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Record W2800922354 · doi:10.3171/2017.10.jns17439

Global hydrocephalus epidemiology and incidence: systematic review and meta-analysis

2018· review· en· W2800922354 on OpenAlexaboutno aff
Michael C. Dewan, Abbas Rattani, Rania A. Mekary, Laurence Glancz, Ismaeel Yunusa, Ronnie E. Baticulon, Graham Fieggen, John C. Wellons, Kee B. Park, Benjamin C. Warf

Bibliographic record

VenueJournal of neurosurgery · 2018
Typereview
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsnot available
FundersVanderbilt University
KeywordsMedicineHydrocephalusIncidence (geometry)Meta-analysisPediatricsSystematic reviewEpidemiologyLatin AmericansMEDLINEDemographySurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Hydrocephalus is one of the most common brain disorders, yet a reliable assessment of the global burden of disease is lacking. The authors sought a reliable estimate of the prevalence and annual incidence of hydrocephalus worldwide. METHODS: The authors performed a systematic literature review and meta-analysis to estimate the incidence of congenital hydrocephalus by WHO region and World Bank income level using the MEDLINE/PubMed and Cochrane Database of Systematic Reviews databases. A global estimate of pediatric hydrocephalus was obtained by adding acquired forms of childhood hydrocephalus to the baseline congenital figures using neural tube defect (NTD) registry data and known proportions of posthemorrhagic and postinfectious cases. Adult forms of hydrocephalus were also examined qualitatively. RESULTS: Seventy-eight articles were included from the systematic review, representative of all WHO regions and each income level. The pooled incidence of congenital hydrocephalus was highest in Africa and Latin America (145 and 316 per 100,000 births, respectively) and lowest in the United States/Canada (68 per 100,000 births) (p for interaction < 0.1). The incidence was higher in low- and middle-income countries (123 per 100,000 births; 95% CI 98-152 births) than in high-income countries (79 per 100,000 births; 95% CI 68-90 births) (p for interaction < 0.01). While likely representing an underestimate, this model predicts that each year, nearly 400,000 new cases of pediatric hydrocephalus will develop worldwide. The greatest burden of disease falls on the African, Latin American, and Southeast Asian regions, accounting for three-quarters of the total volume of new cases. The high crude birth rate, greater proportion of patients with postinfectious etiology, and higher incidence of NTDs all contribute to a case volume in low- and middle-income countries that outweighs that in high-income countries by more than 20-fold. Global estimates of adult and other forms of acquired hydrocephalus are lacking. CONCLUSIONS: For the first time in a global model, the annual incidence of pediatric hydrocephalus is estimated. Low- and middle-income countries incur the greatest burden of disease, particularly those within the African and Latin American regions. Reliable incidence and burden figures for adult forms of hydrocephalus are absent in the literature and warrant specific investigation. A global effort to address hydrocephalus in regions with the greatest demand is imperative to reduce disease incidence, morbidity, mortality, and disparities of access to treatment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.028
Bibliometrics0.0080.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.171
GPT teacher head0.397
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations435
Published2018
Admission routes1
Has abstractyes

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