Quality of life of pediatric and adult individuals with osteogenesis imperfecta: a meta-analysis

Background Osteogenesis imperfecta (OI) is a group of rare inheritable disorders of connective tissue. The cardinal manifestations of OI are low bone mass and reduced bone mineral strength, leading to increased bone fragility and deformity that may lead to significant impairment in daily life. The phenotypic manifestations show a broad range of severity, ranging from mild or moderate to severe and lethal. The here presented meta-analysis aimed to analyze existing findings on quality of life (QoL) in children and adults with OI. Methods Nine databases were searched with predefined key words. The selection process was executed by two independent reviewers and was based on predetermined exclusion and inclusion criteria. The quality of each study was assessed using a risk of bias tool. Effect sizes were calculated as standardized mean differences. Between-study heterogeneity was calculated with the I$^{2}$ statistic. Results Among the studies included two featured children and adolescents (N = 189), and four adults (N = 760). Children with OI had significantly lower QoL on the Pediatric quality of life inventory (PedsQL) with regards to the total score, emotional, school, and social functioning compared to controls and norms. The data was not sufficient to calculate differences regarding OI-subtypes. In the adult sample assessed with Short Form Health Survey Questionnaire, 12 (SF-12) and 36 items (SF-36), all OI types showed significantly lower QoL levels across all physical component subscales compared to norms. The same pattern was found for the mental component subscales namely vitality, social functioning, and emotional role functioning. The mental health subscale was significantly lower for OI type I, but not for type III and IV. All of the included studies exhibited a low risk of bias. Conclusions QoL was significantly lower in children and adults with OI compared to norms and controls. Studies in adults comparing OI subtypes showed that the clinical severity of the phenotype is not related to worse mental health QoL. Future research is needed to examine QoL in children and adolescents in more sophisticated ways and to better understand the association between clinical severity of an OI-phenotype/severity and mental health in adults

Psychometric Evaluation of the German Version of the Perceived Access to Healthcare Questionnaire in a Sample of Individuals with Rare Chronic Diseases

Access to healthcare is multifaceted and poses significant challenges for individuals with chronic and rare diseases (RDs). This study aimed to conduct a psychometric evaluation of the German version of the Perception of Access to Healthcare Questionnaire (PAHQ) among individuals with RDs. We conducted an evaluation of the PAHQ using a sample of 271 adults with an RD diagnosis. The 31-item instrument underwent evaluation including a comparison of three different confirmatory factor models (CFA). Subsequent steps involved item removal, reliability analysis (computation of Cronbach’s alpha), and analysis of criterion-related validity. The six-factor model showed the best fit to the data and was selected for further examination. Subsequently, six items were removed. Fit indices for the final model were acceptable. Cronbach’s alpha ranged from 0.75 to 0.91 for the six subscales, except for the availability subscale which exhibited the lowest value (0.64). In terms of criterion-related validity, different skills relating to the navigation of access dimensions were significantly correlated with corresponding PAHQ subscales, thus confirming validity. The capacity of the PAHQ to guide targeted interventions and facilitate cross-population comparisons positions it as a valuable instrument for advancing healthcare access research and promoting equitable access to care, particularly for individuals with rare and chronic diseases

Biochemical, Nutritional, and Clinical Parameters of Vitamin B12 Deficiency in Infants: A Systematic Review and Analysis of 292 Cases Published between 1962 and 2022

