1. Top of page
  2. Abstract
  3. What this paper adds
  4. Method
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

Aim  To identify predictors of seizure control in newly presenting children with epilepsy in countries with limited resources.

Method  Three hundred and ninety children (273 males, 117 females) aged 2 months to 15 years with newly diagnosed epilepsy were enrolled prospectively at first visit to the multidisciplinary clinic at the children’s hospital in Dhaka, Bangladesh. Data about seizures, motor disability, psychomotor development, and electroencephalography were obtained. Regular monitoring of antiepileptic drug treatment was continued at least for one year. Associations between seizure control and potential predictors were determined by multivariate analysis.

Results  Three hundred and ninety children were enrolled in 6 months, of whom over 60% were from low-income families, 60% had onset at under 1 year, 74% had more than one seizure per week, 69% a single-seizure type, and 38% a history of delayed onset of breathing at birth. Cognitive deficits (IQ<70; 58%) and/or motor (significant limitation of daily living activities; 47%) deficits were common. After 1 year of regular treatment, seizure control was good (seizure freedom) in 53%, and poor (at least one seizure in the last 3mo of follow-up) in 47%. The predictors of poor seizure control were an IQ<70, associated motor disability, multiple seizure types, and a history of cognitive regression (1.9 times more likely to have poor seizure control).

Interpretation  Seizure control can be predicted using three clinical factors (motor disability, cognitive impairment, and multiple seizure types) at the first clinic visit. Such predictors assist the development of referral plans and management guidelines for childhood epilepsies in resource-poor countries.

What this paper adds

  1. Top of page
  2. Abstract
  3. What this paper adds
  4. Method
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References
  •  Adverse clinical factors for seizure control can be identified at presentation, namely motor disability, cognitive impairment, and multiple seizure types.
  •  Multidisciplinary services, including cognitive and motor assessment, should be considered as essential parts of epilepsy management in resource-poor countries.

The management of childhood epilepsy in countries with limited resources has several specific problems. These include lack of medical resources, misunderstanding of the nature of epilepsy, stigmatization, large treatment gaps (i.e. a high percentage of the target population not receiving medication but often a high level of use of traditional healers), and a lack of understanding of the priorities of the users by those seeking to provide treatment. All of these issues arise in the management of epilepsy in children in Bangladesh. In consultation with parents, we formed the view that the ability to predict seizure control with future treatment can be useful. First, it provides an audit so that if the control is widely discrepant from that predicted, a reason may be sought (e.g. seizures were not epileptic, antiepileptic drugs were not taken). Second, it gives the family and patient an expectation of what antiepileptic drugs can achieve and whether they are essential to management. Third, it allows an approximate cost–benefit analysis to be performed. These may be useful in any setting, but in a country with limited resources (e.g. Bangladesh) this may allow doctors and carers to deploy their resources more effectively. The second broad issue raised was the high rate of additional problems of development and behaviour that occurs in children with epilepsy.1

Our previous retrospective study from a specialized epilepsy clinic within a child development centre in Dhaka Shishu (Children’s) Hospital, Bangladesh, a 400-bed national children’s hospital, reported freedom from seizures in 53% after appropriate medical treatment for 1 to 3 years.2 Five predictive factors were independently associated with poor seizure control, i.e. at least one seizure in the last 3 months: multiple seizure types (generalized tonic–clonic seizures and myoclonic or drop attacks; odds ratio [OR] 4.4, p<0.001); high seizure rate (more than one attack per week; OR 3.4, p<0.005); an IQ<70 on psychometric test (OR 2.49, p<0.01); associated motor disability (OR 2.1, p<0.02); and abnormal electroencephalogram (EEG; OR 4.1, p<0.001). After logistic regression analysis, three predictors remained most significant: multiple seizure type (p<0.001), cognitive impairment (p<0.01), and abnormal EEG (p<0.01).

The present study prospectively enrolled children with newly diagnosed epilepsy from the general outpatients departments of Dhaka Shishu (Children’s) Hospital to determine if the retrospective study predictors of poor seizure control were confirmed and therefore applicable for early referral and optimum seizure management at presentation. The model of care also identified early additional developmental impairments and encouraged comprehensive management.


