Cerebral palsy describes the most common physical disability in childhood and occurs in 1 in 500 live births. Historically, the diagnosis has been made between age 12 and 24 months but now can be made before 6 months’ corrected age.
Objectives
To systematically review best available evidence for early, accurate diagnosis of cerebral palsy and to summarize best available evidence about cerebral palsy–specific early intervention that should follow early diagnosis to optimize neuroplasticity and function.
Evidence Review
This study systematically searched the literature about early diagnosis of cerebral palsy in MEDLINE (1956-2016), EMBASE (1980-2016), CINAHL (1983-2016), and the Cochrane Library (1988-2016) and by hand searching. Search terms includedcerebral palsy,diagnosis,detection,prediction,identification,predictive validity,accuracy,sensitivity, andspecificity. The study included systematic reviews with or without meta-analyses, criteria of diagnostic accuracy, and evidence-based clinical guidelines. Findings are reported according to the PRISMA statement, and recommendations are reported according to the Appraisal of Guidelines, Research and Evaluation (AGREE) II instrument.
Findings
Six systematic reviews and 2 evidence-based clinical guidelines met inclusion criteria. All included articles had high methodological Quality Assessment of Diagnostic Accuracy Studies (QUADAS) ratings. In infants, clinical signs and symptoms of cerebral palsy emerge and evolve before age 2 years; therefore, a combination of standardized tools should be used to predict risk in conjunction with clinical history. Before 5 months’ corrected age, the most predictive tools for detecting risk are term-age magnetic resonance imaging (86%-89% sensitivity), the Prechtl Qualitative Assessment of General Movements (98% sensitivity), and the Hammersmith Infant Neurological Examination (90% sensitivity). After 5 months’ corrected age, the most predictive tools for detecting risk are magnetic resonance imaging (86%-89% sensitivity) (where safe and feasible), the Hammersmith Infant Neurological Examination (90% sensitivity), and the Developmental Assessment of Young Children (83% C index). Topography and severity of cerebral palsy are more difficult to ascertain in infancy, and magnetic resonance imaging and the Hammersmith Infant Neurological Examination may be helpful in assisting clinical decisions. In high-income countries, 2 in 3 individuals with cerebral palsy will walk, 3 in 4 will talk, and 1 in 2 will have normal intelligence.
Conclusions and Relevance
Early diagnosis begins with a medical history and involves using neuroimaging, standardized neurological, and standardized motor assessments that indicate congruent abnormal findings indicative of cerebral palsy. Clinicians should understand the importance of prompt referral to diagnostic-specific early intervention to optimize infant motor and cognitive plasticity, prevent secondary complications, and enhance caregiver well-being.
We conducted a community survey to estimate the prevalence and describe the features, risk factors, and consequences of convulsive status epilepticus (CSE) among people with active convulsive epilepsy (ACE) identified in a multisite survey in Africa.We obtained clinical histories of CSE and neurologic examination data among 1,196 people with ACE identified from a population of 379,166 people in 3 sites: Agincourt, South Africa; Iganga-Mayuge, Uganda; and Kilifi, Kenya. We performed serologic assessment for the presence of antibodies to parasitic infections and HIV and determined adherence to antiepileptic drugs. Consequences of CSE were assessed using a questionnaire. Logistic regression was used to identify risk factors.The adjusted prevalence of CSE in ACE among the general population across the 3 sites was 2.3 per 1,000, and differed with site (p < 0.0001). Over half (55%) of CSE occurred in febrile illnesses and focal seizures were present in 61%. Risk factors for CSE in ACE were neurologic impairments, acute encephalopathy, previous hospitalization, and presence of antibody titers to falciparum malaria and HIV; these differed across sites. Burns (15%), lack of education (49%), being single (77%), and unemployment (78%) were common in CSE; these differed across the 3 sites. Nine percent with and 10% without CSE died.CSE is common in people with ACE in Africa; most occurs with febrile illnesses, is untreated, and has focal features suggesting preventable risk factors. Effective prevention and the management of infections and neurologic impairments may reduce the burden of CSE in ACE.
