Development and validation of AIIMS modified INCLEN diagnostic instrument for epilepsy in children aged 1 month-18 years

The development of a smartphone application to help manage epilepsy in resource-limited settings

PURPOSE

Epilepsy is treatable but in low- and middle-income countries (LMICs) it goes untreated with dire consequences for people with it and their families. There are not enough available doctors to treat it so it has been suggested that non-physician health workers (NPHWs) take a role in diagnosis and management. Tools will be essential to help them. A smartphone application (app) for episode diagnosis has proved safe and effective; this paper describes an app for epilepsy management.

METHODS

Questions were devised which captured temporal characteristics of episodes, diagnosis of episodes, seizure types, and epilepsy type, together with information on previous investigations, treatment, drug reactions, and current treatment. For untreated patients a management plan was suggested. The app generated a summary which could be sent to a remote specialist for advice. The finished app was evaluated in 23 people presenting with possible epilepsy by four doctors in training and one NPHW; its summary was compared to face-to-face evaluation by a neurologist.

RESULTS

The app was correct in 22 of 23 (96 %) patients for episode diagnosis, 2 of 2 for symptomatic seizures,18/20 (90 %) for epilepsy type and 9/10 (90 %) for treatment suggestion in untreated patients. The app took less than 15 min to complete.

CONCLUSION

The initial results suggest that this management app is a worthwhile tool to help inexpert doctors or NPHWs manage suspected epilepsy. Its accuracy is well within reported inter-observer agreement. In its present form it requires input from a remote epilepsy specialist. This combination is a potential solution to managing epilepsy in LMICs.

Managing Epilepsy by Telemedicine in Resource-Poor Settings

Epilepsy is a common and treatable disease; in rich countries the expectation is that two-thirds of people will have their seizure episodes controlled on medication. In low- and middle-income countries (LMICs) however most people are not on treatment either because no doctors live near them or the logistics of affordable drug supply is absent. People with epilepsy then are prone to the bad effects of this disease—death, disfigurement from accidents and burns, and social problems due to the stigma with which the disease is associated. So this represents a failure of conventional face-to-face medicine. Might a telemedicine approach do better? The World Health Organization has suggested that non-physician health workers are empowered to diagnose and manage epilepsy; to do this they will need considerable medical support, which might be provided by telemedicine through the telephone, smartphone applications or a combination. This paper sets out what telemedicine does at present for people with epilepsy in LMICs and suggests how it might be developed in the future.

Gut Microbial Dysbiosis in Indian Children with Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a term associated with a group of neurodevelopmental disorders. The etiology of ASD is not yet completely understood; however, a disorder in the gut-brain axis is emerging as a prominent factor leading to autism. To identify the taxonomic composition and markers associated with ASD, we compared the fecal microbiota of 30 ASD children diagnosed using Childhood Autism Rating Scale (CARS) score, DSM-5 approved AIIMS-modified INCLEN Diagnostic Tool for Autism Spectrum Disorder (INDT-ASD), and Indian Scale for Assessment of Autism (ISAA) tool, with family-matched 24 healthy children from Indian population using next-generation sequencing (NGS) of 16S rRNA gene amplicon. Our study showed prominent dysbiosis in the gut microbiome of ASD children, with higher relative abundances of families Lactobacillaceae, Bifidobacteraceae, and Veillonellaceae, whereas the gut microbiome of healthy children was dominated by the family Prevotellaceae. Comparative meta-analysis with a publicly available dataset from the US population consisting of 20 ASD and 20 healthy control samples from children of similar age, revealed a significantly high abundance of genus Lactobacillus in ASD children from both the populations. The results reveal the microbial dysbiosis and an association of selected Lactobacillus species with the gut microbiome of ASD children.

Neurodevelopmental disorders in children aged 2-9 years: Population-based burden estimates across five regions in India

BACKGROUND

Neurodevelopmental disorders (NDDs) compromise the development and attainment of full social and economic potential at individual, family, community, and country levels. Paucity of data on NDDs slows down policy and programmatic action in most developing countries despite perceived high burden.

METHODS AND FINDINGS

We assessed 3,964 children (with almost equal number of boys and girls distributed in 2-<6 and 6-9 year age categories) identified from five geographically diverse populations in India using cluster sampling technique (probability proportionate to population size). These were from the North-Central, i.e., Palwal (N = 998; all rural, 16.4% non-Hindu, 25.3% from scheduled caste/tribe [SC-ST] [these are considered underserved communities who are eligible for affirmative action]); North, i.e., Kangra (N = 997; 91.6% rural, 3.7% non-Hindu, 25.3% SC-ST); East, i.e., Dhenkanal (N = 981; 89.8% rural, 1.2% non-Hindu, 38.0% SC-ST); South, i.e., Hyderabad (N = 495; all urban, 25.7% non-Hindu, 27.3% SC-ST) and West, i.e., North Goa (N = 493; 68.0% rural, 11.4% non-Hindu, 18.5% SC-ST). All children were assessed for vision impairment (VI), epilepsy (Epi), neuromotor impairments including cerebral palsy (NMI-CP), hearing impairment (HI), speech and language disorders, autism spectrum disorders (ASDs), and intellectual disability (ID). Furthermore, 6-9-year-old children were also assessed for attention deficit hyperactivity disorder (ADHD) and learning disorders (LDs). We standardized sample characteristics as per Census of India 2011 to arrive at district level and all-sites-pooled estimates. Site-specific prevalence of any of seven NDDs in 2-<6 year olds ranged from 2.9% (95% CI 1.6-5.5) to 18.7% (95% CI 14.7-23.6), and for any of nine NDDs in the 6-9-year-old children, from 6.5% (95% CI 4.6-9.1) to 18.5% (95% CI 15.3-22.3). Two or more NDDs were present in 0.4% (95% CI 0.1-1.7) to 4.3% (95% CI 2.2-8.2) in the younger age category and 0.7% (95% CI 0.2-2.0) to 5.3% (95% CI 3.3-8.2) in the older age category. All-site-pooled estimates for NDDs were 9.2% (95% CI 7.5-11.2) and 13.6% (95% CI 11.3-16.2) in children of 2-<6 and 6-9 year age categories, respectively, without significant difference according to gender, rural/urban residence, or religion; almost one-fifth of these children had more than one NDD. The pooled estimates for prevalence increased by up to three percentage points when these were adjusted for national rates of stunting or low birth weight (LBW). HI, ID, speech and language disorders, Epi, and LDs were the common NDDs across sites. Upon risk modelling, noninstitutional delivery, history of perinatal asphyxia, neonatal illness, postnatal neurological/brain infections, stunting, LBW/prematurity, and older age category (6-9 year) were significantly associated with NDDs. The study sample was underrepresentative of stunting and LBW and had a 15.6% refusal. These factors could be contributing to underestimation of the true NDD burden in our population.

CONCLUSIONS

The study identifies NDDs in children aged 2-9 years as a significant public health burden for India. HI was higher than and ASD prevalence comparable to the published global literature. Most risk factors of NDDs were modifiable and amenable to public health interventions.