  1. Top of page
  2. Abstract
  3. What this paper adds
  4. Method
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References


The study was conducted at the outpatients’ services of the child development centre in Dhaka Shishu (Children’s) Hospital. For most, it would be the first contact with services for seizures and related problems as none are usually available at primary and secondary level. Most families were self-referred. A child-health physician with basic training in child neurology, a developmental therapist trained in physiotherapy, occupational and speech therapy within a developmental framework, and a child psychologist were the core team members of the service. They received 1 month’s training in childhood epilepsy, associated psychomotor comorbidities, and their management. Weekly meetings with the principal investigator were used to monitor clinical information, diagnosis, drug treatment, and for problem-solving.

Children aged 2 months to 15 years, presenting with two or more unprovoked seizures with or without motor and/or cognitive comorbidities, were included. Families were classified by monthly income in taka (1 US dollar≈70 taka), as low (<10 000 taka per mo), middle (10 000–20 000 taka per mo), and high (more than 20 000 taka per mo);2 residence was classified as urban or rural. Birth history included place and mode of delivery; ‘perinatal asphyxia’ was defined in this setting as a failure to start regular respiration within a minute of birth because that was the available description3 and thus not necessarily including a neonatal encephalopathy.4

General and neurodevelopmental examination findings were collected on a pre-coded, structured form. Details of seizures were recorded as ‘age at onset’, which was categorized as ‘early’ when unprovoked seizures started at or before 12 months of age, or ‘late’; ‘seizure type(s)’ were categorized as ‘single’ or ‘multiple’ type seizures when there was a history of more than one type of seizure such as generalized tonic–clonic and myoclonic or head-drops or absences; ‘rate of seizures’ was categorized as ‘high’ when there were one or more attacks per week.

Epilepsies were classified for descriptive purposes using the International League Against Epilepsy syndromic classification current at the time of the study.5–9 Based on examination findings, EEG, and available neuroimaging features, seizures were categorized as ‘generalized’ or ‘partial/focal’, and epilepsies as ‘idiopathic’, ‘symptomatic or cryptogenic’, and ‘unclassifiable’. A history of unprovoked, repeated seizures among the siblings, parents, grandparents, and paternal or maternal cousins was coded as a positive family history.

Comorbidities were recorded as ‘motor disability’ when a motor functional deficit caused significant limitation of daily living activities, and cognitive impairment when the IQ was <70.

Psychometric assessment was performed close to enrolment using standardized age-appropriate assessments: the Bayley Scales of Infant Development,10 Wechsler Intelligence Scales for Children, revised,11 and the Independent Behaviour Assessment Scale,12 which had been adapted for use in Bangladesh.

A routine digital EEG (a minimum of 30min with photic stimulation and hyperventilation where possible but without sleep) was recorded and reported independently by two paediatric neurophysiologists, one of whom was blind to the child’s clinical data. The interrater reliability was very good on an unweighted kappa measure (κ=0.93; 95% confidence interval [CI] 0.90–0.95;13Table I). EEG findings were categorized as ‘normal’ and ‘abnormal’ for age and state of arousal. Abnormal brain activities were subcategorized for further descriptive analysis into (1) epileptiform discharges (discharges with spike, sharp, and slow wave complexes) with normal background activities between discharges, (2) non-epileptic background abnormality (diffuse or localized irregular slow waves, excessive beta waves, unorganized non-reactive background activities), and (3) both (epileptiform discharges with background abnormality). Neuroimaging, such as ultrasonography, computed tomography or magnetic resonance imaging of the brain, was performed when clinically indicated and financially feasible but was not used for predicting seizure control.

Table I.   Kappa analysis of EEGs to determine the interrater reliability (383 EEGs were reported by one blinded neurophysiologist and one unblinded)
Blinded neurophysiologistUnblinded neurophysiologistTotalCI
  1. EEG, electroencephalogram; CI, confidence interval.

