evidence of a strong contribution of HLA class I and II molecules to susceptibility to GCA. In the non-HLA region, we confirmed a key role for the functional PTPN22 rs2476601 variant and proposed other putative risk loci for GCA involved in Th1, Th17, and Treg cell function
Development of Machine Learning-Based Predictor Algorithm for Conversion of an Ommaya Reservoir to a Permanent Cerebrospinal Fluid Shunt in Preterm Posthemorrhagic Hydrocephalus.
BACKGROUND: An Ommaya reservoir can be used to treat posthemorrhagic hydrocephalus secondary to intraventricular hemorrhage of prematurity until an acceptable weight can be obtained to place a permanent shunt. Identifying newborns at higher risk of developing shunt conversion may improve the management of these patients. This study aimed to develop a predictive algorithm for conversion of an Ommaya reservoir to a permanent shunt using artificial intelligence techniques and classical statistics.
METHODS: A database of 43 preterm patients weighing ≤1500 g with posthemorrhagic hydrocephalus (Papile grades III and IV with Levene ventricular index \u3e4 mm above the 97th percentile) managed with an Ommaya reservoir at our institution between 2002 and 2017 was used to train a k-nearest neighbor algorithm. Validation of results was done with cross-validation technique. Three scenarios were calculated: 1) considering all features regardless whether or not they are correlated with the output variable; 2) considering the features as predictors if they have a correlation \u3e30% with the output variable; 3) considering the output of the previous analysis.
RESULTS: When considering the outputs of a previous multivariate analysis, the algorithm reached 86% of cross-validation accuracy.
CONCLUSIONS: The use of machine learning-based algorithms can help in early identification of patients with permanent need of a shunt. We present a predictive algorithm for a permanent shunt with an accuracy of 86%; accuracy of the algorithm can be improved with larger volume of data and previous analysis