Psoriatic arthritis (PsA) has a strong genetic component, and the identification of genetic risk factors could help identify the ~30% of psoriasis patients at high risk of developing PsA. Our objectives were to identify genetic risk factors and pathways that differentiate PsA from cutaneous‐only psoriasis (PsC) and to evaluate the performance of PsA risk prediction models.2SNP) and biologic pathways that differentiate PsA from PsC were identified using Priority Index software. The generalizability of previously published PsA risk prediction pipelines was explored, and a risk prediction model was developed with external validation.Genome‐wide meta‐analyses were conducted separately for 5,065 patients with PsA and 21,286 healthy controls and separately for 4,340 patients with PsA and 6,431 patients with PsC. The heritability of PsA was calculated as a single‐nucleotide polymorphism (SNP)–based heritability estimate (hP = 1.61 × 10−9), and key pathways that differentiate PsA from PsC, including NF‐κB signaling (adjusted P = 1.4 × 10−45) and Wnt signaling (adjusted P = 9.5 × 10−58). The heritability of PsA in this cohort was found to be moderate (h2SNP = 0.63), which was similar to the heritability of PsC (h2SNP = 0.61). We observed modest performance of published classification pipelines (maximum area under the curve 0.61), with similar performance of a risk model derived using the current data.We identified a novel genome‐wide significant susceptibility locus for the development of PsA on chromosome 22q11 (rs5754467; Key biologic pathways associated with the development of PsA were identified, but the investigation of risk classification revealed modest utility in the available data sets, possibly because many of the PsC patients included in the present study were receiving treatments that are also effective in PsA. Future predictive models of PsA should be tested in PsC patients recruited from primary care. Psoriatic arthritis (PsA) is a chronic inflammatory condition characterized by the presence of peripheral arthritis, dactylitis, enthesitis, and axial spondyloarthritis . PsA affIL23R gene, and the current aim is to translate these genetic discoveries into improved clinical outcomes  registry, and from Australia. Patients recruited in Manchester were diagnosed by a rheumatologist based on the presence of both psoriasis and inflammatory peripheral arthritis, regardless of rheumatoid factor status. While the majority of patients satisfied the CASPAR (Classification of Psoriatic Arthritis) classification system , some weArthritis & Rheumatology website at http://onlinelibrary.wiley.com/doi/10.1002/art.42154).A total of 283 patients with PsA were recruited from St. Vincent's University Hospital observational PsA cohort. All patients met the CASPAR criteria. The study protocol received approval from the local ethics committee of St. Vincent's University Hospital. Written informed consent was obtained from all patients. In addition, a total of 272 patients with PsA were recruited from the prospective SCQM registry in which diagnosis was based on the CASPAR criteria. The study protocol received approval from the local ethics committee of the University Hospital of Geneva (protocol no. 10‐089) and the SCQM Biobank Scientific Advisory Board and followed the Guidelines for Good Clinical Practice. Written informed consent was obtained from all patients. A summary of available clinical phenotype data for this cohort is given in Supplementary Table http://onlinelibrary.wiley.com/doi/10.1002/art.42154) and had been participants in the British Association of Dermatologists Biologic and Immunomodulators Register (BADBIR) study for ~7 years  described previously . Analysihttps://www.understandingsociety.ac.uk/), accessed through the European Genotype‐phenome Archive. Samples were genotyped at the Wellcome Trust Sanger Institute using the Illumina Infinium CoreExome genotyping array. The quality control procedures applied to genotyping of control samples were consistent with those described below for patient samples.As controls, genotype data were available for 9,965 general population subjects from the UK Household Longitudinal Study (http://onlinelibrary.wiley.com/doi/10.1002/art.42154).PsA samples were genotyped using the Illumina Infinium CoreExome genotyping array. This was performed in accordance with the manufacturer's instructions where genotype calling was performed using the GenCall algorithm in the GenomeStudio Data Analysis software platform (Genotyping Module version 1.8.4). Psoriasis samples were genotyped using the Illumina HumanOmniExpressExome‐8v1‐2_A array performed at King's College London with quality control as previously described . The 3 dhttps://www.well.ox.ac.uk/~wrayner/tools/). Imputation was performed using the Michigan Imputation server in which phasing was performed with Shapeit2 and imputation was performed with the HRC panel. Following imputation, SNPs were excluded based on a minor allele frequency (MAF) of <0.01 and imputation accuracy of r2 <0.5.Imputation was performed for the combined data set of PsA, PsC, and control samples described above. Prior to imputation, SNPs with ambiguous alleles (C/G and A/T) were excluded, and remaining SNPs were aligned to the Haplotype Reference Consortium (HRC) panel (version 1.1) using the HRC imputation preparation tool (We accessed imputed genotype data from the UK Biobank (application number 799) for self‐reported outcomes in 731 PsA patients and 3,197 psoriasis patients . ControlGenotype data were available for 1,962 PsA patients and 8,923 controls  . Sample gc) inflation factor, corrected for sample size (λgc1000), was calculated to test for inflation of test statistics attributable to population stratification, and potential inflation of test statistics from other sources. An overview of these analyses is available in Supplementary Figure http://onlinelibrary.wiley.com/doi/10.1002/art.42154).Case–control association analyses were performed with the SNPTEST software package (version 2.5.2) using their scoring method to account for imputation uncertainty. Meta‐analyses were conducted using an inverse variance meta‐analysis assuming fixed effects with version 2.2.2 of the software package Genome‐Wide Association Meta‐Analysis (GWAMA) . Lambda Heritability of PsA and PsC was estimated in the PsA‐BSTOP GWAS data set using genome‐wide complex trait analysis (GCTA software). SNPs were stratified into quartiles based on levels of linkage disequilibrium, and then further stratified into bins according to MAF values . Calculations were performed with no prevalence specified and with a specified disease prevalence of 1% for comparison with previously reported estimates . Both caWe prioritized key genes and pathways for psoriatic disease using the priority index (Pi) pipeline . Genes whttp://onlinelibrary.wiley.com/doi/10.1002/art.42154). The models were internally validated using k‐fold cross‐validation and were trained using the Machine Learning in R (MLR) package .A recent publication reported the performance of an analysis pipeline based on multiple machine learning approaches for the classification of PsA in patients with psoriasis, referred to hereafter as the Michigan classification pipeline . Based ohttp://onlinelibrary.wiley.com/doi/10.1002/art.42154). We utilized a lasso‐penalized linear regression model using all post–quality control imputed SNPs where the penalty (L1) was tuned with 10 repetitions of 10‐fold cross‐validation implemented in the SparSNP software package  of PsA in the PsA‐BSTOP GWAS data set of 3,609 patients and 9,192 controls. The estimated heritability of PsA in the full data set was h2SNP = 0.63 (SD 0.04), while in analyses using non‐MHC SNPs, the estimated heritability was h2SNP = 0.61 (SD 0.04).We calculated the SNP‐based heritability (h2SNP = 0.43 (SD 0.03), while the heritability of PsA in analyses using non‐MHC SNPs was h2SNP = 0.41 (SD 0.03).In analyses in which the disease prevalence was specified to be 1% , the estimated heritability of PsA was h2SNP = 0.61 (SD 0.05), while in analyses using non‐MHC SNPs, the estimated heritability of PsC was h2SNP = 0.59 (SD 0.05). With a disease prevalence of 1%, the estimated heritability of PsC was found to be h2SNP = 0.56 (SD 0.04), while the heritability of PsC in analyses using non‐MHC SNPs was h2SNP = 0.54 (SD 0.05).The heritability of PsC in a population of 2,085 patients and 9,192 controls was estimated to be hhttp://onlinelibrary.wiley.com/doi/10.1002/art.42154). The genomic control inflation factor λgc (λgc1000) for the PsA‐BSTOP GWAS data set was estimated to be 1.1 (1.01), indicating minimal residual population stratification based on inflation of test statistics. We identified 16 non‐MHC loci with genome‐wide significance for the development of PsA (P = 5 × 10−8), 15 of which have previously been reported as significant in PsA and one which is novel (Table P = 1.61 × 10−9) on chromosome 22q11 in close proximity to the gene UBE2L3. We also found that the 2 previously reported PsA‐specific susceptibility loci PTPN22  and chr5q31  had genome‐wide significance for the development of PsA.We performed a meta‐analysis of GWAS summary statistics from a total of 5,065 PsA patients and 21,286 controls for a maximum of 8,558,403 SNPs using data from the PsA‐BSTOP, the UK Biobank, and the PsA Immunochip data sets . We identified significant genome‐wide association in 2 loci previously reported to be associated with the development of PsA, namely the MHC region  and the IL23R gene . No other regions reached genome‐wide significance. However, 4 loci demonstrated evidence of significant association in both data sets, with an overall P value in the meta‐analysis of P < 5 × 10−6  to identify PsA‐specific susceptibility loci using a population consisting of 4,340 PsA patients and 6,431 PsC patients . In addition, several genes involved in IFN regulation were highly ranked . Other highly ranked genes included UBA52, CNPY2, STAT2, and TYK2. Using the top 1% of ranked genes, we found significant enrichment in IFN and interleukin signaling pathways (see Supplementary Table http://onlinelibrary.wiley.com/doi/10.1002/art.42154). These pathways were not found to be enriched when using summary statistics from PsA patients compared to those from PsC patients, suggesting that these pathways are primarily involved in the pathogenesis of psoriasis (see Supplementary Tables http://onlinelibrary.wiley.com/doi/10.1002/art.42154). Pathways found to be enriched in the comparison of PsA to PsC included multiple pathways for NF‐κB signaling (adjusted P = 1.4 × 10−45) and Wnt signaling (adjusted P = 9.5 × 10−58), which provides compelling evidence that these pathways are potentially involved in the development of PsA.We utilized the recently described Pi bioinformatics pipeline to identify key genes and pathways in the development of PsA . Using shttp://onlinelibrary.wiley.com/doi/10.1002/art.42154). In addition, calibration and clinical utility were found to be poor for both the random forest model and the conditional inference forest model . The best model achieved an AUC of 0.66 when assessed using 10‐fold cross‐validation and consisted of 118 SNPs, 34 of which mapped to the MHC   which maps to chromosome 22q11 and is near the genes UBE2L3, YDJC, and CCDC116. This SNP has not been previously reported in the setting of PsA, but is highly correlated (r2 >0.8 based on SNP data from a northern European population) with a previously identified psoriasis SNP. This correlation does not represent a PsA‐specific genetic effect  and target pathways  for psoriasis, further supporting the notion that psoriasis in patients with PsA is genetically and biologically similar to psoriasis in patients with PsC. Interestingly, these pathways for PsA development were reported previously in a study applying the Pi pipeline to a set of 59 SNPs associated with PsA  in mice has been shown to halt progressive and erosive joint destruction in inflammatory arthritis by encouraging bone formation . InteresB3GNT2 locus was associated with the risk of developing PsA but not PsC (P = 0.029). While we found significant association with this SNP when comparing PsA patients to controls (P = 2.05 × 10−7), we found no evidence that this association is PsA‐specific based on our stratified analyses comparing PsA to PsC using PsA‐BSTOP data (P = 0.41) or on the larger meta‐analysis