Pooled data from published reports on infants with clinically diagnosed vitamin B12 (B12) deficiency were analyzed with the purpose of describing the presentation, diagnostic approaches, and risk factors for the condition to inform prevention strategies. An electronic (PubMed database) and manual literature search following the PRISMA approach was conducted (preregistration with the Open Science Framework, accessed on 15 February 2023). Data were described and analyzed using correlation analyses, Chi-square tests, ANOVAs, and regression analyses, and 102 publications (292 cases) were analyzed. The mean age at first symptoms (anemia, various neurological symptoms) was four months; the mean time to diagnosis was 2.6 months. Maternal B12 at diagnosis, exclusive breastfeeding, and a maternal diet low in B12 predicted infant B12, methylmalonic acid, and total homocysteine. Infant B12 deficiency is still not easily diagnosed. Methylmalonic acid and total homocysteine are useful diagnostic parameters in addition to B12 levels. Since maternal B12 status predicts infant B12 status, it would probably be advantageous to target women in early pregnancy or even preconceptionally to prevent infant B12 deficiency, rather than to rely on newborn screening that often does not reliably identify high-risk children

Biochemical, Nutritional, and Clinical Parameters of Vitamin B12 Deficiency in Infants: A Systematic Review and Analysis of 292 Cases Published between 1962 and 2022

Pooled data from published reports on infants with clinically diagnosed vitamin B12 (B12) deficiency were analyzed with the purpose of describing the presentation, diagnostic approaches, and risk factors for the condition to inform prevention strategies. An electronic (PubMed database) and manual literature search following the PRISMA approach was conducted (preregistration with the Open Science Framework, accessed on 15 February 2023). Data were described and analyzed using correlation analyses, Chi-square tests, ANOVAs, and regression analyses, and 102 publications (292 cases) were analyzed. The mean age at first symptoms (anemia, various neurological symptoms) was four months; the mean time to diagnosis was 2.6 months. Maternal B12 at diagnosis, exclusive breastfeeding, and a maternal diet low in B12 predicted infant B12, methylmalonic acid, and total homocysteine. Infant B12 deficiency is still not easily diagnosed. Methylmalonic acid and total homocysteine are useful diagnostic parameters in addition to B12 levels. Since maternal B12 status predicts infant B12 status, it would probably be advantageous to target women in early pregnancy or even preconceptionally to prevent infant B12 deficiency, rather than to rely on newborn screening that often does not reliably identify high-risk children

Depressive symptoms are negatively associated with hair N-arachidonoylethanolamine (anandamide) levels: A cross-lagged panel analysis of four annual assessment waves examining hair endocannabinoids and cortisol

Background The endocannabinoid system (ECS) is increasingly being recognized as key regulatory system coupled with the glucocorticoid system implicated in the pathophysiology of major depressive disorder (MDD). However, prior studies examining the ECS in MDD have been inconclusive, of small sample size or of cross-sectional nature limiting interpretation of causal inferences or time-dependent effects. Methods In a prospective community-based cohort study including 128 individuals (women: 108), depressive symptoms (PHQ-9) as well as hair cortisol and endocannabinoids were measured annually over four years (T1-T4). Cortisol, N-arachidonoylethanolamine (AEA), and 2-arachidonoyl-sn-glycerol/1-arachidonoyl-sn-glycerol (2-AG/1-AG) were extracted from 3 cm hair segments reflecting cumulative concentrations of the last three months prior sampling. Results Cross-sectional group comparisons at baseline revealed reduced AEA and cortisol levels in the group with a positive MDD screening compared to individuals with low depressive symptomatology (both p < .05). Cross-lagged panel models showed that AEA levels at T2 were negatively associated with depressive symptoms at T3 (p < .05). Also, depressive symptoms at T3 were negatively associated with AEA levels at T4 (p < .01). The direction of association was reversed for 2-AG/1-AG, as 2-AG/1-AG levels at T1 were positively associated with depressive symptoms at T2 (p < .01). Conclusions While cross-sectional analyses suggest higher depressive symptomatology to be associated with reduced AEA and cortisol release, longitudinal analyses reveal that primarily AEA levels are negatively associated with depressive symptoms. These longitudinal associations elucidate time-dependent relationships between depressive symptomatology and the ECS and further highlight AEA as potential treatment target in MDD

Development and validation of a multivariable risk score for prolonged length of stay in the surgical intensive care unit

