Using Critical Success Index or Gilbert Skill Score as composite measures of positive predictive value and sensitivity in diagnostic accuracy studies: Weather forecasting informing epilepsy research.

The Critical Success Index (CSI) and Gilbert Skill score (GS) are verification measures that are commonly used to check the accuracy of weather forecasting. In this article, we propose that they can also be used to simplify the joint interpretation of positive predictive value (PPV) and sensitivity estimates across diagnostic accuracy studies of epilepsy data. This is because CSI and GS each provide a single measure that takes the weather forecasting equivalent of PPV and sensitivity into account. We have re-analysed data from our recent systematic review of diagnostic accuracy studies of administrative epilepsy data using CSI and GS. We summarise the results and benefits of this approach.

Subcortical nuclei volumes are associated with cognition in children post-convulsive status epilepticus: Results at nine years follow-up.

PURPOSE: The purpose of the present study was to investigate the relationship between subcortical nuclei volume and cognition in children with post-convulsive status epilepticus (CSE). METHODS: Structural T1-weighted magnetic resonance imaging (MRI) scans (Siemens Avanto, 1.5 T) and neuropsychological assessments (full-scale intelligence quotient (FSIQ) and Global Memory Scores (GMS)) were collected from subjects at a mean 8.5 years post-CSE (prolonged febrile seizures (PFS), n = 30; symptomatic/known, n = 28; and other, n = 12) and from age- and sex-matched healthy controls (HC). Subjects with CSE were stratified into those with lower cognitive ability (LCA) (CSE+, n = 22) and those without (CSE-, n = 48). Quantitative volumetric analysis using Functional MRI of the Brain Software Library (FSL) (Analysis Group, FMRIB, Oxford) provided segmented MRI brain volumes. Univariate analysis of covariance (ANCOVA) was performed to compare subcortical nuclei volumes across subgroups. Multivariable linear regression was performed for each subcortical structure and for total subcortical volume (SCV) to identify significant predictors of LCA (FSIQ <85) while adjusting for etiology, age, socioeconomic status, sex, CSE duration, and intracranial volume (ICV); Bonferroni correction was applied for the analysis of individual subcortical nuclei. RESULTS: Seventy subjects (11.8 ±â€¯3.4 standard deviation (SD) years; 34 males) and 72 controls (12.1 ±â€¯3.0SD years; 29 males) underwent analysis. Significantly smaller volumes of the left thalamus, left caudate, right caudate, and SCV were found in subjects with CSE+ compared with HC, after adjustment for intracranial, gray matter (GM), or cortical/cerebellar volume. When compared with subjects with CSE-, subjects with CSE+ also had smaller volumes of the left thalamus, left pallidum, right pallidum, and SCV. Individual subcortical nuclei were not associated, but SCV was associated with FSIQ (p = 0.005) and GMS (p = 0.014). Intracranial volume and etiology were similarly predictive. CONCLUSIONS: Nine years post-CSE, SCV is significantly lower in children who have LCA compared with those that do not. However, in this cohort, we are unable to determine whether the relationship is independent of ICV or etiology. Future, larger scale studies may help tease this out.

The accuracy of using administrative healthcare data to identify epilepsy cases: A systematic review of validation studies.

Our objective was to undertake a systematic review ascertaining the accuracy of using administrative healthcare data to identify epilepsy cases. We searched MEDLINE and Embase from 01/01/1975 to 03/07/2018 for studies evaluating the diagnostic accuracy of routinely collected healthcare data in identifying epilepsy cases. Any disease coding system in use since the International Classification of Diseases, Ninth Revision (ICD-9) was permissible. Two authors independently screened studies, extracted data, and quality-assessed studies. We assessed positive predictive value (PPV), sensitivity, negative predictive value (NPV), and specificity. The primary analysis was a narrative synthesis of review findings. Thirty studies were included, published between 1989 and 2018. Risks of bias were low, high, and unclear in 4, 14, and 12 studies, respectively. Coding systems included ICD-9, ICD-10, and Read Codes, with or without antiepileptic drugs (AEDs). PPVs included ranges of 5.2%-100% (Canada), 32.7%-96.0% (USA), 47.0%-100% (UK), and 37.0%-88.0% (Norway). Sensitivities included ranges of 22.2%-99.7% (Canada), 12.2%-97.3% (USA), and 79.0%-94.0% (UK). Nineteen studies contained at least one algorithm with a PPV >80%. Sixteen studies contained at least one algorithm with a sensitivity >80%. PPV was highest in algorithms consisting of disease codes (ICD-10 G40-41, ICD-9 345) in combination with one or more AEDs. The addition of symptom codes to this (ICD-10 R56; ICD-9 780.3, 780.39) lowered PPV. Sensitivity was highest in algorithms consisting of symptom codes with one or more AEDs. Although using AEDs alone achieved high sensitivities, the associated PPVs were low. Most NPVs and specificities were >90%. We conclude that it is reasonable to use administrative data to identify people with epilepsy (PWE) in epidemiological research. Studies prioritizing high PPVs should focus on combining disease codes with AEDs. Studies prioritizing high sensitivities should focus on combining symptom codes with AEDs. We caution against the use of AEDs alone to identify PWE.

Characteristics of NPS use in patients admitted to acute psychiatric services in Southeast Scotland: a retrospective cross-sectional analysis following public health interventions.

OBJECTIVES: Assess the impact of selective prohibition and seizure of novel psychoactive substances (NPS) supply on NPS use prevalence within psychiatric admissions and evaluate demographic characteristics of current NPS users. DESIGN: A 6-month retrospective cross-sectional analysis of discharge letters between 1 October 2015 and 31 March 2016. SETTING: General psychiatry inpatients and intensive home treatment team (IHTT) community patients at a psychiatric hospital in a Scottish city. PARTICIPANTS: All participants were between the ages of 18 and 65 years. After application of exclusion criteria, 473 discharge letters of general psychiatry patients were deemed suitable for analysis and 264 IHTT patient discharge letters were analysed. INTERVENTIONS: A nationwide temporary class drug order (TCDO) was placed on 10 April 2015 reclassifying methylphenidate-related compounds as class B substances. On 15 October 2015, local forfeiture orders were granted to trading standards permitting the seizure of NPS supplies. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome measure was to determine the prevalence of NPS use in two cohorts. Second, demographic features of patients and details regarding their psychiatric presentation were analysed. RESULTS: The prevalence of NPS use in general psychiatry and IHTT patients was 6.6% and 3.4%, respectively. Inpatients using NPS compared with non-users were more likely to be men (OR 2.92, 95% CI 1.28 to 6.66, P=0.009), have a forensic history (OR 5.03, CI 2.39 to 10.59, P<0.001) and be detained under an Emergency Detention Certificate (OR 3.50, CI 1.56 to 7.82, P=0.004). NPS users were also more likely to be diagnosed under International Statistical Classification of Diseases and Related Health Problems, Version 10, F10-19 (OR 9.97, CI 4.62 to 21.49, P<0.001). CONCLUSIONS: Compared with previous work, psychiatric inpatient NPS use has fallen. NPS continue to be used by a demographic previously described resulting in presentations consistent with a drug-induced psychosis and at times requiring detention under the Mental Health Act. Further research is required to evaluate the effectiveness of the recent prohibition of all NPS.