using UK Biobank and Immunochip data (P = 0.31).A previous study by Aterido et al investigated pathways associated with PsA susceptibility and reported significant association with the glycosaminoglycan metabolism pathway (Reactome R‐HSA‐1630316) . HoweverOur prediction models showed only modest ability to discriminate PsA from PsC in the available data sets, which was consistent with the findings of a recently published study by Smith et al . For theThe lack of discrimination observed in our data sets could be due to the differences in demographic and clinical characteristics of participants in our data sets compared to those of the participants in the original study. PsA is clinically a heterogeneous disease and differing proportions of patients with oligoarticular or polyarticular arthritis mutilans and axial disease  could have contributed to the decreased performance of the model. This potential issue was recognized by the authors of the original study and, although we followed the author recommendations by modeling the effects of these markers in our data to learn these cohort‐specific parameters, the overall classification performance remained low .An important limitation of our study was the potential impact of poor phenotype specificity in the PsC cohorts where the existence of undiagnosed PsA could have confounded the performance of any classification models. Although the participants in the BSTOP study were not screened for the absence of PsA by a rheumatologist, they were routinely followed‐up with an average of 8 consultations and had a psoriasis disease duration of 27 years without a recorded diagnosis of PsA. Additionally, restricting analyses to a subgroup of PsC patients with psoriasis for a duration of ≥10 (to minimize the risk of undiagnosed PsA) did not improve the performance of the predictive model (data not shown). However, given the extent of undiagnosed PsA in dermatology clinics, we cannot exclude the possibility of undiagnosed PsA in this group, which would have impacted both feature selection and model performance .In conclusion, predicting the risk of PsA development in patients with psoriasis remains an important research question, and external validation in addition to statistical validation is an important step in the clinical translation of PsA prediction models, as external validation tests the transportability of models to plausibly related populations . While pAll authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Barton had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.Soomro, Stadler, Dand, Barker, Smith, Bowes, Barton.Dand, Jadon, Duckworth, Ho, Marzo‐Ortega, Helliwell, Ryan, Kane, Korendowych, Simpson, Packham, McManus, Gabay, Lamacchia, Nissen, Brown, Verstappen, Barker, Smith, FitzGerald, McHugh, Warren, Bowes, Barton.Soomro, Stadler, Dand, Bluett, Jalali‐najafabadi, Duckworth, Van Staa, Barker, Smith, Bowes, Barton.Author Ryan is an employee of Genuity Science Dublin. Author Brown is an employee of Genomics England.Disclosure FormClick here for additional data file.Appendix S1 Supporting InformationClick here for additional data file.Supplementary table 1 | summary of clinical phenotype data for available psoriatic arthritis patientsSupplementary table 2 | two sets of genetic features used witin the Michigan classification pipelineSupplementary table 3 | Priority Index gene prioritisation of PsA compared to population controls (top 100)Supplementary table 4 | Priority Index pathway prioritisation for PsA compared to population controlsSupplementary table 5 | Priority Index gene prioritisation of PsA compared to PsC (top 100)Supplementary table 6 | Priority Index pathway prioritisation for PsA compared to PsCSupplementary table 7 | Classification performance metrics for random forest and conditional random forest in internal validation (IV) using the PsA‐BSTOP GWAS and external validation (EV) using the UK Biobank ICD10 datasetSupplementary table 8 | SNP weight for best model from SparSNP cross‐validation (intercept = 0.335167696577)Click here for additional data file.


To determine the characteristics of crystalline lens with varying refractive errors and relationship with axial elongation in young school children.A total of 1465 children aged 6–8 years were examined annually for 2 years. Each participant underwent a series of ophthalmic examinations, including cycloplegic autorefraction, crystalline lens and axial length measurement. Crystalline lens power was determined, and factors associated with different refractive statuses were investigated.Crystalline lens power decreased with time; reduction in lens power in Year 1 was greater in children with emmetropia (−0.69 ± 0.59 dioptre [D]) than in those with hyperopia (−0.49 ± 0.56 D) or myopia (−0.45 ± 0.55 D) (p < 0.001). Among the emmetropes, there were no differences in loss of crystalline lens power between those who remained emmetropic (−0.63 ± 0.59 D) and those who became myopic at Year 1 (−0.74 ± 0.61 D) and Year 2  visits. Among myopes at Year 1 visit, there was a greater reduction at Year 2 in those who had baseline emmetropia (−0.61 ± 0.51 D) than those who had baseline myopia . The trend was similar among children of the same age. There was a significant correlation between changes in lens power and axial elongation in non‐myopia  and new myopia , but not in established myopia .There is accelerated loss of lens power in emmetropia and early stage of myopia. However, this loss is retarded when myopia persists and is accompanied by disappearance of the compensatory effect of lens power against axial elongation. These findings provide new insights into human refractive development. The growth and changes in crystalline lens, especially in infancy and childhood, appear to be part of the coordinated growth and development process between the ocular biometric components , leading to emmetropization , crystalline lens thickness and refractive error state. These data were gathered from a large sample of primary school children aged 6–8 years who were examined annually over a 2‐year period.The study population included 1465 children enrolled in the Shanghai Time Outside to Reduce Myopia (STORM) trial. The STORM trial was a 2‐year, school‐based, prospective, cluster‐randomized study conducted from 2016 to 2018. Primarily, it was designed to determine the effect of outdoor time on the onset and progression of myopia. The methodology of this trial has been presented in detail elsewhere. In brief, school children (grades I–II) aged 6–8 years were enrolled and monitored annually over a 2‐year period ; slit‐lamp examination ; intraocular pressure check ; cycloplegic autorefraction ; and AL measurements IOLMaster . Measurements of the anterior and posterior radii of curvature of the cornea as well as ACD, lens thickness and central corneal thickness, assessed using a Pentacam , were performed in some of the children. The measurement was performed once for each child unless the quality of the measurement presented to be not ‘OK’, data of biometric measurements were then used in the following analysis only if the quality was ‘OK’. The examinations were conducted by experienced physicians who were trained in the aforementioned techniques prior to the initiation of the study.Refractive error measurements and assessments of the crystalline lens curvature were conducted postcycloplegic examination. Briefly, cycloplegia was determined as follows: a single drop of 0.5% proparacaine hydrochloride  was administered for topical anaesthesia, followed by two drops of 1% cyclopentolate  administered 5 min apart. The pupil size and response to light was determined approximately 40 min after instillation. Cycloplegia was considered complete if the pupil size was large with no or negligible response to light.Of the original trial sample, 1465 children for whom crystalline lens thickness, corneal curvature, corneal thickness and ACD (using Pentacam) data were available for all visits  were included in the final analysis. Only data from the right eyes of the participants were analysed. The spherical equivalent (SE) was calculated as the sphere power plus half of the cylinder power in dioptres (D). Hyperopia, emmetropia and myopia were defined as SE ≥+1.00 D, between >−0.50 D and <+1.00 D, and ≤−0.50 D respectively  stable emmetropia ; (b) premyopia ; and (c) around myopia . Participants with myopia at Year 1 visit were categorized into the following states: (a) new myopia  and (b) established myopia (myopia at both baseline and Year 1 visits). A detailed scheme is presented in Fig. The corneal power was calculated using the anterior and posterior corneal radii of curvature and a refractive index of 1.376, as proposed by Olsen and Manns et al.,  Olsen, .Km,a = (nc−1)/ Rm,aKm,p = (n−nc)/ Rm,pK = Km,a + Km,p−Km,a * Km,p * CCT/nc.where Km,a and Km,p are the mean anterior and posterior keratometric measurements respectively; Rm,a and Rm,p are the anterior and posterior corneal radii of curvature respectively; CCT is the central corneal thickness; and nc is the corneal refractive index.n = 4/3 of the aqueous and vitreous indices, c1 = 0.596 and c2 = 0.358 as estimated using the Gullstrand–Emsley eye model. The SE refraction was defined as Scv = SE/(1–0.014 * SE). The effective ACD included the central corneal thickness, and the ACD as yielded by the Pentacam.The crystalline lens power was calculated using Bennett’s formula based on cycloplegic refraction, corneal power, ACD, lens thickness and AL Bennett , as showt‐tests (between genders) or analysis of variance with post hoc tests (for refractive groups). Differences in biometric parameters (including lens power) between the baseline and each of the annual visits were compared using repeated‐measures analysis of variance by testing for sphericity. Changes in lens power and other biometric parameters  between the first and second year of follow‐up were assessed using paired t‐tests. Correlations of the ocular biometric parameters and their changes were analysed using the Pearson correlation coefficients. Multiple regression analysis was performed to investigate the factors associated with changes in lens power among different refractive states.The parameters were presented as the mean ± standard deviation for the continuous variables. Intergroup differences were tested with Student’s n = 182 [6 years], 668 [7 years] and 615 [8 years]; 54.6% males). At baseline, older children had significantly reduced lens power, longer AL, more myopic SE, deeper ACD and a thinner crystalline lens , but no difference in corneal power (p = 0.317). Similarly, over the 2‐year follow‐up period, the crystalline lens power was reduced, the crystalline lens became thinner, the AL longer and the SE became less hyperopic/more myopic across all age groups. All changes were significant except for the change in ACD (p < 0.01)  exhibited broadly Gaussian distributions, with a decrease in mean lens power over time (decrease in mean power of −0.56 ± 0.58 D at Year 1 versus baseline and −0.49 ± 0.52 D at Year 2 versus Year 1)  . During the second year of the follow‐up period, the loss of lens power was greater in new myopes (−0.61 ± 0.51 D) versus established myopes  . These relationships were similar for the first‐year changes and different age groups  earlier would result in earlier consumption of the lens power. This process was associated with a greater degree of uncompensated elongation during childhood, thus increasing the risk of myopia onset and progression. This is consistent with the common clinical intuition that early‐onset emmetropia is a major risk factor for the subsequent development of myopia , rather than the optically defined emmetropia (−0.50 D to +0.50 D), maybe the preferred end‐point for refractive development in humans , continued with rapid loss in the early stage of myopia (if present), and was characterized by reduced loss when myopia persisted. Further research is warranted to elucidate the underlying mechanisms of this process. These findings may contribute to the current knowledge regarding human refractive development, which would facilitate the routine management of refractive development of young children and guide their normal growth to avoid the development of amblyopia and refractive error. The results may also contribute to the exploration of potential novel approaches for the prevention and control of myopia.