Cerebral palsy (CP) is the most common childhood-onset motor disorder accompanied by associated impairments, placing a heavy burden on families and health systems. Most children with CP live in low/middle-income countries with little access to rehabilitation services. This study will evaluate the Akwenda CP programme, a multidimensional intervention designed for low-resource settings and aiming at improving: (1) participation, motor function and daily activities for children with CP; (2) quality of life, stress and knowledge for caregivers; and (3) knowledge and attitudes towards children with CP in the communities.This quasi-randomised controlled clinical study will recruit children and youth with CP aged 2-23 years in a rural area of Uganda. Children will be allocated to one of two groups with at least 44 children in each group. Groups will be matched for age, sex and motor impairment. The intervention arm will receive a comprehensive, multidimensional programme over a period of 11 months comprising (1) caregiver-led training workshops, (2) therapist-led practical group sessions, (3) provision of technical assistive devices, (4) goal-directed training and (5) community communication and advocacy. The other group will receive usual care. The outcome of the intervention will be assessed before and after the intervention and will be measured at three levels: (1) child, (2) caregiver and (3) community. Standard analysis methods for randomised controlled trial will be used to compare groups. Retention of effects will be examined at 12-month follow-up.The study has been approved by the Uganda National Council for Science and Technology (SS 5173) and registered in accordance with WHO and ICMJE standards. Written informed consent will be obtained from caregivers. Results will be disseminated among participants and stakeholders through public engagement events, scientific reports and conference presentations.Pan African Clinical Trials Registry (PACTR202011738099314) Pre-results.
Due to the heterogeneous nature of depression, the underlying etiological mechanisms greatly differ among individuals, and there are no known subtype-specific biomarkers to serve as precise targets for therapeutic efficacy. The extensive research efforts over the past decades have not yielded much success, and the currently used first-line conventional antidepressants are still ineffective for close to 66% of patients. Most clinicians use trial-and-error treatment approaches, which seem beneficial to only a fraction of patients, with some eventually developing treatment resistance. Here, we review evidence from both preclinical and clinical studies on the pathogenesis of depression and antidepressant treatment response. We also discuss the efficacy of the currently used pharmacological and non-pharmacological approaches, as well as the novel emerging therapies. The review reveals that the underlying mechanisms in the pathogenesis of depression and antidepressant response, are not specific, but rather involve an interplay between various neurotransmitter systems, inflammatory mediators, stress, HPA axis dysregulation, genetics, and other psycho-neurophysiological factors. None of the current depression hypotheses sufficiently accounts for the interactional mechanisms involved in both its etiology and treatment response, which could partly explain the limited success in discovering efficacious antidepressant treatment. Effective management of treatment-resistant depression (TRD) requires targeting several interactional mechanisms, using subtype-specific and/or personalized therapeutic modalities, which could, for example, include multi-target pharmacotherapies in augmentation with psychotherapy and/or other non-pharmacological approaches. Future research guided by interaction mechanisms hypotheses could provide more insights into potential etiologies of TRD, precision biomarker targets, and efficacious therapeutic modalities.
Objectives Approximately 80% of people with epilepsy live in low- and middle-income countries (LMICs), where limited resources and stigma hinder accurate diagnosis and treatment. Clinical machine learning models have demonstrated substantial promise in supporting the diagnostic process in LMICs by aiding in preliminary screening and detection of possible epilepsy cases without relying on specialised or trained personnel. How well these models generalise to naïve regions is, however, underexplored. Here, we use a novel approach to assess the suitability and applicability of such clinical tools to aid screening and diagnosis of active convulsive epilepsy in settings beyond their original training contexts. Methods We sourced data from the Study of Epidemiology of Epilepsy in Demographic Sites dataset, which includes demographic information and clinical variables related to diagnosing epilepsy across five sub-Saharan African sites. For each site, we developed a region-specific (single-site) predictive model for epilepsy and assessed its performance at other sites. We then iteratively added sites to a multi-site model and evaluated model performance on the omitted regions. Model performances and parameters were then compared across every permutation of sites. We used a leave-one-site-out cross-validation analysis to assess the impact of incorporating individual site data in the model. Results Single-site clinical models performed well within their own regions, but generally worse when evaluated in other regions (p<0.05). Model weights and optimal thresholds varied markedly across sites. When the models were trained using data from an increasing number of sites, mean internal performance decreased while external performance improved. Conclusions Clinical models for epilepsy diagnosis in LMICs demonstrate characteristic traits of ML models, such as limited generalisability and a trade-off between internal and external performance. The relationship between predictors and model outcomes also varies across sites, suggesting the need to update specific model aspects with local data before broader implementation. Variations are likely to be particular to the cultural context of diagnosis. We recommend developing models adapted to the cultures and contexts of their intended deployment and caution against deploying region- and culture-naïve models without thorough prior evaluation.