BACKGROUND: Chronically critical illness is highly relevant in intensive care units, but the definitions in literature vary greatly. The timely detection of prolonged intensive care unit length of stay could support care planning for chronically critical ill patients.AIM: To develop and validate a risk score for predicting prolonged length of stay in the surgical intensive care unit.METHODS: This single centre cohort study formed part of a nursing-led project in one surgical intensive care unit. We examined the performance of seven predefined predictive factors of prolonged (&gt;20 days) intensive care unit length of stay in adults on the seventh day of stay in intensive care to develop (n = 304) and validate (n = 101) a risk score. Candidate variables (Charlson Comorbidity Index, Simplified Acute Physiology Score II, minimum plasma albumin, need for anti-infective drugs, time of mechanical ventilation, main feeding method and score on the Sedation-Agitation Scale) were analysed using multiple logistical regression analysis.RESULTS: Our risk score assigned different points to the following conditions: Charlson Comorbidity Index &gt;2, minimum albumin &lt;20 g/l between days 1 and 7, mechanical ventilation &gt;14 hr on day 7 and the need for parenteral nutrition on day 7. For a validation data set (n = 101), the area under the receiver operating characteristic curve was 0.89 (95% confidence interval 0.77­0.87). At a cut-off value of 100 points, the degree of sensitivity was 88%, the specificity 75%, the positive predictive value 53%, the negative predictive value 95%, and the model fit R2 0.40.CONCLUSIONS: Our model allowed the timely detection of prolonged intensive care unit length of stay with four candidate predictive factors. The timely identification of patients with prolonged intensive care unit length of stay is possible and could influence the person-centred prevention of chronically critical illness and adequate resource allocation. (Trial registration no DRKS 00017073)

Lipidomics in Major Depressive Disorder

Omic sciences coupled with novel computational approaches such as machine intelligence offer completely new approaches to major depressive disorder (MDD) research. The complexity of MDD's pathophysiology is being integrated into studies examining MDD's biology within the omic fields. Lipidomics, as a late-comer among other omic fields, is increasingly being recognized in psychiatric research because it has allowed the investigation of global lipid perturbations in patients suffering from MDD and indicated a crucial role of specific patterns of lipid alterations in the development and progression of MDD. Combinatorial lipid-markers with high classification power are being developed in order to assist MDD diagnosis, while rodent models of depression reveal lipidome changes and thereby unveil novel treatment targets for depression. In this systematic review, we provide an overview of current breakthroughs and future trends in the field of lipidomics in MDD research and thereby paving the way for precision medicine in MDD

Machine learning based outcome prediction in stroke patients with MCA‐M1 occlusions and early thrombectomy

Background Clinical outcome varies substantially between individuals with large vessel occlusion (LVO) stroke. A small infarct core and large mismatch were found to be associated with good recovery. We investigated if those imaging variables improve individual prediction of functional outcome after early (< 6h) endovascular treatment (EVT) in LVO stroke. Methods We included 222 patients with acute ischemic stroke due to middle cerebral artery (MCA)‐M1 occlusion who received EVT. As predictors, we used clinical variables and region of interest (ROI) based magnetic resonance imaging (MRI) features. We developed different machine learning models and quantified their prediction performance by the area under the curve (AUC) of receiver operator characteristics (ROC) curves and the Brier score. Results Successful recanalization rate was 78%, with 54% patients having a favorable outcome (modified Rankin scale, mRS 0‐2). Small infarct core was associated with favorable functional outcome. Outcome prediction improved only slightly when imaging was added to patient variables. Age was the driving factor, with a sharp decrease of likelihood for favorable functional outcome beyond 78 years of age. Conclusions In patients with MCA‐M1 occlusion strokes referred to EVT within 6 hours of symptom onset, infarct core volume was associated with outcome. However, ROI based imaging parameters led to no significant improvement in outcome prediction on individual patient level when added to a set of clinical predictors. Our study is in concordance with the current practice, where mismatch imaging or collateral readouts are not recommended for excluding patients with MCA‐M1 occlusion for early EVT