Methods for constructing normalised reference scores: an application for assessing child development

The use of the lambda-mu-sigma (LMS) method for estimating centiles and producing reference ranges has received much interest in clinical practice, especially for assessing growth in childhood. However, this method may not be directly applicable where measures are based on a score calculated from question response categories that is bounded within finite intervals, for example, in psychometrics. In such cases, the main assumption of normality of the conditional distribution of the transformed response measurement is violated due to the presence of ceiling (and floor) effects, leading to biased fitted centiles when derived using the common LMS method. This paper describes the methodology for constructing reference intervals when the response variable is bounded and explores different distribution families for the centile estimation, using a score derived from a parent-completed assessment of cognitive and language development in 24 month-old children. Results indicated that the z-scores, and thus the extracted centiles, improved when kurtosis was also modeled and that the ceiling effect was addressed with the use of the inflated binomial distribution. Therefore, the selection of the appropriate distribution when constructing centile curves is crucial. </p

Methods for constructing normalised reference scores: an application for assessing child development

The use of the lambda-mu-sigma (LMS) method for estimating centiles and producing reference ranges has received much interest in clinical practice, especially for assessing growth in childhood. However, this method may not be directly applicable where measures are based on a score calculated from question response categories that is bounded within finite intervals, for example, in psychometrics. In such cases, the main assumption of normality of the conditional distribution of the transformed response measurement is violated due to the presence of ceiling (and floor) effects, leading to biased fitted centiles when derived using the common LMS method. This paper describes the methodology for constructing reference intervals when the response variable is bounded and explores different distribution families for the centile estimation, using a score derived from a parent-completed assessment of cognitive and language development in 24 month-old children. Results indicated that the z-scores, and thus the extracted centiles, improved when kurtosis was also modeled and that the ceiling effect was addressed with the use of the inflated binomial distribution. Therefore, the selection of the appropriate distribution when constructing centile curves is crucial. </p

Impact of varying the definition of myopia on estimates of prevalence and associations with risk factors: time for an approach that serves research, practice and policy.

BACKGROUND: Refractive error is an increasing global public health concern that requires robust and reliable research to identify modifiable risk factors and provide accurate estimates of population burden. We investigated the impact of reclassification of individuals when using different threshold values of spherical equivalent (SE) to define myopia, on estimates of frequency, distribution and associations with risk factors, to inform current international initiatives to standardise definitions. METHODS: A random sample of 1985 individuals from the 1958 British birth cohort, at age 44, had autorefraction and self-reported on educational attainment and social class.Refraction status assigned in three different models using SE: (A) moderate to high myopia -3 diopters (D) or more extreme (≤-3.00D), (B) hypermetropia +1.00D or more extreme (≥+1.00D) and (C) mild myopia using three different thresholds: -1.00D, -0.75D or -0.50D, hence reciprocal changes in definition of emmetropia. RESULTS: Frequency estimates and associations with risk factors altered significantly as the threshold value for myopia moved towards SE 0.0D: prevalence of mild myopia increased from 28% to 47%, the association with highest educational attainment attenuated and with higher social class strengthened, with changes in risk ratios of approximately 20%. CONCLUSION: Even small changes in the threshold definition of myopia (±0.25D) can significantly affect the conclusions of epidemiological studies, creating both false-positive and false-negative associations for specific risk factors. An international classification for refractive error, empirically evidenced and cognisant of the question(s) being addressed and the population(s) being studied, is needed to serve better translational research, practice and policy

