Real-world Independent Testing of e-ASPECTS Software (RITeS): Checklist for Statistical Analysis Plan

Statistical Analysis Plan reporting checklist as per: https://www.equator-network.org/reporting-guidelines/guidelines-for-the-content-of-statistical-analysis-plans-in-clinical-trials/ . ## Background - RITeS project ## The Real-world Independent Testing of e-ASPECTS Software (RITeS) project will test commercially available AI software that claims to provide automated assessment of CT brain imaging for patients with acute stroke. RITeS will independently compare the results of e-ASPECTS and e-CTA software against the current gold-standard, expert human interpretation using a large representative sample of CT imaging collected in several clinical trials of acute stroke.Mair, Grant. (2020). Real-world Independent Testing of e-ASPECTS Software (RITeS): Checklist for Statistical Analysis Plan, [text]. University of Edinburgh. College of Medicine & Veterinary Medicine. https://doi.org/10.7488/ds/2803

"Davies2018_OPEN_DATASET_summary_results.txt" - Data supporting paper Davies et al. "Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function."

Data supporting paper Davies et al "Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function." Nature Communications DOI: 10.1038/s41467-018-04362-x . Open dataset summary results (5 cohorts removed; details in README) ; General Cognitive Function N = 282,014. ## Note re working with data ## The file "Davies2018_OPEN_DATASET_summary_results.txt" contains over twelve million rows. Users will encounter difficulties if they attempt to view the content using Notepad++ or Microsoft Notepad. Microsoft Excel 2016 will not display all rows. This space-delimited text file contains seven columns, with a header row, which are listed in the readme file. ## Note re other copy ## The file "Davies2018_OPEN_DATASET_summary_results.txt" is identical to the file of the same name previously made available on the website of the Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE) http://www.ccace.ed.ac.uk/node/335 as part of the zip archive "Davies_NC_2018_OPEN_DATASET.zip" .Davies, G; Lam, M; Lencz, T; Deary, IJ. (2019). "Davies2018_OPEN_DATASET_summary_results.txt" - Data supporting paper Davies et al. "Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.", [dataset]. University of Edinburgh. Centre for Cognitive Ageing and Cognitive Epidemiology. https://doi.org/10.7488/ds/2558

'DAVIES_NC_2018' - Data supporting paper Davies et al. "Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function."

Data supporting paper Davies et al. "Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function." Nature Communications DOI: 10.1038/s41467-018-04362-x . UK Biobank only summary results; Reaction Time N = 330,069; Verbal Numerical Reasoning N = 168,033. ## Note ## The files "Davies2018_UKB_RT_summary_results_29052018.txt" and "Davies2018_UKB_VNR_summary_results_29052018.txt" are identical to the two files of the same names previously available on the website of the Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE) http://www.ccace.ed.ac.uk/node/335 as part of the zip archive "Davies_NC_2018.zip".Davies, G; Lam, M; Lencz, T; Deary, IJ. (2019). 'DAVIES_NC_2018' - Data supporting paper Davies et al. "Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.", [dataset]. University of Edinburgh. Centre for Cognitive Ageing and Cognitive Epidemiology. https://doi.org/10.7488/ds/2559

RESTART | planned secondary analyses

List of planned post hoc analysesSalman, Rustam Al-Shahi. (2019). RESTART | planned secondary analyses, 2013-2018 [text]. University of Edinburgh. https://doi.org/10.7488/ds/2551

Gene expression analysis of subpopulations of mouse embryonic stem cells sorted based on Id1 and Nanog expression

Overall design: Id1-Venus Nanog-tagRFP (IVNR) reporter mouse ES cells cultured in LIF+FCS were sorted into Nanog-tagRFP-high, Id1-Venus-high, or double low subpopulations. Unsorted IVNR cells cultured in LIF+FCS, as well as Id1-Venus (Id1V) reporter ES cells cultured in 2i and in 2i+LIF were included as controls. All samples were collected in duplicate. Total 12 samples. Experiment type: Expression profiling by array.Analysis of gene expression in sorted subpopulations of mouse embryonic stem cells. We set out to investigate whether expression of Id1 in Nanog-low cells affected the expression of pluripotency factors and signalling molecules.Malaguti M, Lowell S, 2018, Gene expression analysis of subpopulations of mouse embryonic stem cells sorted based on Id1 and Nanog expression, Gene Expression Omnibus, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10822

Motyl AAL, et al. (2020). Pre-symptomatic developmental phenotypes in Spinal Muscular Atrophy