The profile of cognitive impairment associated with the late stages of Parkinson's disease (LSPD) is rarely reported. Its characterization is necessary to better understand the cognitive changes that occur as the disease progresses and to better contribute to its management.In this cross‐sectional study, we characterized the cognitive profile of LSPD patients using the comprehensive assessment methodology proposed by the International Parkinson and Movement Disorders Society Task Force. The association of clinical and demographic variables with dementia diagnosis was also investigated using binary logistic regression analysis.N = 30), 25 (83.3%) LSPD patients met the diagnostic criteria for mild cognitive impairment, mostly with multiple domain impairment (96.0%) and a heterogeneous profile. Memory was the most frequent and severely impaired cognitive domain in both groups. Disease disability, orientation, complex order comprehension, verbal learning, and visuoconstructive abilities were significantly associated with dementia diagnosis (p < .05).Eighty‐four LSPD patients were included . Fifty‐four (64.3%) were classified as demented and presented a global impairment cognitive profile. In the nondemented group  were classified as demented, most of them presented a global impairment profile, with both Alzheimer's and PD‐typical impairments. Twenty‐five patients (30%) presented mild cognitive impairment, mainly with a heterogeneous profile. Disease disability, orientation, complex order comprehension, verbal learning, and visuoconstruction were found to contribute to the dementia diagnosis. However, there are few published studies on late‐stage Parkinson's disease (LSPD). Indeed, LSPD is a poorly studied population due to the typically severe motor and nonmotor symptoms that often complicate cognitive assessment. This may be the reason why studies including this population are neuropathological studies  were recruited.All participants and their formal/informal caregivers were informed about the study objectives and procedures and were asked for their written informed consent. The informed consent of cognitively impaired patients was signed by the caregiver. The study was approved by the local ethics committee.The inclusion criteria were (1) idiopathic PD according to the UK Brain Bank criteria , it took place at patients’ home. The Movement Disorders Society—Unified Parkinson Disease Rating Scale (MDS–UPDRS) (Parts I and IV)  was performed by a neuropsychologist. It took place in a single session, at the patients' homes, to ensure the presence of the usual amenities and to reduce as far as possible any interference in the patients’ lives.A clinical interview was undertaken, with caregiver collaboration, to obtain each LSPD patient's sociodemographic and clinical information.To assess the impact of cognitive impairment on activities of daily living (ADL), two approaches were taken: 1) a patient and caregiver clinical interview and 2) the Pill Questionnaire  below the adjusted normative scores (z‐score ← 1).We considered a cognitive test/domain as impaired if its The cognitive profile was described based on the organization of cognitive domains proposed by the MDS PDD Level II  by using the MDS MCI Level II criteria (comprehensive assessment) .To describe the cognitive performance of LSPD patients, we compared clinical and demographic variables, and neuropsychological z‐scores of the demented and nondemented patients by using the Chi‐square, Mann‐Whitney U, and Wilcoxon tests, as appropriate (p < .05), as appropriate.Subsequently, we analysed cognitive profile subgroups by comparing clinical and cognitive variables in each of the demented and nondemented groups and between groups, using Chi‐square, Wilcoxon, Mann‐Whitney U, and Kruskal‐Wallis tests with post‐hoc pairwise analysis with Bonferroni correction of (p < .05) between demented and nondemented groups as independent variables and with presence or absence of dementia as the dependent variable. Per block step, the improvement of the regression model was compared using the likelihood ratio test. The goodness of fit of the model was assessed with the Hosmer‐Lemeshow test.Finally, to examine the contribution of the clinical, demographic and neuropsychological measures for dementia diagnosis, binary logistic regression analysis with a forward conditional procedure was run with all of the variables that reached statistical significance .33.1Eighty‐four LSPD patients performed the NPA. Forty‐eight (57.1%) were women, with a mean age of 75.4 years (±6.9), 6.5 years (±4.5) of education, 16.9 years (±7.5) of disease duration, and 58.5 years (±10.9) at PD onset. 97.3% were on levodopa treatment Table .According to MDS PDD Level II criteria, 54 (64.3%) LSPD patients met the criteria for PDD (27/36 men (75%), 27/49 women (55%)).There were no statistically significant differences between demented and nondemented groups concerning sex, age, education, disease duration, age at PD onset, or levodopa treatment profile. We highlight the fact that there were no significant differences in the MDS–UPDRS tremor item, which arose in both groups with sufficiently low frequency or intensity to cause no impact on function, as well as in motor complications (MDS–UPDRS Part IV), whose frequency and severity were between mild and moderate in both groups Table .3.2N = 30), 5 (16.7%) LSPD patients did not present changes in cognitive domains. The remaining 25 (83.3%) had impairment on at least two neuropsychological tests, meeting criteria for the diagnosis of MCI (4.0% with single‐domain impairment and 96.0% with multiple domain impairment).In the nondemented group (z‐score −1.7±0.5)  Figure . When di) Figure  particulInstrumental function was also impaired in nondemented LSPD (LSPD‐NoD) patients (20.7%), mainly visuoperceptive (40.7%) and visuospatial (39.3%) functions. Executive function was the least impaired cognitive domain in this group (6.7%). However, when we analyzed it in detail, we observed a high frequency of impairment in attention tasks, mainly in set shifting (70.4%) and set activation (44.8%).N = 54), 40.7% of LSPD patients reported changes in multiple domains and 59.3% in all cognitive domains.In the demented group (The memory cognitive domain was the most frequently impaired (86.8%). We dissociated it into its two components to analyze its deficit patterns, observing that the majority of demented LSPD (LSPD‐D) patients (60.4%) presented changes in both components, and that impairment was accentuated (mean z‐score −2.6±0.7), with a high frequency of intrusions (73.6% LSPD‐D patients with more than five intrusions).p < .05).For executive function, the second most impaired LSPD‐D cognitive domain (85.2%), we observed a pattern of changes similar to those in the nondemented group (mainly affecting attention) but with a much more pronounced frequency and impairment severity in all executive function cognitive tasks (p = .00). When we looked at its pattern of changes, visuospatial was the function that was most frequently impaired (85.1%), followed by visuoconstructive (83.7%), two cognitive functions where there was also the most pronounced impairment (mean z‐score −3.9±2.6) (p < .05)  did not present significant changes in the cognitive tasks underlying each cognitive profile. They presented a heterogeneous cognitive profile. Only 6.7% of LSPD patients were classified as having a subcortical profile, 6.7% as having a cortical profile and, 13.3% as having a global impairment profile , orientation in space , language (complex order comprehension) , and construction , (2) S&E disability scale , (3) RAVLT verbal learning , and (4) copy of the clock test  were associated with the condition of dementia, with reduced scores supporting the dementia diagnosis.The hierarchical logistic regression analysis, with presence/absence of PDD as the dependent variable and clinical and neuropsychological measures as independent variables, showed that (1) the MMSE subscales scores of orientation in time  LSPD patients met the criteria for PDD. Of the 30 (35.7%) LSPD‐NoD patients, 5 (16.7%) did not present cognitive impairment. The remaining 25 (83.3%) met criteria for the diagnosis of MCI (4.0% with single‐domain impairment and 96.0% with multiple‐domain impairment). Reid et al.  investigAnalysis of the cognitive performance of LSPD patients indicated that most of the demented and nondemented patients presented impairment in multiple cognitive domains.Memory was the cognitive domain most frequently impaired, and the severity of the changes was also the most pronounced in both groups. Analysis by components showed that in the nondemented group, impairment prevailed in the mediotemporal component, with more frequent changes in long‐term retention, with a high frequency of intrusions in immediate and differed evocation, which also reveals that LSPD‐NoD patients have difficulty maintaining the distinction between information coming from the outside and their own associations , assessed by the Boston Naming Test. Errors on this test, although infrequent, sometimes arose due to visuoperceptive changes and not due to an impairment in naming. These findings go against what is reported in the literature. Naming is not frequently reported as an impaired cognitive task in PD  the decline in executive function occurs in the early stages and then tapers off during the mid‐stages of PD , data extraction (lead), formal analysis (lead), funding acquisition, investigation (lead), methodology, project administration , visualization, writing—original draft preparation. Margherita Fabbri: Data extraction, formal analysis, writing—review and editing. Catarina Godinho: Data extraction, formal analysis, writing—review and editing. Rita Moiron Simões: Data extraction, formal analysis, writing—review and editing. Inês Chendo: Writing—review and editing. Miguel Coelho: Writing—review and editing. Isabel Pavão Martins: Conceptualization , methodology, supervision, writing—review and editing. Joaquim J. Ferreira: Conceptualization , investigation, methodology (lead), project administration , supervision (lead), writing—review, peer review (lead) and editing (lead).Catarina Severiano e Sousa: No conflict of interest to report. No additional disclosures to report. Margherita Fabbri: No conflict of interest to report. No specific funding was received for this work. She has received consultancy fees from AbbVie. No additional disclosures to report. Catarina Godinho: No conflict of interest to report. No specific funding was received for this work. No additional disclosures to report. Rita Simões: no conflict of interest to report. No specific funding was received for this work. She has received consultancy fees from BIAL—PORTELA & Ca, SA, Zambon, and AbbVie. No additional disclosures to report. Inês Chendo: No conflict of interest to report. No specific funding was received for this work. No additional disclosures to report. Miguel Coelho: No conflict of interest to report. No specific funding was received for this work. He has received consultancy fees from Zambon. No additional disclosures to report. Isabel Pavão Martins: No conflict of interest to report. No specific funding was received for this work. No additional disclosures to report. Joaquim J. Ferreira: No conflict of interest to report. No specific funding was received for this work. He has received grants from GlaxoSmithKline, Grunenthal, Fundação MSD , TEVA, MSD, Allergan, Novartis, Medtronic. He received consultancy fees from GlaxoSmithKline, Novartis, TEVA, Lundbeck, Solvay, BIAL, Merck‐Serono, Merz, Ipsen, Biogen, Acadia, Allergan, Abbvie, Sunovion Pharmaceuticals, Zambon, Affiris. He has also participated in advisory boards for Bial and provided expert testimony to Novartis.TABLE S1. Cognitive performance of LSPD patientsClick here for additional data file.TABLE S2. Comparative analysis of the LSPD patients’ cognitive performance according to their cognitive profile in nondementia vs dementia groupsClick here for additional data file.