Total  383 

Treatment with antiepileptic drugs was given following standard treatment procedures for specific seizures and epilepsy syndromes.14,15 Locally available antiepileptic drugs, phenobarbital, carbamazepine, sodium valproate, phenytoin, nitrazepam, and clonazepam were used. In addition, short courses of oral prednisolone were used for infantile spasms.14 Parents with children having prolonged generalized tonic–clonic seizures were trained to use rectal diazepam.16–19 Follow-up was for a minimum of 12 months, at 1- to 3-month intervals depending on the seizure rate and travel distances.

Compliance was encouraged in various ways: for example, travel costs were provided to very poor families, and telephone or postal communications and home visits were used when these failed. Monitoring of medication was by regular follow-up, tablet counts, and, very occasionally, for example when there was no response in seizure rate, by blood levels. Family members were taught the importance of regular medication and follow-up in epilepsy. Diaries of seizures were maintained by families.


Seizure control, the main outcome measure, was categorized as ‘good’ when a child was seizure-free, and ‘poor’ when any seizure was reported during the last quarter of the 12-month follow-up period.

Statistical analysis

All analyses used Stata Intercooled (StataCorp, version 12). Of the 390 children originally enrolled, 71 were lost to follow-up. The clinical features in the enrolled and lost to follow-up groups were compared to investigate whether there were differences between the groups that could introduce important bias. Chi-squared analyses were used for categorical data, and a t-test was used for continuous data. Significant predictors of outcome were investigated using logistic regression. The OR (which approximates a relative risk20) and 95% CIs were calculated using bootstrapping with 100 replications.21 We analysed this 10 times to identify weak and strong predictors of outcome. Significant predictors were divided into strong (significant [p<0.05] in each of the 10 analyses) and weak (significant in fewer than all 10 analyses).22 As the CIs differ on each analysis, only ORs are presented. Potential predictors of seizure outcome included in the model were (1) ‘early onset’, (2) ‘multiple seizures types’, (3) ‘high rate of seizures’, (4) severe epilepsy syndrome with regression, (5) ‘motor disability’, (6) ‘IQ<70’, (7) ‘positive family history of epilepsy’, and (8) ‘abnormal EEG’. All potential predictors were included in each analysis.

The study protocol was approved by the ethical review committee of Dhaka Shishu Hospital, Bangladesh Institute of Child Health, and the research ethics committee of Great Ormond Street Hospital for Children and University College London Institute of Child Health. Patients were recruited from April to October 2001. Parents’ written consent was obtained at the initial consultation.


  1. Top of page
  2. Abstract
  3. What this paper adds
  4. Method
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

A total of 390 children were enrolled: 77% were below 5 years, whereas 36% (140/390) were of age 12 months or less (Table II). The male:female ratio was 2:1. Most (95%) of the children were from low- to middle-income families, 61% from rural areas, and 37% of mothers were not literate. Only 31% of mothers had an antenatal check-up during the pregnancy in question. Preterm delivery was reported in 6%, and 65% (254/390) had a home delivery; among the remainder, most had hospital delivery with complicated labour starting at home. A history suggestive of insult to the growing brain was reported in 68% (267/390). Perinatal asphyxia (38%) and neonatal seizures (33%) were the most common, with an overlap of both in 22%. In this setting, perinatal asphyxia is loosely defined as failure to start breathing within 1 minute of birth. Other events reported were recurrent complex febrile seizures, infection of the central nervous system, and head injury.

Table II.   Sociodemographic profile, perinatal history, and neonatal history of the 390 (100%) study children
  1. aMedian age at first day of assessment 22 months (range 2–44mo). bOverlap present, i.e. a proportion (21.8%) had both perinatal asphyxia and neonatal seizures. CNS < central nervous system.

