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Record W3204903837 · doi:10.3171/2021.7.peds21209

Preoperative risk and postoperative outcome from subdural fluid collections in African infants with postinfectious hydrocephalus

2021· article· en· W3204903837 on OpenAlexaff
Jessica Lane, Paddy Ssentongo, Mallory Peterson, Joshua Harper, Edith Mbabazi-Kabachelor, John Mugamba, Peter Ssenyonga, Justin Onen, Ruth Donnelly, Jody Levenbach, Venkateswararao Cherukuri, Vishal Monga, Abhaya V. Kulkarni, Benjamin C. Warf, Steven J. Schiff

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2021
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsUniversity Health NetworkSickKids FoundationToronto Western HospitalHospital for Sick ChildrenUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsMedicineBayley Scales of Infant DevelopmentHydrocephalusAnesthesiaNeurosurgerySurgeryPediatricsCognition

Abstract

fetched live from OpenAlex

OBJECTIVE: This study investigated the incidence of postoperative subdural collections in a cohort of African infants with postinfectious hydrocephalus. The authors sought to identify preoperative factors associated with increased risk of development of subdural collections and to characterize associations between subdural collections and postoperative outcomes. METHODS: The study was a post hoc analysis of a randomized controlled trial at a single center in Mbale, Uganda, involving infants (age < 180 days) with postinfectious hydrocephalus randomized to receive either an endoscopic third ventriculostomy plus choroid plexus cauterization or a ventriculoperitoneal shunt. Patients underwent assessment with the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III; sometimes referred to as BSID-III) and CT scans preoperatively and then at 6, 12, and 24 months postoperatively. Volumes of brain, CSF, and subdural fluid were calculated, and z-scores from the median were determined from normative curves for CSF accumulation and brain growth. Linear and logistic regression models were used to characterize the association between preoperative CSF volume and the postoperative presence and size of subdural collection 6 and 12 months after surgery. Linear regression and smoothing spline ANOVA were used to describe the relationship between subdural fluid volume and cognitive scores. Causal mediation analysis distinguished between the direct and indirect effects of the presence of a subdural collection on cognitive scores. RESULTS: Subdural collections were more common in shunt-treated patients and those with larger preoperative CSF volumes. Subdural fluid volumes were linearly related to preoperative CSF volumes. In terms of outcomes, the Bayley-III cognitive score was linearly related to subdural fluid volume. The distribution of cognitive scores was significantly different for patients with and those without subdural collections from 11 to 24 months of age. The presence of a subdural collection was associated with lower cognitive scores and smaller brain volume 12 months after surgery. Causal mediation analysis demonstrated evidence supporting both a direct (76%) and indirect (24%) effect (through brain volume) of subdural collections on cognitive scores. CONCLUSIONS: Larger preoperative CSF volume and shunt surgery were found to be risk factors for postoperative subdural collection. The size and presence of a subdural collection were negatively associated with cognitive outcomes and brain volume 12 months after surgery. These results have suggested that preoperative CSF volumes could be used for risk stratification for treatment decision-making and that future clinical trials of alternative shunt technologies to reduce overdrainage should be considered.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.251
Teacher spread0.233 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2021
Admission routes1
Has abstractyes

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