To investigate the effect of a quality improvement project with an educational/motivational intervention in northern Italy on the implementation of the trial of labor after cesarean section (CS).n = 23) of the Emilia‐Romagna region was included. Gynecologist opinion leaders were first trained about Italian CS recommendations. Barriers to implementation were discussed and shared. Educational/motivational interventions were implemented. Data of multipara with previous CS, with a single, cephalic pregnancy at term, were collected during two periods, before (2012–2014) and after (2017–2019) the intervention (2015–2016). The primary outcome was the rate of vaginal birth after CS (VBAC) and perinatal outcomes.A pre‐post study design was used. Every birth center (P < 0.001). The likelihood of VBAC—adjusted for age 40 years or older, Caucasian, body mass index  at least 30, previous vaginal delivery, and labor induction—was increased by the intervention by 42% . Neonatal well‐being was improved by intervention; neonates requiring resuscitation decreased from 2.1% to 1.6% (P = 0.001).A total of 20 496 women were included. The VBAC rate increased from 18.1% to 23.1% after intervention (Educating and motivating gynecologists toward the trial of labor after CS is worth pursuing. Health quality improvement is demonstrated by increased VBAC even improving neonatal well‐being. Educating gynecologists toward trial of labor after cesarean section is an intervention that leads to increasing vaginal birth after cesarean section, even improving neonatal well‐being. However, it is associated with both immediate and long‐term maternal and perinatal risks.Elective repeat CS (RCS) and VBAC for women with a previous CS are both associated with benefits and harms.As Italy has one of the highest CS rates (31.1%) in Europe,Few studies have evaluated the effects of clinician‐centered interventions to promote VBAC, and the available data show conflicting results.On these bases, we decided to perform an area‐based quality improvement program focusing on the implementation of Italian guidelines related to VBAC in Emilia‐Romagna, a north Italian region, characterized by a proactive policy of health quality.22.1The present pre‐post study is part of a project endorsed by the Regional Health Authority of Emilia‐Romagna, a regional governmental body accountable for issuing routinely collected anonymized patient data to research institutions. Institutional Review Board or Ethics Committee approval was not needed because, according to the Italian privacy law , regional National Health Service data can be used for scientific purposes provided sensitive information is anonymized.Emilia‐Romagna is a region of central Italy that accounts for about 30 000 deliveries/year occurring in 23 public birth centers. Data about birth certificates have been issued annually since 2003 and analyzed in a public report.The study included every woman categorized in Robson Class V2.2Gynecologist opinion leaders were first trained in Italian National Health Service recommendations on the appropriate use of CS, counseling on VBAC, and knowledge of Grobman score. The gynecologist opinion leader was the most experienced as well as the most motivated physician with attitudes in counseling on the mode of delivery. The training was performed for one opinion leader for each birth unit. Barriers to implementation and possible solutions were discussed locally and shared at the regional level. The educational/motivational interventions program included: (1) training of physicians regarding evidence‐based clinical practices conducted by gynecologist opinion leaders, (2) implementation of clinical audits in each birth unit by a multidisciplinary perinatal team, and (3) implementation of best practices in each birth unit and joint discussions by women and clinicians.Moreover, distance technology‐assisted learning resources were also developed to implement professionals' knowledge and counseling attitudes. In each birth unit, the local intervention identified was implemented for 2 years, during 2015 and 2016.Data of multipara with one or two previous CS, with a single, cephalic pregnancy at term, were captured from birth certificates in two periods, before (2012–2014) and after (2017–2019) the intervention, which occurred in 2015–2016.The primary outcome was the rate of VBAC in multiparous women with at least one previous CS, with a single cephalic pregnancy, at 37 weeks or more of pregnancy (Robson group 5), comparing the pre‐intervention (2012–2014) and post‐intervention (2017–2019) periods. According to the Grobman nomogram, the main outcome was adjusted for known maternal conditions affecting VBAC success, i.e., previous vaginal delivery, pre‐pregnancy body mass index  classes, maternal age 40 years or older, maternal education level, and place of origin . Educational/motivational VBAC intervention was also included. Relevant perinatal outcomes were collected.2.3Data from the 23 maternity services of Emilia‐Romagna during calendar years 2012–2014 and 2017–2019 were extracted from the Emilia‐Romagna Birth Certificates , including the mother's sociodemographic information , obstetric history , clinical information on the current pregnancy , and the newborn  collected within 10 days of delivery by the attending midwife of all Maternity units.2.4t test and χ2 test were performed for continuous and categorical variables, respectively. Continuous variables were described as the mean ± standard deviation (SD), whereas categorical variables were described as the absolute and percentage frequencies. The multivariable prediction model for the risk of having an RCS was developed by carrying out the following steps. First, univariate logistic regression models were used to assess the relationship among each relevant independent variable. The final prediction model was determined by a stepwise backward selection procedure in which only independent variables associated with RCS risk with P value less than 0.05 were retained. Results of logistic models were reported as the odds ratio (OR) with 95% confidence interval (CI) and Wald P value. Statistical analyses were performed with stata 16.1 (StataCorp. 2019).Analyses were set up by comparing the two study groups “before” and “after” the educational/motivational intervention. Student 3During the study period a total of 269 497 women delivered in the area: 106 014 of them gave birth in the pre‐intervention period (2012–2014) while 95 813 women delivered during the post‐intervention period (2017–2019), including 11 035 (10.4%) and 9461 (9.8%) women  classified in Robson group 5, respectively. The post‐intervention was smaller, in line with the overall reduction of the births from 2012 to 2019.P = 0.001) whereas a significantly lower rate of Italian women was found in the post‐intervention group . Similarly, obese women and women conceiving with assisted reproductive technologies significantly increased in the post‐intervention period.The characteristics of the population are reported in Table P < 0.001), corresponding to a 5.0% reduction (Table P < 0.001), indicating different management of women with previous CS in the latter group, accompanied by a significantly higher rate of women delivering between 39 and 41 weeks of pregnancy (P = 0.001). Table Compared with the pre‐intervention group, the post‐intervention group presented an overall significant reduction in RCS rate  (Table P = 0.001), requiring less heart massage, adrenaline, and other drugs (P < 0.02)  Table . NeonataP = 0.000), the educational/motivational intervention , the pre‐pregnancy BMI classes , and maternal age 40 years or older  , adjusted for potential risk factors, was associated with having a vaginal delivery.The educational/motivational intervention (OR 1.45, 95% CI 1.3–1.6; 4The educational motivational intervention implemented for 2 years in our region allowed an overall increase in VBAC rate of around 5%, although with heterogeneity among birth centers.Such an effect has been obtained with a multidisciplinary program, including audits regarding the indications for CS, feedback to health professionals, and implementation of best practices. Few studies have evaluated similar programs. A systematic review evaluated the effects of clinician‐centered interventions.It must be underlined that risk factors for unsuccessful VBAC, as reported in the Grobman nomogram, were significantly increased in the population during the post‐intervention period. Nevertheless, the educational/motivational program was effective in reducing the CS rate in women of Robson group 5.A limitation of our study is the lack of data about uterine ruptures occurring in the different periods. However, the safety of increasing VBAC was witnessed by the stable rate of neonatal complications requiring intensive care admission. A positive effect of having reduced RCS was demonstrated by the lower rate of neonates needing resuscitation in the post‐intervention period, confirming safe and good outcomes described in successful VBAC.Another limitation of this study is the differential distribution of VBAC across the 23 hospitals included in the study, suggesting heterogeneity in the implementation of the program. These data were reported in Table The quality improvement program of our study, in line with the recently published one,In conclusion, educating and motivating gynecologists toward TOLAC is worth pursuing. Health quality improvement is demonstrated by increased VBAC, even improving neonatal well‐being.Open Access Funding provided by Universita degli Studi di Modena e Reggio Emilia within the CRUI‐CARE Agreement.The authors have no conflict of interests.FM, FF, and DM made substantial contributions to the conception or design of the work, the acquisition, analysis, interpretation of data for the work, and wrote the paper; FM, DM, EP, EB, and IN drafted the work or revised it critically for important intellectual content. FF gave final approval of the version to be published.Table S1Click here for additional data file.


