| Literature DB >> 27988968 |
Francis Levira1,2,3, David J Thurman4, Josemir W Sander5,6, W Allen Hauser7, Dale C Hesdorffer7, Honorati Masanja1, Peter Odermatt2,3, Giancarlo Logroscino8, Charles R Newton9,10,11.
Abstract
To determine the magnitude of risk factors and causes of premature mortality associated with epilepsy in low- and middle-income countries (LMICs). We conducted a systematic search of the literature reporting mortality and epilepsy in the World Bank-defined LMICs. We assessed the quality of the studies based on representativeness; ascertainment of cases, diagnosis, and mortality; and extracted data on standardized mortality ratios (SMRs) and mortality rates in people with epilepsy. We examined risk factors and causes of death. The annual mortality rate was estimated at 19.8 (range 9.7-45.1) deaths per 1,000 people with epilepsy with a weighted median SMR of 2.6 (range 1.3-7.2) among higher-quality population-based studies. Clinical cohort studies yielded 7.1 (range 1.6-25.1) deaths per 1,000 people. The weighted median SMRs were 5.0 in male and 4.5 in female patients; relatively higher SMRs within studies were measured in children and adolescents, those with symptomatic epilepsies, and those reporting less adherence to treatment. The main causes of death in people with epilepsy living in LMICs include those directly attributable to epilepsy, which yield a mean proportional mortality ratio (PMR) of 27.3% (range 5-75.5%) derived from population-based studies. These direct causes comprise status epilepticus, with reported PMRs ranging from 5 to 56.6%, and sudden unexpected death in epilepsy (SUDEP), with reported PMRs ranging from 1 to 18.9%. Important causes of mortality indirectly related to epilepsy include drowning, head injury, and burns. Epilepsy in LMICs has a significantly greater premature mortality, as in high-income countries, but in LMICs the excess mortality is more likely to be associated with causes attributable to lack of access to medical facilities such as status epilepticus, and preventable causes such as drowning, head injuries, and burns. This excess premature mortality could be substantially reduced with education about the risk of death and improved access to treatments, including AEDs.Entities:
Keywords: Case fatality; Convulsions; Death; Developing countries; Premature mortality; Resource-poor countries; Seizures
Mesh:
Year: 2016 PMID: 27988968 PMCID: PMC7012644 DOI: 10.1111/epi.13603
Source DB: PubMed Journal: Epilepsia ISSN: 0013-9580 Impact factor: 5.864
Mortality estimates from population-based studies
| Population-based | Country-location (income) | Total population | Quality | People with epilepsy original cohort | People with epilepsy followed | Duration of FU (years)[ | Estimated person-years | Deaths | SMR | 95% CI | CFR | 95% CI | Mortality rate per 1,000 person-year | 95% CI |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Ngugi (2014)[ | Kenya-rural (L) | 232,164 | 100 | 754 | 606 | 2.7 | 2,048 | 61 | 6.5 | 5.00–8.30 | 8.1 | 6.1–10 | 29.8 | 22.8–38.3 |
| Kochen (2005)[ | Argentina-urban (M) | 70,000 | 90 | 106 | 96 | 8 | 768 | 8 | 2.45 | 1.14–4.65[ | 8.3 | 2.8–13.9 | 10.4 | 4.5–20.5 |
| Kaiser (2007)[ | Uganda-rural (L) | 4,743 | 90 | 61 | 57 | 7 | 399 | 18 | 7.2 | 4.40–11.6 | 31.6 | 19.5–43.6 | 45.1 | 26.7–71.3 |