Age at presentationa
Family income
 Lower income23560.3
 Middle income13735.1
 Higher income184.6
Birth-related information
Place of birth
Mode of delivery
 Vaginal delivery32282.6
 Elective Caesarean section4411.2
 Emergency Caesarean section133.4
 Forceps delivery112.8
Events of potential brain insult
 None recalled12331.5
 Perinatal asphyxiab14837.9
 Neonatal seizuresb12832.8
 Recurrent complex febrile seizures4511.5
 CNS infection225.6
 Head injury71.7

‘Early onset’ seizures were recorded in 236 (60%), ‘multiple seizure types’ in 120 (31%), and 288 (74%) presented with a ‘high rate of seizures’. ‘Severe epilepsy syndrome’ was diagnosed in 121 (31%), most having West syndrome (66% [80/121]). ‘Family history of epilepsy’ was reported in 30 (7%) (Table III). Generalized epilepsies were diagnosed in 205 (52.5%). Partial epilepsies were diagnosed in 165 (42%), whereas 20 (5%) remained unclassified.

Comorbidities were found in 239 (61%), with ‘motor disability’ in 183 (47%), and IQ<70 in 227 (58%). Routine EEG recording was performed in 383 and 266 (70%) had ‘abnormal’ features, with 119 (31%) showing both epileptiform and non-epileptic background abnormalities (Table III). Neuroimaging (ultrasonography, computed tomography, or magnetic resonance imaging) of the brain was performed in 187 children and was abnormal in 70% (131/187) (atrophy in 76, hydrocephalus in 12, ischemic damage in 11, leukomalacia in seven, lissencephaly in five, tuberous sclerosis in five, and non-specific abnormality in 15).

Table III.   Seizure profile, epilepsy classification, comorbidities, and EEG findings in total study children (n=390) and seizure outcome in 319 children
Onset of seizures
 Early onset23660
 Later onset15439
Seizure type(s)
Rate of seizures
Severe epilepsy syndrome (n=121)
 West syndrome8066
 Myoclonic encephalopathy2924
 Lennox–Gastaut syndrome119
 Landau–Kleffner syndrome11
Epilepsy classification
 Generalized symptomatic or cryptogenic13735
 Partial symptomatic or cryptogenic10226
 Generalized idiopathic6817
 Partial idiopathic6316
Family history of epilepsy
 Present in first-degree relative307
 Motor disability18347
EEG findings (n=383)
 Epileptiform discharges8823
 Non-epileptic background abnormality5915
Seizure outcome (n=319)
 Good seizure control16853
 Poor seizure control15147
Seizure outcome in relation to EEG features (n=319)
 EEG feature (%)Good seizure controlPoor controlTotal
  Normal57 (61)36 (39)93 (100)
  Only epileptiform discharges43 (57)32 (43)75 (100)
  Non-epileptic background abnormality17 (40)25 (59)40 (100)
  Both51 (47)58 (53)109 (100)
Total168 (53)151 (47)319 (100)

From the total study population, 71 (18%) were lost to follow-up (Table IV). These were mainly single attendances and the children were later untraceable. Their mean age at presentation was 34 months compared with 39 months in the 319 followed-up children (p=0.93). Male:female ratio was the same as in the followed-up population; 73% (52/71) came from rural, poor-income families. Single seizure type was reported in 76% compared with 68%, high seizure rate in 66% compared with 75%, and motor disability in 49% in both in the lost to follow-up and the regular follow-up groups respectively. Cognitive assessment could be performed in only a few of the lost children.