Our study compared rScO2 desaturation events in children undergoing GA or chloral hydrate sedation (CHS).During pediatric general anesthesia (GA) and sedation, clinicians aim to maintain physiological parameters within normal ranges. Accordingly, regional cerebral oxygen saturation (rScOn = 40) and GA (n = 52). Data of 81 children  were analyzed.Ninety-two children undergoing long auditory assessments were randomly assigned to two study arms: CHS . In this group, ENT surgeons performed minor interventions in 29 patients based on intraprocedural microscopic ear examinations.2) and allow oxygen administration. Chloral hydrate was administered in the parent’s presence. Children had no intravenous access which is an advantage of sedation techniques.In the CHS group, recommendations for monitoring and treatment of children undergoing moderate sedation were met. Furthermore, children received a double-barreled nasal oxygen cannula to measure end-tidal carbon dioxide , oxygen saturation (SpO2), etCO2, systolic and mean blood pressure (BP), and heart rate (HR); these variables were analyzed for their association with drop in rScO2 to below baseline (%drop_rScO2).Adverse event (AE) was a decline in cerebral oxygenation to below 50% or below 20% from the baseline for ≥1 min. The primary endpoint was the number of children with AE across the study arms. Secondary variables were: fraction of inspired oxygen . Severe neurological complications are rare events after general anesthesia (GA) in early childhood . PossiblAnesthesia enables necessary surgical or diagnostic procedures to be conducted that are relevant to a child’s development . DiagnosNumerous medical procedures in children are performed under sedation by non-anesthesiologists . Severalwww.safetots.org) defined a criteria-set known as the “10 N concept” that incorporates the following: no fear and accidental awareness, no postoperative discomfort , normovolemia, normotension, normocardia, normoxemia, normocapnia, and normonatremia. These criteria aim to maintain homeostasis, thus increasing anesthesia safety in pediatric patients. However, not all physiological reference values are well-defined ) rScO2 baselines were 73 (69.5–79 [57–85]) and 70 (68–74 [62.5–84]) in the anesthesia groups with and without surgery (p = 0.33), respectively, and 81 (73–85 [60.5–89.5]) in the sedation group, which was higher than that in the anesthesia groups (both p < 0.02).Thus, data of 81 children  were analyzed . The statistical test results remained non-significant when the GA groups were merged (p = 0.88). Three children, one from each group, met the first criterion of an AE, namely desaturation ≥1 min below 20% from baseline. The child in the sedation group also fulfilled the second criterion for an AE, namely, desaturation < absolute value 50% for 39.7 min. Table The pairwise χ2 in children receiving sedation was below baseline for 78% of the procedural time, whereas the anesthesia groups reached significantly lower values: 49% for GA with surgery, and 37% for GA without intervention .Although the groups did not differ with respect to the primary endpoint, it is of interest from a practical point of view that in our study, rScO2p-value distributions were uniform  and FIO2 + 0.645 ± 0.124, highlighting that both variables have similar high influences on %drop_ rScO2.In contrast, the distributions of HR, SIO2 cannot be a priori hypothesized as strictly linear. We extend the statistical modeling by including nonlinear interactions using GAM; this model is presented in Fig. IO2), GAM explains 85% of the rScO2 variance (R2 = 0.85). GAM’s highly predictive performance can be explained using tensor products, i.e., interactions (synergy) between covariates. Accordingly, a concomitant increase in HR and FIO2 should lead to a more effective correction of %drop_rScO2.Linear regressions were fitted without interactions; nonetheless, the homeostatic response of the brain to changes in HR and F2 drop to below 50% or < 20% of baseline for ≥1 min). Hereby, one patient in each group had an AE. The secondary endpoint delivered the current study’s novelty, i.e., the strong influence of HR on cerebral oxygenation, whereas previous works advocated for maintaining BP and etCO2 within specific ranges [This randomized controlled trial investigated cerebral oxygenation in children aged up to 36 months undergoing 10 N-based GA or CHS for a long-lasting diagnostic procedure. The primary endpoint compared the incidence of AE across groups  receiving GA experienced cerebral desaturation. These patients were aged 2 and 3 months, thus having a high risk of critical perioperative events . The proces used , 28. In ur study . In a muur study . Adherenpatients . Only 2%a et al. ; however2 values that represent a hypoxic–ischemic threshold in children [2 below 50% absolute or a %drop_rScO2 below 20% from baseline appeared to be a reasonable trigger for therapeutic intervention [2 during noncardiac surgery under GA [To date, no human studies have determined the critical rScOchildren . Based orvention , 33. Intunder GA . Moreoveunder GA .2 in the CHS study arm was statistically significant more frequent below the baseline than in the GA groups. One possible interpretation is that closer monitoring and rapid intervention by an anesthesiologist may reduce the duration of suboptimal rScO2. In this context, this includes the adherence to the predefined 10 N concept, which can also be seen as a checklist for a structured approach to maintain homeostasis, and has been suggested for children undergoing GA [pO2), and discharge. The procedure resulted in a low AE rate of 0.67%. Of the nine affected children, three developed respiratory complications (two had a mild hypoxia that was successfully treated with head repositioning and one developed evening stridor) [pO2 < 90% and vomiting). The authors stated that the attending nurse could resolve all significant AEs, e.g. by repositioning the children’s head and providing supplementary oxygen [In our study, rScOgoing GA . Notablygoing GA , especiagoing GA . In othestridor) . Anothery oxygen . Smallery oxygen  or only y oxygen , 40. Howy oxygen . In prevy oxygen –44.2 values in children undergoing CHS for a standard diagnostic procedure. Our results encourage the development of quality criteria for monitoring and therapeutic measures that support maintenance of cerebral homeostasis in children during sedation. Padmanabhan et al. studied cerebral oxygenation in 100 children undergoing procedural sedation with various sedatives . As in our study, severe drops of rScO2 values (< 50% absolute or more than 20% from baseline) were rarely observed, but the authors detected a greater effect of hypercarbia on rScO2 than hypoxemia [Altogether, these studies demonstrate that a high level of safety can be achieved with sedation procedures, including CHS, but do not allow conclusions to be drawn regarding cerebral oxygenation, because NIRS is not a standard monitoring for sedation in clinical practice or in studies evaluating the safety of a specific sedation protocol. To our knowledge, the present study is the first to analyze rScOypoxemia .2 in children undergoing GA [2 on rScO2 in children under GA has been reported [Previous studies revealed that BP is an influencing factor on %drop_rScOgoing GA , 29, 46.going GA , 48, andgoing GA , 49, ultgoing GA , and oscgoing GA , 51). A going GA , which dgoing GA . While tgoing GA . Althougreported , it was IO2 and HR showed a greater influence on %drop_ rScO2 than BP and etCO2. Michelet et al. examined hemodynamics during intraoperative episodes of cerebral oxygen desaturation in children aged ≤3 months and reported both decreased BP and HR [2 in neonates undergoing urgent or elective surgery [In our data, FP and HR . In cont surgery .IO2, accurately predicts %drop_ rScO2, providing novel possibilities for maintaining brain homeostasis even when NIRS monitoring is unavailable. Accordingly, a HR of 110–130 bpm and an FIO2 of 0.3–0.4 would support a stable rScO2 for children aged ≤3 years under GA for noncardiac surgery  cerebral oxygenation by closely controlling HR and FIO2.Oxygen delivery  plays a key role in maintaining homeostasis. During anesthesia, FHowever, cerebral oxygen delivery also depends on cerebral blood flow (CBF), which is determined by perfusion pressure and cerebrovascular resistance , and is 2 were maintained within physiological ranges, i.e. reduced variance; therefore, a precise estimation of their effect-sizes is not feasible. Third, the NIRS sensors were attached to the awake child in the presence of the parents immediately after the administration of chloral hydrate or midazolam. A slight deviation of the baseline compared to a state without external influences cannot completely excluded. Fourth, the groups differed in their adherence to the 10 N criteria in the GA group (not available in the CHS group) and used drugs . Anesthetic and sedative drugs affect cerebral autoregulation and cerebral metabolism to varying degrees, even within a drug class. These effects can partially depend on the dosage used and carbon dioxide levels [2 [Our study has several limitations. First, some children underwent minor surgery based on the results of intraprocedural microscopic ear examinations, which resulted in the creation of a third group. Second, by study design (10 N concept), BP and etCOe levels . Becauseevels [2 , our resIO2 are highly correlated with brain oxygenation in children aged up to 3 years old. Our results advocate for the rapid correction of bradycardia to reduce the duration of suboptimal cerebral oxygenation in children below 3 years of age.The optimized 10 N concept contributes to smaller deviations of cerebral oxygenation from pre-procedural baselines. Our study provides further evidence that HR and F


ClinicalTrials.gov identifier: NCT02612129), patients (2‐18 years) were randomised 2:1 to arimoclomol:placebo, stratified by miglustat use. Routine clinical care was maintained. Arimoclomol was administered orally three times daily. The primary endpoint was change in 5‐domain NPC Clinical Severity Scale (NPCCSS) score from baseline to 12 months. Fifty patients enrolled; 42 completed. At month 12, the mean progression from baseline in the 5‐domain NPCCSS was 0.76 with arimoclomol vs 2.15 with placebo. A statistically significant treatment difference in favour of arimoclomol of −1.40  was observed, corresponding to a 65% reduction in annual disease progression. In the prespecified subgroup of patients receiving miglustat as routine care, arimoclomol resulted in stabilisation of disease severity over 12 months with a treatment difference of −2.06 in favour of arimoclomol (P = .006). Adverse events occurred in 30/34 patients (88.2%) receiving arimoclomol and 12/16 (75.0%) receiving placebo. Fewer patients had serious adverse events with arimoclomol  vs placebo . Treatment‐related serious adverse events (n = 2) included urticaria and angioedema. Arimoclomol provided a significant and clinically meaningful treatment effect in NPC and was well tolerated.Niemann‐Pick disease type C (NPC) is a rare, genetic, progressive neurodegenerative disorder with high unmet medical need. We investigated the safety and efficacy of arimoclomol, which amplifies the heat shock response to target NPC protein misfolding and improve lysosomal function, in patients with NPC. In a 12‐month, prospective, randomised, double‐blind, placebo‐controlled, phase 2/3 trial ( The primary endpoint was the 5‐domain NPC Clinical Severity Scale (NPCCSS) score, as described by Mengel et al.We conducted the present trial ; at least one neurological sign of disease; ability to walk independently or with assistance; and if treated with miglustat, being on stable dosing for at least 6 months. Patients who completed our NPC observational studyEligible patients were male or female patients aged 2 to 18 years who fulfilled the following criteria: genetically confirmed mutations in both alleles of 2.3Patients enrolled in the trial were stratified by use of miglustat at baseline. An interactive response technology system assigned treatment to each patient via a randomisation list. Patients in both strata were randomised 2:1 to receive arimoclomol or placebo. Given the ultra‐rare condition, and expected rate of progression, sample size and trial duration were primarily informed by feasibility and not by a formal sample size calculation. Up to 52 patients with NPC were planned to be randomised, to have at least 40 evaluable patients' data at the 12 months landmark visit.To ensure blinding, all investigational products and their packaging  were indistinguishable in terms of composition, texture, appearance, solubility, smell, and flavour.2.4The screening visit (visit 1) included a baseline assessment, randomisation assignment, and pharmacokinetic (PK) assessment . Each patient was randomised to receive arimoclomol or placebo three times daily. Arimoclomol was administered orally or by feeding tube at 93 to 372 mg/day based on the patient's body weight as described in During the 12‐month treatment phase, efficacy assessments for the primary endpoint, the 5‐domain NPCCSS scores, and for the non‐disease specific Clinical Global Impression—Improvement scale (CGI‐I) scores were performed at baseline and after 3, 6, 9, and 12 months of treatment; all other efficacy and biomarker assessments were performed at baseline and after 6 and 12 months of treatment.An independent Data Safety Monitoring Board (DSMB), consisting of three experts who had access to unblinded data, reviewed safety data four times during the blinded phase. For patients in either treatment group with rapid disease progression, an “early escape clause” could be invoked if a particular set of criteria were met (assessed by the investigator and approved by the sponsor). In these events, blinded study drug dosing was suspended and “rescue” arimoclomol treatment was initiated while patients continued with their current protocol schedule Figure .2.52.5.1The primary endpoint was change from baseline in NPC severity at 12 months as assessed by the 5‐domain NPCCSS, an abbreviated assessment tool originating from the 17‐domain NPCCSS developed by Yanjanin et al.2.5.2NPC is a heterogeneous disease, and patients aged 2 to 18 years present with a large spectrum of disease manifestations.In the EU, miglustat is indicated for the treatment of progressive neurological manifestations in patients with NPC. However, not all patients are candidates for miglustat treatment , and it is recommended that the benefit of treatment should be evaluated on a regular basis .post hoc subgroup analyses were also conducted. In the first post hoc analysis, patients with double functional null mutations in NPC1 were excluded. The presence of functional null mutations on both alleles of NPC1  is rare in patients with NPC, and is strongly predictive of early onset and rapid disease progression.post hoc analysis, only patients with an annual severity increment score (ASIS) of 0.5 to 2.0 were included. Cortina‐Borja et al. suggested that by applying differential ASIS cut‐off points of 0.5 to 2.0, which excludes the very mild and very severe patients, trial cohorts may be stratified to obtain a more homogeneous patient population that, if untreated, would change in clinical score within the typical period of a clinical trial.Two 2.5.3A key secondary endpoint was responder analysis of CGI‐I scores (responder defined as stable or improved) at 12 months compared with baseline; this was implemented as a co‐primary endpoint for the FDA. Other key secondary endpoints were: responder analysis of 5‐domain NPCCSS scores (defined as stable or improved) at month 12 vs baseline; time to worsening on 5‐domain NPCCSS (defined as the time until the patient worsened by 2 points vs baseline); proportion of patients worsening on 5‐domain NPCCSS at 6 and 12 months by 2 points on the 5‐domain NPCCSS; and change in 17‐domain NPCCSS (excluding hearing domains) at 12 months. Additional secondary endpoints included: change from baseline in Scale for Assessment and Rating of Ataxia (SARA) score at 6 and 12 months; change in the nine‐hole peg test (9‐HPT) result at 6 and 12 months; change in health‐related quality of life (HRQoL) as measured by the 5‐dimension 3‐level EuroQol questionnaire, youth version (EQ‐5D‐3L Y) proxy at 6 and 12 months; change in individual 5‐domain NPCCSS scores at month 12; and NPC clinical database (NPC‐cdb) score changes from baseline at trial time points. The NPC‐cdb score aims to reflect clinical status; an increase in score indicates a reduction in the patient's abilities. The score was calculated as defined by Stampfer et al.2.5.4HSP70 was assessed as a marker of pharmacodynamic activity of arimoclomol. Cholestane‐triol in serum and unesterified cholesterol in peripheral blood mononuclear cells (PBMCs) are measures of lipid burden in NPC. Cholestane‐triol in serum, unesterified cholesterol, and HSP70 were investigated as previously reported.2.5.5All treatment‐emergent adverse events (TEAEs) and serious TEAEs were recorded, as were any changes in results of physical examinations, vital signs, electrocardiographic results, and standard haematology and clinical chemistry findings. All events were classified using the Medical Dictionary for Regulatory Activities version 19.0. Arimoclomol inhibits the organic cation transporter 2 involved in creatinine secretion in the kidneys leading to a reversible increase in serum creatinine and/or decrease in mean creatinine clearance. Therefore, to avoid possible treatment effects on creatinine levels leading to unblinding of the investigators, visit 2 (7‐14 days after start of treatment) creatinine test results were reviewed by an independent expert only.2.6No formal statistical calculation was used to determine sample size. Efficacy endpoints were analysed in the full analysis set, which included all patients who were randomised and started study treatment . All dode facto “treatment policy” estimand. The primary MMRM model was applied on the prespecified subgroup levels with enough patients to substantiate a formal analysis. See Data for continuous outcomes including the primary endpoint were analysed under an efficacy (de jure) estimand with a mixed model for repeated measures (MMRM), with main effects factors for treatment, visit, miglustat stratum, and the corresponding baseline value and the interaction term between visit and treatment. Baseline disease severity scores were chosen as a covariate in the primary analysis to account for anticipated differences between individuals and treatment arms with regards to severity and to allow the analysis of change from baseline to mirror that of absolute values. Missing data were not imputed for the primary endpoint analysis but were imputed for sensitivity analyses. Sensitivity analyses were performed both under the primary estimand and under a 33.1The trial was conducted between June 2016 and June 2018; 52 patients were screened, and 50 were randomised  from 14 sites in nine countries. Thirty‐four patients received arimoclomol and 16 received placebo Figure .The proportion of patients completing 12 months of randomised treatment was 79.4% in the arimoclomol group and 93.8% in the placebo group Figure . In the Baseline disease characteristics and demographics of patients are detailed in Table Subgroup baseline characteristics are summarised in Table 3.23.2.1P = .046; Figure For the primary endpoint, at month 12, mean  change on the 5‐domain NPCCSS score was 0.76  for arimoclomol compared with 2.15  for placebo, corresponding to a significant treatment effect in favour of arimoclomol of −1.40  was 50.0% and 37.5% in the arimoclomol and placebo groups, respectively Table . At 12 m3.3P = .001; Figure P = .096; Figure A significant increase in HSP70 level was observed in response to 12 months of treatment with arimoclomol  with a trend of increased levels with a higher 5‐domain NPCCSS score at baseline. Lyso‐SM‐509 levels showed a correlation with serum cholestane‐triol at baseline and change to Month 12 . Patients treated with arimoclomol showed a significant reduction in plasma Lyso‐SM‐509 level at Month 12 compared with placebo ] 666 [313] ng/mL) compared with healthy controls (below 10 pg/mL); baseline concentration inversely correlated with age of neurological disease onset  of patients in the arimoclomol group and 75.0% (12/16) in the placebo group had TEAEs  treatment effect in favour of arimoclomol, corresponding to a 65% reduction in annual disease progression. The −1.40 change in the 5‐domain NPCCSS at 12 months is clinically meaningful according to the recent validation of the 5‐domain NPCCSS, which shows that a change of 1 point or greater on the scale constitutes a clinically meaningful change for caregivers/patients and physicians.P = .043) when correcting for age at first neurological symptom  and genotype. When applying the ASIS criteria of 0.5 to 2.0 (n = 21) as described by Cortina‐Borja et al.,P = .054). In addition, as expected, reducing heterogeneity by analysing only patients without double functional null mutations (n = 47) showed an enhanced signal of treatment effect of −1.61  over 12 months was in line with a cohort of patients of the same age, 2.92 points per yearAmong the secondary endpoints, the NPC‐specific secondary endpoints  provided directional support of a treatment benefit of arimoclomol towards slowing disease progression. The time to worsening was based on a predefined change threshold of 2 on the overall 5‐domain NPCCSS score. Although subsequently, and as part of the 5‐domain validation, a minimal important difference threshold of 1 point or greater has been proposed.To minimise the burden on trial patients, no cerebrospinal fluid biomarkers were taken.Biomarker effects were determined in blood and peripheral tissue. A significant increase in HSP70 was observed in response to treatment with arimoclomol, as well as a significant reduction in plasma Lyso‐SM‐509, which correlated with arimoclomol exposure. Existing literature report that increase in Lyso‐SM‐509 in NPC correlates with NPC‐specific biomarkers and disease severity 40 #43 aOverall, the effect on biomarkers supports the mechanism of action of arimoclomol in NPC that involves an amplification of the heat shock response, augmentation of lysosomal function and a reduction in accumulating lipid burden.Arimoclomol was well tolerated. The majority of TEAEs were assessed by the investigators to be related to NPC rather than the investigational product. The most common event of vomiting occurred in a similar proportion of patients in both treatment groups . Although a higher proportion of patients in the arimoclomol vs placebo group had a history of seizures/epilepsy at baseline (35.3% vs 12.5%), a similar proportion had seizure category TEAEs  in the arimoclomol (17.6%) and placebo (12.5%) groups during the trial. Creatinine elevations were an expected pharmacodynamic effect of treatment, most likely due to inhibition of organic cation transporter 2 involved in creatinine secretion in the kidneys by arimoclomol. One patient withdrew due to increased creatinine. Serious TEAEs occurred in 5/34 (14.7%) patients in the arimoclomol group compared with 5/16 (31.3%) patients in the placebo group; 2 patients in the arimoclomol group discontinued due to serious TEAEs. One patient in the arimoclomol group died, assessed as related to NPC progression.post hoc analyses were performed as a result of discussions with regulatory bodies.As with any clinical trial conducted in an ultra‐rare disorder, our study was limited by the small sample size, particularly in certain subgroups. Therefore, we acknowledge that the results are less robust than in trials with larger patient populations. The In totality, this trial demonstrated a statistically significant and clinically meaningful treatment effect of arimoclomol in NPC supported by significant and consistent effects across several disease‐ and pharmacodynamic biomarkers. These data establish the potential of arimoclomol as an efficacious and well‐tolerated disease‐modifying treatment for NPC. The treatment effect of arimoclomol was increased in subgroups that were well balanced in terms of disease characteristics. The effect on biomarkers supports the mechanism of action of arimoclomol in NPC which involves an amplification of the heat shock response, augmentation of lysosomal function and a reduction in accumulating lipid burden. The long‐term safety and efficacy of arimoclomol is currently being further explored in the ongoing open‐label extension study.Journal of Child Neurology and Child Neurology Open (Sage), as an editor of the Journal of Inherited Metabolic Disease (JIMD) and JIMD Reports (Society for the Study of Inborn Errors of Metabolism), and royalties from UpToDate (Section Editor for Pediatric Neurology). Rosalia M. Da Riol has received travel expenses and congress fees reimbursements from Sanofi Genzyme and Takeda. Mireia Del Toro has received consulting fees and speaker honoraria, travel expenses, and congress fees from Biomarin, Sanofi Genzyme, and Takeda, and is an investigator for industrial trials . Federica Deodato has received speaker honoraria from Sanofi Genzyme and Takeda, and travel reimbursement and congress fees from Actelion, Sanofi Genzyme, and Takeda. Matthias Gautschi has received consulting fees from Sanofi Genzyme, and travel expenses and congress fees from Takeda, and is an investigator for industrial trials from Horizon, Idorsia, Kaleido, Mallinckrodt, and Orphazyme A/S. Stephanie Grunewald has received consultancy funding from Hyperion, Moderna, Nutricia, Sobi, and Ultragenyx, and has participated in commercially funded research and received travel grants from Orphazyme A/S. Sabine Grønborg has received speaker honoraria from Actelion and Novo Nordisk, and travel grants from Sanofi Genzyme. Paul Harmatz has provided consulting support to and/or has received grant support from Aeglea, Alexion, Armagen, Audentis, BioMarin, Chiesi, Denali, Enzyvant, Genzyme, Homology, Inventiva, JCR, Orphazyme, Paradigm, Pfizer, PTC Therapeutics, RegenXbio, Sangamo, Shire, Sobi, and Ultragenyx. Bénédicte Héron has received consulting fees and speaker honoraria from Actelion and Takeda, travel expenses and congress fees reimbursements from Sanofi Genzyme and Takeda, and is an investigator for industrial studies and trials . Esther M. Maier has received fees from Sanofi. Saikat Santra has participated in commercially funded research, has received education and travel grants from Actelion and Orphazyme A/S, and has participated in commercially funded research from Vtesse‐Sucampo‐Mallinckrodt. Anna Tylki‐Szymanska has received speaker honoraria and/or travel grants from BioMarin, Chiesi, Sanofi Genzyme, and Takeda. Simon Day is a paid consultant to Orphazyme A/S. Anne Katrine Andreasen, Marie Aavang Geist, Nikolaj Havnsøe Torp Petersen, Linda Ingemann, Thomas Blaettler, Thomas Kirkegaard, and Christine í Dali are employees and shareholders of Orphazyme A/S. Thomas Hansen is an employee of Orphazyme A/S. Agathe Roubertie has nothing to disclose.Eugen Mengel has received investigator fees and consultant honoraria from Actelion, Alexion, Orphazyme A/S, Sanofi Genzyme, and Takeda. Marc C. Patterson has received, or will receive, research support from Actelion, Amicus, Glycomine, NIH, Orphazyme A/S, and Shire/Takeda; has served as Chair of the Scientific Advisory Committee of a Registry of Niemann‐Pick disease type C, sponsored by Actelion Pharmaceuticals, Inc.; has received consultancy fees from Amicus, Genzyme, IntraBio, Novartis, Orphazyme A/S, Takeda, and Vtesse‐Sucampo‐Mallinckrodt; holds stock in IntraBio; and receives a stipend as Editor‐in Chief of the Eugen Mengel and Christine í Dali designed the trial. All authors were involved in stages of data collection, analysis, and interpretation of the trial. Thomas Hansen conducted statistical analyses. All authors were contributors in writing the manuscript, and all read and approved the final manuscript.ClinicalTrials.gov identifier: NCT02612129) protocol and associated documentation were approved by the relevant independent ethics committees and/or institutional review boards, and written informed consent was obtained at enrolment from either the patient or their legal guardian.All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation  and with the Helsinki Declaration of 1975, as revised in 2000 (5). The trial . NPCCSS, Niemann‐Pick disease type C Clinical Severity Scale.Click here for additional data file.Supplementary Figure S2 Outlier analysis: Jackknifed MMRM of change from baseline to month 12 in 5‐domain NPCCSS (FAS). The primary analysis was repeated 50 times, omitting one patient at a time. Data shown as estimate ± SE. FAS, full analysis set; MMRM, mixed model for repeated measures; NPCCSS, Niemann‐Pick disease type C Clinical Severity Scale.Click here for additional data file.AppendixS1: Supporting InformationClick here for additional data file.