| Nicoletti (2009)[ | Bolivia-rural (M) | 55,675 | 85 | 118 | 103 | 10 | 1,030 | 10 | 1.34 | 0.68–2.39 | 9.7 | 4.0–15.4 | 9.7 | 4.7–17.9 |
| Houinato (2013)[ | Benin-rural (L) | 11,688 | 80 | 160 | 150 | 1.5 | 225 | 5 | 3.3 | 0.5–6.2 | 22.2 | 7.2–51.9 | ||
| Banerjee (2010)[ | India-urban (M) | 52,377 | 80 | 337 | 337 | 5 | 1,685 | 20 | 2.58 | 1.50–4.13 | 5.9 | 3.4–8.5 | 11.9 | 7.3–18.3 |
| Carpio (2005)[ | India-rural (Vusai) (M) | 16,000 | 80 | 51 | 51 | 10 | 510 | 10 | 3.9 | 2.1–7.25 | 19.6 | 8.7–30.5 | 19.6 | 9.4–36.1 |
| Summary: higher quality population studies | 442,647 | 1,587 | 1,400 | 5.8[ | 6,665 | 132 | 2.6[ | 8.1[ | 19.8 | 16.7–23.5 | ||||
| Carpio (2005)[ | India-urban (Parsis) (M) | 14,010 | 65 | 109 | 104 | 14 | 1,456 | 34 | 0.76 | 0.51–1.01 | 32.7 | 23.7–41.7 | 23.4 | 16.2–32.6 |
| Kamgno (2003)[ | Cameroon-rural (L) | NR | 60 | 271 | 128 | 10 | 1,280 | 37 | 28.9 | 21.1–36.8 | 28.9 | 20.4–39.8 | ||
| Mu (2011)[ | China-rural (M) | 5,840,000 | 50 | 3,568 | 2,998 | 4.5 | 13,491 | 106 | 4.9 | 4.0–6.1 | 3.5 | 2.9–4.2 | 7.9 | 6.4–9.5 |
| Ding (2013)[ | China-rural (M) | 3,185,000 | 50 | 2,455 | 1,986 | 6.1 | 12,114 | 206 | 2.9 | 2.6–3.4 | 10.4 | 9.0–11.7 | 17.0 | 14.8–19.5 |
| Carpio (2005)[ | Mali-urban/rural (L) | 7,158 | 40 | 36 | 31 | 12 | 372 | 13 | 4.25 | 2.8–6.45 | 41.9 | 24.6–59.3 | 34.9 | 18.8–59.8 |
| Summary: lower quality population studies | >9,112,561 | 8,894 | 7,233 | 6.0[ | 32,850 | 431 | 2.9[ | 10.4[ | 13.1 | 11.9–14.4 | ||||
FU, follow-up; SMR, standardized mortality ratio; CI, confidence interval; CFR, case fatality ratio; (L), low-income country; (M), middle-income country.
Length of follow-up described variously as median (Ngugi et al.[35]), mean (Ding et al.[29]), or the total interval of cohort assessment (others).
Mean weighted by study person-years.
Median weighted by study person-years.
Follow-up study of cohort described in Ding et al.[28]
Mortality estimates from clinical cohort studies
| Country-location | Quality | People with epilepsy in original cohort | People with epilepsy followed | Duration of FU (years) | Person-years | Deaths | SMR | 95% CI | Case fatality ratio (%) | 95% CI | Mortality rate per 1,000 person-year | 95% CI | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Carpio (2005)[ | Ecuador-urban (M) | 50 | 420 | 379 | 3 | 1,137 | 7 | 6.3 | 2.0–10.0 | 1.8 | 0.5–3.2 | 6.2 | 2.5–12.7 |
| Almeida (2010)[ | Brazil-urban/Rural (M) | 45 | 550 | 550 | 10 | 5,500 | 16 | 2.9 | 1.5–4.3 | 2.9 | 1.7–4.7 | ||
| Terra (2011)[ | Brazil-urban (M) | 35 | 1,012 | 987 | 10 | 9,870 | 53 | 5.4 | 4.0–6.8 | 5.4 | 4.0–7.0 | ||
| Jilek-Aall (1992)[ | Tanzania-Rural (L) | 35 | 164 | 146 | 30 | 4,380 | 110 | 75.3 | 68.4–82.3 | 25.1 | 20.6–30.3 | ||
| Thomas (2001)[ | India-urban (M) | 25 | 447 | 246 | 12 | 2,952 | 18 | 7.3 | 4.1–10.6 | 6.1 | 3.6–9.6 | ||
| Terra (2010)[ | Brazil-urban/Rural (M) | 25 | 267 | 267 | 13 | 3,471 | 9 | 3.4 | 1.2–5.5 | 2.6 | 1.2–4.0 | ||
| Devilat (2004)[ | Chile-urban/Rural (M) | 5 | NR | NR | 6 | NR | 16 | 3.21 | 1.5–5.0 | ||||
| Terra (2009)[ | Brazil-urban/Rural (M) | 5 | 996 | 835 | 8 | 6,680 | 11 | 1.3 | 0.5–2.1 | 1.6 | 0.8–2.9 | ||
| Summary: all studies | 3,856 | 3,410 | 12.4[ | 33,990 | 240 | 4.8 | 5.4[ | 7.1 | 6.2–8.0 | ||||
FU, follow-up; SMR, standardized mortality ratio; CI, confidence interval; CFR, case fatality ratio; (L), low-income country; (M), middle-income country.