Table IV.   Differences between those lost to follow-up (n=71) and those followed up (n=319)
Item n (%) in 319 n (%) in 71 (lost)χ2 (degrees of freedom) p value
Age at first contact
 Up to 12mo114 (36)30 (42)0.86 (2)0.93
 >1–5y127 (40)28 (39)  
 ≥5y78 (24)13 (18)  
 Male210 (66)48 (68)1.58 (1)0.26
 Female109 (34)23 (32)
Age at seizure onset
 ≤12mo191 (60)40 (56)0.11 (1)0.78
 >12mo128 (40)31 (44)
Economic status (income)
 Poor181 (57) 6.96 (2)0.03
 Middle120 (38)54 (76)  
 Higher18 (6)17 (24)  
Place of birth
 Home193 (61)55 (77)1.37 (1)0.96
History of events
 None97 (30)27 (38)  
 Perinatal asphyxia, neonatal seizure158 (49)34 (48)0.26 (2)0.99
 Recurrent seizure with associated fever64 (20)10 (14)  
Seizure type
 Single216 (68)54 (76)1.29 (1)0.39
 Multiple103 (32)47 (24)  
Epilepsy classification
 Generalized idiopathic48 (15)19 (26)  
 Generalized symptomatic and crypt111 (35)27 (38) 0.01
 Partial idiopathic57 (18)7 (10)1.45 (4) 
 Partial symptomatic and crypt ogenic89 (28)12 (17)  
 Unclassified14 (4)6 (9)  
 None223 (70)46 (65)0.56 (1)0.58
 Yes96 (30)25 (35)  
Seizure rate
 Low78 (24)24 (34)0.01 (1)0.59
 High241 (75)47 (66)  
Motor disability
 Absent171 (54)36 (51)0.46 (1)0.61
 Present158 (49)35 (49)  
 Poor IQ127 (40)   
 Absent192 (60)28 (39)0.01 (1)0.57
 Present 43 (60)  
Family history of epilepsy0.92 (1)0.36
 None295 (92)65 (92)  
 Present24 (8)6 (8)  
Seizure control  
 Good control168 (53)   
 Poor control151 (47) 0.01 (1)0.50
 Lost to follow-up71 (22)   

The most common antiepileptic drug used was phenobarbital (32%) followed by sodium valproate (25%), carbamazepine (25%), and nitrazepam (23%). ‘Good seizure control’ was achieved in 168 (53%). Better outcome was achieved in children who had no comorbidity 83 (77%) than in those with comorbidities 85 (40%). Two patients died at 6 months and 17 months after enrolment. Both had early-onset multiple seizure types with severe motor and cognitive disability. The exact cause of death remained unknown.

Predictors of poor seizure control

There were two strong predictors of seizure control. Children with low IQ were 2.1 times more likely to have poor seizure control, and those with motor disability were 2.5 times more likely to have poor seizure control. In addition there were two weak predictors. Those children with multiple seizure types were 1.7 times more likely to have poor seizure control (p<0.05 in 2/10 analyses), those with an epilepsy associated with cognitive regression were 1.9 times more likely to have poor seizure control (p<0.05 in 7/10 analyses). The use of bootstrap modelling in this analysis was to minimize the errors that may have occurred through a stepwise regression model. The bootstrap modelling may also have errors but these have been explored elsewhere.23

Treatment gap and compliance are important aspects of this study and the methods of encouraging compliance have been given. Among the total population, 86.9% had been to traditional healers at one stage, despite using physicians for other illnesses, 86.7% of those presenting were not on medication, and 7.6% had previously briefly taken medication. Compliance, assessed by verbal enquiry and drug strip counting, was assessed as poor in 8.5%, this was strongly related to poverty.


  1. Top of page
  2. Abstract
  3. What this paper adds
  4. Method
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

This study attempted to identify prospectively the factors that predict good or poor seizure control, by offering a hospital-based multidisciplinary service to newly referred patients. In our earlier retrospective study, three factors (multiple seizure types, cognitive deficit, and abnormal EEG) were identified as predictors of poor outcome2 with a view to developing an appropriate system of management in a resource-poor country like Bangladesh. Previously identified clinical factors were validated in this prospective study, with the addition of another clinical predictor, namely ‘motor disability’. Routine EEG did not add to the prediction. These neurodevelopmental predictors are comparable to similar findings both in developed and resource-poor countries.24 Associations between low IQ and poor seizure control have been found in several studies,25–29 as has motor disability.2,25–39 A significant predictor in this study was multiple types of seizure, a relatively unreported finding.2,38 It is possible that the average delay of 15 months from seizure onset to assessment allowed time for other seizure types to appear.