Modern society is becoming increasingly interested in people who are emotionally competent and who have the psychosocial skills required to be successful within the current social environment. However, no studies have been published on the assessment of the role of Emotional Intelligence (EI) on mental health if we assume the possible mediation of resilience and personality factors in the case of pre‐service teachers. Therefore, the aim of the study was to analyse the mediating role of resilience and personality factors in the relationship between EI and mental health of 1,022 pre‐service teachers enrolled in different educational degrees. The results found support the mediating role of resilience in the relationship between emotional intelligence and mental health; nevertheless, this was not the case when personality traits were analysed. Furthermore, it has been found that EI and resilience positively affect mental health of university students. Practical implications of this study are oriented towards an advance within the emerging trend of deepening the EI and resilience constructs among mental health care providers. Only if we understand the complex interactions between the constructs which determine people will it be possible to develop educational and health programmes responding to current needs. The World Health Organization  defines et al., There is little evidence on the demands and difficulties associated with university life from the perspective of students with mental health problems, although this perspective may be of great value in determining the best way to support these students  are highly important within the field of psychology  were entered to identify the background of the literature. No previous studies have been found concerning the possible mediation role of resilience and personality factors in that relationship and involving a sample of university students to assess the role of EI on mental health. Therefore, the aim of our study was to analyse the mediating role of resilience and personality factors in the relationship between EI and mental health of university students. In addition, the validity and internal consistency of the instruments used in this study will be analysed.The proposed model is shown schematically below see Fig. .The objectives of our study were the following:Our first objective was to test for a direct relationship between EI and Mental Health. Our second objective was to test for a mediating relationship between EI, Resilience and Mental Health. Our third was to test whether personality traits mediate the relationship between EI, Resilience and Mental Health.The study was carried out by through non‐probability convenience sampling, in which students in the Bachelor's Degrees in Education from different universities in the south of Spain were invited to participate voluntarily. We calculated the minimal sample size at 95% confidence level, with a 5% confidence interval at 80% of statistical power . Regarding to their degree, 40.09% were enrolled in Primary Education, 26.76% in Early Childhood Education, 14.80% in Social Education, 6.37% were studying for a Master's degree in Teaching, 2.94% in Speech Therapy, and 9.04% were studying for other degrees. This range includes all individuals who were studying a degree whose frequency with respect to the total is less than 1%. Regarding the course, it was found that 57.05% were enrolled in the first year, 10% were in the second, 18. 72% in the third and 14.21% in the fourth. Finally, with regard to the region, it was found that 55.88% were studying in Jaén, followed by Granada (13.03%), Córdoba (10.09%), Cádiz (4.90%), Seville (4.41%), and Málaga (4.14%), and 7.55% belonged to other regions, whose frequency with respect to the total is less than 1%.This scale is composed of 16 short sentences used to evaluate four dimensions: Self‐Emotion Appraisal (SEA), Other's Emotion Appraisal (OEA), Use of Emotion (UOE) and Regulation of Emotion (ROE). Participants in the study were asked to rate their agreement with the sentences on a five‐point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The Spanish version of Extremera, Rey, and Sánchez‐Álvarez  was usedThis instrument was designed to assess the individual's resilience through Equanimity, which refers to a balanced perspective on life and experiences. This could be seen as just sitting back and taking whatever comes, thus moderating extreme responses to adversities. This construction is often related to one's mood. RS‐14 scale validated by Sánchez‐Teruel and Robles‐Bello  was usedIt is a self‐report test which measures the big five personality traits, i.e., extraversion, agreeableness, conscientiousness, neuroticism and openness. It is made up of 44 items with liker type responses ranging from 1  to 5 . This instrument was designed simultaneously in English and Spanish. The reliability analysis (Cronbach α) of this scale was for each of the corresponding factors of: extraversion (α = 0.69), agreeableness: (α = 0.75), conscientiousness (α = 0.74), neuroticism (α = 0.75) and openness (α = 0.77).This is a 5‐item reduced mental health scale based on the SF‐36 Health Questionnaire  was asked to approve the implementation of this study and its approval was obtained, whose code is OCT.20/1.TES. Once ethical approval was obtained, the instrument was administered online, using the google form tool. In most cases, the authors of the manuscript attended classes to explain the purpose of the study and to guarantee the preservation of anonymity and ethics to potential participants. Once they agreed to participate voluntarily, they were provided with the link to the instrument. In those cases where it was not possible to attend classes, teachers were informed of the purpose of the research and provided with the researchers' contact details so that participants could contact them if they wished to do so.R programme were used for all the analyses performed within this study. In order to gain significance, the α value for all statistical tests was set to 0.05. Before factorial treatment, data was explored by data screening to analyse the assumptions required for factorial treatment and their distribution. A Confirmatory Factor Analysis (CFA) was performed to extract data resulting from each scale so as to verify the validity and internal consistency of those scales. CFA and SEM model analysis were performed using the r lavaan package Rosseel, . BecauseZKurtosis = 81.62, p < 0.01).Table r > 0.90), nor singularity (r > 0.95). To analyse linearity, homogeneity and homoscedasticity, a linear regression with obtained data and randomly created data sets was performed. Subsequently, the residues of this regression were explored. It was stated that any anomaly in the distribution of the residues would be due to the distribution of our data, given the fact that the other variable was random  = 279.935, p < .001, with CFI = 0.972, TLI = 0.967, SRMR = 0.063, RMSEA = 0.051 . The reliability of this scale was Cronbach α = 0.867 and McDonald ω = 0.868.Standardised factor loads for this scale varied between .377 (SE 0.016) and .728 (SE 0.019), for more details see Table WLEIS‐S scale showed an excellent fit  = 183.180, p < 0.001, with CFI = 0.989, TLI = 0.987, SRMR = 0.041, RMSEA = 0.029 . The reliability of this scale was Cronbach α = 0.834 and McDonald ω = 0.894.Standardised factor loads for this scale varied between 0.389 SE 0.027) and 0.890 (SE 0.024), for more details see Table 7 and 0.8et al., χ2 (892) = 7238.382, p < 0.001, with CFI = 0.746, TLI = 0.892, SRMR = 0.090, RMSEA = 0.084 . Since this scale is one of the most widely used scales in the study of personality  = 1759.512, p < 0.001, with CFI = 0.908, TLI = 0.898, SRMR = 0.067, RMSEA = 0.061 . The reliability of this scale was Cronbach's α = 0.763 and McDonald's ω = 0.823.Analysis of the original scale produced an unacceptable fit  = 55.384, p < 0.001, with CFI = 0.972, TLI = 0.944, SRMR = 0.065, RMSEA = 0.099 . The reliability of this scale was Cronbach α = 0.787 and McDonald ω = 0.792.Standardised factor loads for this scale varied between 0.501 SE 0.025) and .801 (SE 0.030), for more details see Table 5 and .80et al., χ2 (10) = 168,993, p < 0.001, with IFC = 0.935, TLI = 0.816, SRMR = 0.091, RMSEA = 0.125 .The proposed structural model is presented in Fig. Table β = 0.980), RES and mental health (MH) also showed a significant positive relationship (β = 0.230). The direct relationship between EI and MH was shown to be significant (β = 0.183). The results shown so far indicate that EI is able to predict part of the variance of students' MH scores directly. Additionally, the results shown by our explanatory model indicate that IE can also predict part of the variance of the MH scores through the mediation of the RES.The regression relationships are shown in the upper part and the correlation relationships are shown in the lower part. The significant relationships are represented in Fig. β = 0.725), whereas no personality traits showed any significant relationship with mental health (MH). These results show the close relationship between EI and the personality factors measured by the Big5 scale . But unlike the mediating role we have seen RES play in explaining MH scores, none of the personality factors helped predict MH. Finally, all personality traits showed significant and negative correlations with RES.In the case of the personality traits, all showed significant regression relationships with EI . IP: Inmaculada García‐Martínez.•Availability of data and material: Data are available on justified request to the corresponding author.•Ethics approval: This research has been approved by the Ethics Committee of the University of Jaén. Code: OCT.20/1.TES.•Consent to participate: The authors gave their consent to participate voluntarily in the research.•Acknowledgements: The research is included within the Ibero‐American Network for the Development of Professional Teaching Identity.•Funding for open access charge: University of Granada / CBUA.