Seizures in up to one third of children with epilepsy may not be controlled by the first anti-epileptic drug (AED). In this study, we describe multiple AED usage in children attending a referral clinic in Uganda, the factors associated with multiple AED use and seizure control in affected patients. One hundred thirty nine patients attending Mulago hospital paediatric neurology clinic with epilepsy and who had been on AEDs for ≥6 months were consecutively enrolled from July to December 2013 to reach the calculated sample size. With consent, the history and physical examination were repeated and the neurophysiologic and imaging features obtained from records. Venous blood was also drawn to determine AED drug levels. We determined the proportion of children on multiple AEDs and performed regression analyses to determine factors independently associated with multiple AED use. Forty five out of 139 (32.4 %) children; 46.7 % female, median age 6 (IQR = 3–9) years were on multiple AEDs. The most common combination was sodium valproate and carbamazepine. We found that 59.7 % of children had sub-therapeutic drug levels including 42.2 % of those on multi-therapy. Sub-optimal seizure control (adjusted odds ratio [ORa] 3.93, 95 % CI 1.66–9.31, p = 0.002) and presence of focal neurological deficits (ORa 3.86, 95 % CI 1.31–11.48, p = 0.014) were independently associated with multiple AED use but not age of seizure onset, duration of epilepsy symptoms, seizure type or history of status epilepticus. One third of children with epilepsy in Mulago receive multiple AEDs. Multiple AED use is most frequent in symptomatic focal epilepsies but doses are frequently sub-optimal. There is urgent need to improve clinical monitoring in our patients.
Sleep plays a prominent role in the growth and development of children. Children with cerebral palsy (CP) are more prone to sleep disorders (SDs) than their peers. Children with CP, have a higher prevalence of disorders involving; initiation and maintenance of sleep, sleep-wake transition, excessive sleepiness and arousal. These sleep disorders impact on the quality of life of these children. Despite, having a high prevalence of CP in Uganda, there is a paucity of data that focuses on sleep disorders in CP, including a lack of prevalence estimates of sleep breathing disorder (SBD) in CP. Understanding the prevalence and disorders of sleep within this population would help advise on the development of tailored interventions to address the needs of these children and improve their quality of life. This study determined the prevalence and associated factors of sleep disorders among children aged 2 - 12 years with cerebral palsy in Uganda.This was a cross sectional study. All participants had a physical examination and screening with the Sleep Disturbances Scale for Children (SDSC) questionnaire to determine the prevalence of sleeps disorders. A total score (TS) ≥ 51 on the Sleep Disturbances Scale for Children was regarded as abnormal.A total of 135 participants were recruited. The prevalence of sleep disorders was 43/135 (32%) with 95% CI: (24.0-39.7). The most common type of sleep disorders was a disorder of initiating and maintaining sleep 37(27%). The factors associated with sleep disorders among children with cerebral palsy were bilateral spasticity (p = 0.004); OR:(95%CI), 11.193: (2.1 - 59.0), lowest levels of gross motor function V (p = < 0.001); OR:(95%CI), 13.182: (3.7 - 47.0) or IV (p = 0.007); OR:(95%CI), 12.921: (2.0 - 82.3), lowest level of manual ability V (p = 0.004); OR:(95%CI), 11.162: (2.2 - 56.4) and presence of epilepsy (p = 0.011); OR:(95%CI), 3.865: (1.4 - 10.9).The prevalence of sleep disorders among children with cerebral palsy in Uganda is high. Severe disability and presence of epilepsy were associated with sleep disorders among children with cerebral palsy.
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