Machine learning in sudden cardiac death risk prediction: a systematic review

Abstract Aims Most patients who receive implantable cardioverter defibrillators (ICDs) for primary prevention do not receive therapy during the lifespan of the ICD, whilst up to 50% of sudden cardiac death (SCD) occur in individuals who are considered low risk by conventional criteria. Machine learning offers a novel approach to risk stratification for ICD assignment. Methods and results Systematic search was performed in MEDLINE, Embase, Emcare, CINAHL, Cochrane Library, OpenGrey, MedrXiv, arXiv, Scopus, and Web of Science. Studies modelling SCD risk prediction within days to years using machine learning were eligible for inclusion. Transparency and quality of reporting (TRIPOD) and risk of bias (PROBAST) were assessed. A total of 4356 studies were screened with 11 meeting the inclusion criteria with heterogeneous populations, methods, and outcome measures preventing meta-analysis. The study size ranged from 122 to 124 097 participants. Input data sources included demographic, clinical, electrocardiogram, electrophysiological, imaging, and genetic data ranging from 4 to 72 variables per model. The most common outcome metric reported was the area under the receiver operator characteristic (n = 7) ranging between 0.71 and 0.96. In six studies comparing machine learning models and regression, machine learning improved performance in five. No studies adhered to a reporting standard. Five of the papers were at high risk of bias. Conclusion Machine learning for SCD prediction has been under-applied and incorrectly implemented but is ripe for future investigation. It may have some incremental utility in predicting SCD over traditional models. The development of reporting standards for machine learning is required to improve the quality of evidence reporting in the field

The integrin ligand SVEP1 regulates GPCR-mediated vasoconstriction via integrins alpha 9 beta 1 and alpha 4 beta 1

Background and Purpose: Vascular tone is regulated by the relative contractile state of vascular smooth muscle cells (VSMCs). Several integrins directly modulate VSMC contraction by regulating calcium influx through L-type voltage-gated Ca2+ channels (VGCCs). Genetic variants in ITGA9, which encodes the α9 subunit of integrin α9β1, and SVEP1, a ligand for integrin α9β1, associate with elevated blood pressure; however, neither SVEP1 nor integrin α9β1 has reported roles in vasoregulation. We determined whether SVEP1 and integrin α9β1 can regulate VSMC contraction. Experimental Approach: SVEP1 and integrin binding were confirmed by immunoprecipitation and cell binding assays. Human induced pluripotent stem cell-derived VSMCs were used in in vitro [Ca2+]i studies, and aortas from a Svep1+/− knockout mouse model were used in wire myography to measure vessel contraction. Key Results: We confirmed the ligation of SVEP1 to integrin α9β1 and additionally found SVEP1 to directly bind to integrin α4β1. Inhibition of SVEP1, integrin α4β1 or α9β1 significantly enhanced [Ca2+]i levels in isolated VSMCs to Gαq/11-vasoconstrictors. This response was confirmed in whole vessels where a greater contraction to U46619 was seen in vessels from Svep1+/− mice compared to littermate controls or when integrin α4β1 or α9β1 was inhibited. Inhibition studies suggested that this effect was mediated via VGCCs, PKC and Rho A/Rho kinase dependent mechanisms. Conclusions and Implications: Our studies reveal a novel role for SVEP1 and the integrins α4β1 and α9β1 in reducing VSMC contractility. This could provide an explanation for the genetic associations with blood pressure risk at the SVEP1 and ITGA9 loci

The Impact of the Financial Crisis on Lifestyle Health Determinants Among Older Adults Living in the Mediterranean Region: The Multinational MEDIS Study (2005-2015).

Objectives: By the end of the 2000s, the economic situation in many European countries started to deteriorate, generating financial uncertainty, social insecurity and worse health status. The aim of the present study was to investigate how the recent financial crisis has affected the lifestyle health determinants and behaviours of older adults living in the Mediterranean islands. Methods: From 2005 to 2015, a population-based, multi-stage convenience sampling method was used to voluntarily enrol 2749 older adults (50% men) from 20 Mediterranean islands and the rural area of the Mani peninsula. Lifestyle status was evaluated as the cumulative score of four components (range, 0 to 6), that is, smoking habits, diet quality (MedDietScore), depression status (Geriatric Depression Scale) and physical activity. Results: Older Mediterranean people enrolled in the study from 2009 onwards showed social isolation and increased smoking, were more prone to depressive symptoms, and adopted less healthy dietary habits, as compared to their counterparts participating earlier in the study (p<0.05), irrespective of age, gender, several clinical characteristics, or socioeconomic status of the participants (an almost 50% adjusted increase in the lifestyle score from before 2009 to after 2009, p<0.001). Conclusions: A shift towards less healthy behaviours was noticeable after the economic crisis had commenced. Public health interventions should focus on older adults, particularly of lower socioeconomic levels, in order to effectively reduce the burden of cardiometabolic disease at the population level