Mean weighted by study person-years.
Median weighted by study person-years.
Figure 1Summary results of search strategy. Flow diagram showing results of systematic literature search. Medline, EMBASE, and LILACS databases were used to search for scientific articles of studies of mortality associated with epilepsy between 1990 and 2014. The search used medical subject headings associated with epilepsy and its manifestation, mortality, and geographic location restricted to low- and middle-income countries. Authors FL and CN independently evaluated citations of the search output by reading title and abstract and arrived at a total of 56 articles. Through the inclusion criteria developed, a total of 17 articles were finally included in the systematic review.
Epilepsia © ILAE
Figure 2Mortality in epilepsy by age at death. Estimates of mortality rate by age. SMR stands for standardized mortality ratio; ratio of age standardized mortality rate in epilepsy and general population. SMR >1 represents excess mortality in epilepsy compared to the general population.
Epilepsia © ILAE
Estimates of proportional mortality in epilepsy by cause in population-based and clinical cohort studies
| Study | Country-location | Design | Quality (%) | Number of people with epilepsy followed | Number of deaths | Causes of death (%) | |||
|---|---|---|---|---|---|---|---|---|---|
| Direct | Indirect | Unrelated | Undetermined | ||||||
| Ngugi (2014)[ | Kenya-rural | Population | 100 | 606 | 61 | 44.3 | 11.4 | 34.3 | 9.8 |
| Kaiser (2007)[ | Uganda-rural | Population | 90 | 61 | 18 | 33.0 | 17.0 | 44.4 | 5.6 |
| Nicoletti (2009)[ | Bolivia-rural | Population | 85 | 103 | 10 | 10 | 20 | 50 | 20 |
| Banerjee (2010)[ | India-urban | Population | 80 | 337 | 20 | 5 | 30 | 45 | 20 |
| Kamgno (2003)[ | Cameroon-rural | Population | 60 | 271 | 37 | 75.5 | 10.8 | 13.7 | |
| Mu (2011)[ | China-rural | Population | 50 | 2,998 | 106 | 21.6 | 58.8 | 19.6 | |
| Ding (2013)[ | China-rural | Population | 50 | 1,986 | 206 | 14.1 | 32.5 | 39.3 | 14.1 |
| Carpio (2005)[ | Mali-rural/urban | Population | 40 | 36 | 13 | 38.0 | NR | 62.0 | NR |
| Summary: all population-based | 6,546 | 471 | 27.3[ | 20.0[ | 41.9[ | 14.1[ | |||
| Carpio (2005)[ | Ecuador-urban | Clinical cohort | 50 | 379 | 7 | 42 | 30 | 28 | |
| Almeida (2010)[ | Brazil-urban/rural | Clinical cohort | 45 | 550 | 16 | 62.5 | |||
| Terra (2011)[ | Brazil-urban | Clinical cohort | 35 | 987 | 53 | 15.1 | 84.9 | ||
| Jilek-Aall (1992)[ | Tanzania-rural | Clinical cohort | 35 | 164 | 110 | 17.3 | 18.2 | 32.7 | 31.8 |
| Terra (2010)[ | Brazil-urban/ rural | Clinical cohort | 25 | 267 | 9 | 77.8 | |||
| Devilat (2004)[ | Chile-Santiago | Clinical cohort | 5 | NR | 16 | 39.3 | |||
| Summary: all clinical cohorts | >2,347 | 211 | 39.3[ | 24.1[ | 47.6[ | ||||
Median percentage.