Glaucomys oregonensis) and Townsend's chipmunks (Neotamias townsendii). For Humboldt's flying squirrels, these estimates support a small body of research investigating potential variation in survival among age and sex classes, but age‐ and sex‐specific survival has not been evaluated for Townsend's chipmunks. We also quantified the effects of age‐ and sex‐specific emigration on confounded estimates of apparent survival. Our estimates of juvenile flying squirrel survival were high relative to other small mammal species and estimates for both species were variable among years. We found survival differed moderately among age and sex classes for Humboldt's flying squirrels, but little among age and sex classes for Townsend's chipmunks, and that the degree to which emigration confounded apparent survival estimates varied substantially among years. Our results demonstrate that emigration can influence commonly used estimates of apparent survival. Unadjusted estimates confounded the interpretation of differences in survival between age and sex classes and masked potential temporal patterns in survival because the magnitude of adjustment varied among years. We conclude that apparent survival estimators are robust during some time periods; however, when emigration rates vary in time, the effects of emigration should be carefully considered and accounted for.Age‐ and sex‐specific survival estimates are crucial to understanding important life history characteristics, and variation in these estimates can be a key driver of population dynamics. When estimating survival using Cormack–Jolly–Seber (CJS) models, emigration is typically unknown but confounded with apparent survival. Consequently, especially for populations or age classes with high dispersal rates, apparent survival estimates are often biased low and temporal patterns in survival might be masked when site fidelity varies temporally. We used 9 years of annual mark–recapture data to estimate age‐, sex‐, and time‐specific apparent survival of Humboldt's flying squirrels ( Confounding between apparent survival and emigration is well established. However, adjusting apparent survival estimates with estimates of site fidelity separates the two temporal processes. This is important because site fidelity can be highly variable within and among species. ApparenGlaucomys oregonensis; hereafter flying squirrel) and Townsend's chipmunks , which occur sympatrically in forested habitat throughout western Oregon. Both species are important components of the avian  and mammalian prey base  a CJS estimator that jointly estimates apparent survival and recapture probability, and (2) an integrated modeling approach to estimate immigration rates, which we used to derive site‐fidelity rates and emigration‐adjusted survival. Previous research in this system established that flying squirrels have higher survival rates than chipmunks , western hemlock (Tsuga heterophylla), and Pacific silver fir , common snowberry , deer fern (Blechnum spicant), huckleberry (Vaccinium spp.), Oregon grape (Mahonia aquifolium), oxalis , salal , sword fern (Polystichum munitum), and vine maple (Acer circinatum).We collected field data annually during September–November from 2011 to 2019 on nine sites in the H. J. Andrews Experimental Forest on the west slope of the Cascade Mountains in Oregon, United States  were randomly selected from potential sites defined by three strata gradients of elevation (range = 683–1244 m) and canopy openness (range = 0–40%). The average distance among sites was 2963 m (range = 1078–5940 m). As described by Weldy et al. , at each2.3φ) and recapture probability (p) for flying squirrels and chipmunks using mark–recapture data and CJS models . This hierarchical model consists of two state processes and one observation process. The first state process, φ (the probability of surviving and remaining in the study area), was linked with the observation processes p  and emigration‐adjusted survival estimates (φadjusted).We estimated apparent annual survival  intercept for i at t, where ages ranged 1–3  for flying squirrels and 1–2 (juvenile and adult) for chipmunks, and an additive age‐ and sex‐specific (s) effect, where the effect of sex differed by age, the sex variable was defined as 0 for males and 1 for females, and we included a zero‐centered age‐, sex‐, and time‐specific random effect with standard deviation σa,s,t.We modeled variation in iy,t, where recaptures on each occasion from the second to the last trapping occasion were modeled as Bernoulli trials with success probability ip,t. To determine the most supported model structure for the observation process, we considered nine logit linear model structures (seven univariate and two bivariate) for both species to account for variation in p  during t from t = 2 to the number of occasions. The response variable  was the age‐, sex‐, and time‐specific counts of captured unmarked individuals.We used Poisson regression to estimate age‐, sex, and time‐specific immigration rates . These assumptions were reasonable on the study sites, which were randomly placed within a large, continuous, old late‐successional forest where site edges did not reflect biological edges. We then derived estimates of emigration‐adjusted survival (φadjusted), defined as:We assumed that age‐ and sex‐specific emigration at p , the most supported model. We used the relative change in WAIC (ΔWAIC) to evaluate models relative to the top‐ranking model, and because the estimate of WAIC is sensitive to the sample distribution, we estimated the 95% credible interval (CI) for the difference in WAIC from the top‐ranking model. We assessed the meaningfulness of a difference between two models based on the degree to which the CI for the difference did or did not overlap zero.For the observation process, we used the Watanabe–Akaike information criterion  flying squirrels per year at each site and 69.1 (range = 19–165 per year at each site) chipmunks per year at each site. Site‐ and year‐specific (2012–2019) counts of unmarked individuals ranged 0–12 for flying squirrels and 3–54 for chipmunks.We live trapped 117,432 trap nights and captured 1403 individual flying squirrels  and 4394 individual chipmunks . Of these, we estimated p for flying squirrel included the additive effects of a mean intercept and an individual‐level random effect (Table p of flying squirrels was 0.66 (CI: 0.51–0.73), but individual estimates varied substantially , ranged 0.25 (CI: 0.02–0.69) to 0.96 (CI: 0.76–0.99), and had a bi‐modal posterior density with a dominant peak at approximately 0.45 and a smaller secondary peak at 0.81 , and the probability of recapture of individuals after encountering traps was 0.77 (CI: 0.74–0.80). Individual p of chipmunks varied substantially , ranged 0.21 (CI: 0.01–0.62) to 0.93 (CI: 0.61–0.99), and had a bi‐modal posterior density with a dominant peak at approximately 0.50 and a much smaller secondary peak at 0.83 , but less so for chipmunks , and the species‐specific pattern of temporal variation was similar for both sexes. Flying squirrel immigration rates for females and males were low (≤0.11) for both age classes during six of eight study occasions , but were much higher (~0.22) for females and males of both age classes in 2012 and 2017 . Female flying squirrels  and chipmunks  had lower immigration rates than males of those species, respectively.Immigration rates varied among years for flying squirrels . For female flying squirrels, φ ranged 0.31 (CI: 0.12–0.55) to 0.71 (CI: 0.49–0.90) for juveniles, 0.43 (CI: 0.27–0.60) to 0.83 (CI: 0.69–0.94) for subadults, and 0.43 (CI: 0.32–0.55) to 0.84 (CI: 0.69–0.95) for adults  to 0.50 (CI: 0.29–0.73) for juveniles, 0.39 (CI: 0.19–0.61) to 0.70 (CI: 0.54–0.85) for subadults, and 0.37 (CI: 0.26–0.49) to 0.80 (CI: 0.61–0.94) for adults. Pairwise differences in φ and φadjusted among flying squirrel age and sex classes were generally small and the CIs for the pairwise differences broadly overlapped zero. We found weak evidence that female juvenile φ was lower relative to female subadult φ  and male juvenile φ was lower relative to both male subadult φ  and male adult φ . The rank order of φ among age classes was more variable among years for female flying squirrel relative to males, with all age classes represented as the minimum and maximum of the within‐year estimates at least once during 8 years  and adult (maximum 3 of 8 years) age classes . Annual φ ranged 0.13 (CI: 0.03–0.32) to 0.25 (CI: 0.09–0.50) for juvenile females and ranged 0.09 (CI: 0.02–0.19) to 0.38 (CI: 0.30–0.46) for adult females  to 0.30 (CI: 0.13–0.55) for juveniles and 0.07 (CI: 0.02–0.16) to 0.31 (CI: 0.26–0.37) for adults . Emigration adjustments ranged 0.03 (CI: 0.01–0.07) to 0.33 (CI: 0.24–0.43), varied temporally for both sexes, and were substantial during the 2012–2013 interval . Bayesian p‐values estimated from the posterior predictive checks were 0.53 for flying squirrels and 0.44 for chipmunks, indicating adequate fit for all models and suggesting that both candidate models generated data consistent with the observed data.Covariate posterior distributions were similar for both sets of priors Table . Visual 4), particularly for species with high adult survival, our finding suggests that resource availability was high during portions of the study period. Our approach also uncovered temporal variation in apparent survival biases that are likely present in a wide range of species and ecosystems.Our analysis reinforces the need to adjust for emigration in estimates of apparent survival and demonstrates that reducing biases associated with emigration can result in much higher survival estimates than expected. We also present an analytical method to parse confounded survival and movement probabilities to reduce bias in empirical apparent annual survival estimates relative to emigration‐adjusted survival. After reducing bias associated with emigration, we revealed that juvenile flying squirrel survival may be much higher than anticipated based on previous studies, as our estimates are among the highest observed for any small mammal species Table . Indeed,Our findings were consistent with previous studies that demonstrated sometimes substantial negative biases of apparent survival relative to true survival caused by confounding of survival and emigration probabilities  followed winters with high rainfall Figure . Future We were concerned that age‐ or sex‐specific variation in site‐fidelity rates would bias inferences about differences in survival. We chose to use a submodel extension to the CJS model framework that estimated age‐, sex‐, and time‐specific immigration probabilities, which we used to derive estimates of site‐fidelity rates and adjusted survival. This approach is similar to others that integrate data to estimate adjusted survival ; Data curation ; Formal analysis (lead); Investigation ; Methodology ; Visualization ; Writing – original draft (lead); Writing – review & editing . Damon B. Lesmeister: Conceptualization ; Data curation ; Funding acquisition ; Investigation ; Project administration ; Supervision ; Validation ; Writing – review & editing . Clinton W. Epps: Conceptualization ; Data curation ; Funding acquisition ; Investigation ; Project administration ; Supervision ; Validation ; Writing – review & editing .