Spinal muscular atrophy (SMA) is a leading genetic cause of infant death, characterised primarily by a loss of lower motor neurons. SMA is caused by mutations in the survival motor neuron 1 (SMN1) gene. New SMN-restoring therapies for SMA have emerged in recent years; however, data from both pre-clinical and clinical studies demonstrate that there is a limited therapeutic time-window for them to be effective. Moreover, it is now clear that peripheral organs and tissues can also be affected by the disease. To better understand the earliest changes occurring during SMA, with implications for defining the optimum time and location of therapy delivery, we undertook a detailed anatomical, histological and molecular analysis of pre-symptomatic, prenatal changes occurring in a mouse model of SMA. We generated 3D-renderings of whole embryos at embryonic day (E)14.5 using micro-computed tomography (µCT). These analyses showed that E14.5 SMA embryos are significantly smaller than littermate controls, indicative of a general developmental delay. Cardiac ventricles were smaller in SMA heart, whilst liver and brain volumes remained unaffected. Morphometric and histological analyses showed no overt structural defects indicative of degenerative pathology in any of the organs examined. We then performed a comparative proteomics' screen of spinal cord, brain, liver, skeletal muscle and heart in SMA and control mice using Tandem Mass Tagging mass spectrometry. This revealed significant molecular perturbations in all organs examined, with the liver showing the greatest magnitude of change. Notably, we found a lack of overlap in affected proteins and molecular pathways between organs, highlighting tissue-specific prenatal molecular phenotypes in SMA. Together, our data demonstrate that considerable changes are already present across numerous tissues and organs at an early, pre-symptomatic stage in SMA mice, suggesting that there is a significant developmental component to SMA pathogenesis.Motyl, Anna Abigail Lydia; Gillingwater, Thomas; Wishart, Thomas. (2020). Motyl AAL, et al. (2020). Pre-symptomatic developmental phenotypes in Spinal Muscular Atrophy, [dataset]. University of Edinburgh. College of Medicine and Veterinary Medicine. https://doi.org/10.7488/ds/2776

Association between the Edinburgh CT and genetic diagnostic criteria for lobar intracerebral haemorrhage (ICH) associated with cerebral amyloid angiopathy and the risk of recurrent ICH: outline protocol for a population-based analysis, and external validation in a hospital-based cohort

This is an outline protocol for a study assessing the association between the Edinburgh CT and genetic diagnostic criteria for lobar intracerebral haemorrhage (ICH) associated with cerebral amyloid angiopathy and the risk of recurrent ICH.Rodrigues, Mark; Seiffge, David; Werring, David; Al-Shahi Salman, Rustam. (2018). Association between the Edinburgh CT and genetic diagnostic criteria for lobar intracerebral haemorrhage (ICH) associated with cerebral amyloid angiopathy and the risk of recurrent ICH: outline protocol for a population-based analysis, and external validation in a hospital-based cohort, [text]. https://doi.org/10.7488/ds/7479

Data for "A smartphone-based test for the assessment of attention deficits in delirium: a case-control diagnostic test accuracy study in older hospitalised patients."

Paper: A smartphone-based test for the assessment of attention deficits in delirium: a case-control diagnostic test accuracy study in older hospitalised patients. ABSTRACT ## Background ## Delirium is a common and serious acute neuropsychiatric syndrome which is often missed in routine clinical care. Inattention is the core cognitive feature. Diagnostic test accuracy (including cut-points) of a smartphone Delirium App (DelApp) for assessing attention deficits was assessed in older hospital inpatients. ## Methods ## This was a case-control study of hospitalised patients aged ≥65 years with delirium (with or without pre-existing cognitive impairment), who were compared to patients with dementia without delirium, and patients without cognitive impairment. Reference standard delirium assessment, which included a neuropsychological test battery, was based on Diagnostic and Statistical Manual of Mental Disorders-5 criteria. A separate blinded assessor administered the DelApp arousal assessment (score 0-4) and attention task (0-6) yielding an overall score of 0 to 10 (lower scores indicate poorer performance). Analyses included receiver operating characteristic curves and sensitivity and specificity. Optimal cut-points for delirium detection were determined using Youden's index. ## Results ## A total of 187 patients were recruited, mean age 83.8 (range 67-98) years, 152 (81%) women; n=61 with delirium; n=61 with dementia without delirium; and n=65 without cognitive impairment. Patients with delirium performed poorly on the DelApp (median score=4/10; inter-quartile range 3.0, 5.5) compared to patients with dementia (9.0; 5.5, 10.0) and those without cognitive impairment (10.0; 10.0, 10.0). Area under the curve for detecting delirium was 0.89 (95% Confidence Interval 0.84, 0.94). At an optimal cut-point of <8, sensitivity was 91.7% (84.7%, 98.7%) and specificity 74.2% (66.5%, 81.9%) for discriminating delirium from the other groups. Specificity was 68.3% (56.6%, 80.1%) for discriminating delirium from dementia (cut-point <6). ## Conclusion ## Patients with delirium (with or without pre-existing cognitive impairment) perform poorly on the DelApp compared to patients with dementia and those without cognitive impairment. A cut-point of <8/10 is suggested as having optimal sensitivity and specificity. The DelApp is a promising tool for assessment of attention deficits associated with delirium in older hospitalised adults, many of whom have prior cognitive impairment, and should be further validated in representative patient cohorts.Tieges, Zoe; MacLullich, Alasdair. (2020). Data for "A smartphone-based test for the assessment of attention deficits in delirium: a case-control diagnostic test accuracy study in older hospitalised patients.", [dataset]. University of Edinburgh. College of Medicine & Veterinary Medicine. Department of Geriatric Medicine. https://doi.org/10.7488/ds/2752