Our current data are more representative of the general population with more children from rural areas (61% vs 31%), from lower income groups (60% vs 31%), and more children under 1 year of age (36% vs 10%). There are, however, two potential sources of bias. Both sources are likely to have led to more conservative estimates of the relative risks reported. It is possible that children from the lower-income groups and those with earlier-onset epilepsy have poorer seizure and cognitive outcomes, and it is children with these features who were less likely to be followed up. As in the retrospective study, symptomatic or cryptogenic generalized and partial epilepsies were diagnosed in most (61%).2 This may reflect treatment-seeking behaviour of families when there is comorbidity, as has been reported in other developing countries.23

Knowledge of the likely seizure outcome of treatment is helpful in empowering families to make decisions about the cost/benefit of regular long-term drug treatment. The service offered not only identified cognitive and other additional impairments as factors important in prognosis, but also allowed these problems to be addressed. Problems of learning, behaviour, and coordination are often of greater concern than seizures. Such a comprehensive and empowering approach may be important in encouraging compliance. Whether being able to distinguish between an approximately 40% and 80% chance of seizure remission with treatment between those with and without comorbidities, respectively, is useful is debatable, but it is the starting point for having an auditable predictor with the possibility of developing more precise measures. This approach would allow referring health workers to assess the likely need for and benefit of treatment.

Overall, these findings suggest the need for a comprehensive management approach to children with epilepsy, including careful history-taking of seizure semiology, and motor and cognitive assessment. The Ministry of Health of the Bangladesh Government has been establishing multidisciplinary (i.e. child health physician, child psychologist, developmental therapist) child development centres within all medical college hospitals between 2008 and 2011. The present study results can offer an important guideline to seizure management for these newly trained professionals.

Potentially preventable causes of epilepsy such as birth-related problems, i.e. perinatal asphyxia and neonatal seizures and their comorbidities, were explored in this study. These were associated with ‘multiple seizure types’ and ‘early onset epilepsies’.40,41 These factors (perinatal asphyxia and neonatal seizure) were not therefore included in the bivariate and multiple regression analysis in the prospective study. Because 85% of deliveries occur at home by traditional birth attendant,42 information is limited and further research on causal relationships between perinatal events and childhood epilepsies needs to be conducted.

This study indicates the predictive power of simple clinical/cognitive data taken early. It must be of interest that this unit in Bangladesh managed to provide the appropriate multidisciplinary team for all children presenting with epilepsy. The seizure remission rate was comparable to that in resource-rich countries, and this achievement must relate to lowering the treatment gap.

The main limitation of this study is that it was not population-based, so it provides a clear account of a model for managing a referred (mostly self-referred) group of children with epilepsy. It does not give an absolute measure of the needs of the population. Also there must be some doubt about the very long-term outcome, particularly those lost to follow-up.


  1. Top of page
  2. Abstract
  3. What this paper adds
  4. Method
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

This study suggests that assessment of the phenotype of any child with epilepsy should include cognitive and motor disabilities; these domains need assessment and management in their own right and have prognostic significance for seizure control. It is therefore logical to include at some level such a multidisciplinary service as part of an epilepsy programme. Although EEG has a significant role in the diagnosis and management of epilepsy, it did not add significantly to the prediction of seizure remission.


  1. Top of page
  2. Abstract
  3. What this paper adds
  4. Method
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

The data collection and analysis of this study were possible through an academic link programme funded by the Department for International Development and managed by the British Council, Dhaka, between the Shishu Bikash Kendro (Child Development Center), Dhaka Shishu (Children’s) Hospital, and the Institute of Child Health and Great Ormond Street Hospital for Children NHS Trust, London, UK. We thank Ms. Angie Wade, statistician, Institute of Child Health, London, for her support in the statistical analysis. We are grateful to the parents and families: without their voluntary participation, this study would not have been possible. RCS is supported by Great Ormond Street Hospital Children’s Charity. Professor Brian Neville and Dr Rod Scott received support for attending professional meetings from UCB, Jansen-Cilag, Sanofi-Aventis, Special Products, and Cyberonics.


  1. Top of page
  2. Abstract
  3. What this paper adds
  4. Method
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References
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