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Impact of Thrombophilia on Risk of Arterial Ischemic Stroke or Cerebral Sinovenous Thrombosis in Neonates and Children

2010· review· en· W2134148711 on OpenAlexaff
Gili Kenet, Lisa K Lütkhoff, Manuela Albisetti, Timothy J. Bernard, Mariana Bonduel, Leonardo R. Brandão, Stéphane Chabrier, Anthony K.C. Chan, Gabrielle deVeber, Barbara Fiedler, Heather J. Fullerton, Neil A. Goldenberg, Eríc F. Grabowski, Gudrun Günther, Christine Heller, Susanne Holzhauer, Alfonso Iorio, Janna M. Journeycake, Ralf Junker, Fenella J. Kirkham, Karin Kurnik, Christoph Male, Marilyn J. Manco‐Johnson, Rolf M. Mesters, Paul Monagle, C. Heleen van Ommen, Leslie Raffini, Kevin Rostásy, Paolo Simioni, Ronald Sträter, Guy Young, Ulrike Nowak‐Göttl

Bibliographic record

VenueCirculation · 2010
Typereview
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsMcMaster University
FundersWestfälische Wilhelms-Universität Münster
KeywordsMedicineThrombophiliaArterial Ischemic StrokeThrombosisIntracranial ThrombosisStroke (engine)Ischemic strokePediatric strokeVascular diseaseCardiologyPediatricsInternal medicineVenous thrombosisIschemia

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this study was to estimate the impact of thrombophilia on risk of first childhood stroke through a meta-analysis of published observational studies. METHODS AND RESULTS: A systematic search of electronic databases (Medline via PubMed, EMBASE, OVID, Web of Science, The Cochrane Library) for studies published from 1970 to 2009 was conducted. Data on year of publication, study design, country of origin, number of patients/control subjects, ethnicity, stroke type (arterial ischemic stroke [AIS], cerebral venous sinus thrombosis [CSVT]) were abstracted. Publication bias indicator and heterogeneity across studies were evaluated, and summary odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with fixed-effects or random-effects models. Twenty-two of 185 references met inclusion criteria. Thus, 1764 patients (arterial ischemic stroke [AIS], 1526; cerebral sinus venous thrombosis [CSVT], 238) and 2799 control subjects (neonate to 18 years of age) were enrolled. No significant heterogeneity was discerned across studies, and no publication bias was detected. A statistically significant association with first stroke was demonstrated for each thrombophilia trait evaluated, with no difference found between AIS and CSVT. Summary ORs (fixed-effects model) were as follows: antithrombin deficiency, 7.06 (95% CI, 2.44 to 22.42); protein C deficiency, 8.76 (95% CI, 4.53 to 16.96); protein S deficiency, 3.20 (95% CI, 1.22 to 8.40), factor V G1691A, 3.26 (95% CI, 2.59 to 4.10); factor II G20210A, 2.43 (95% CI, 1.67 to 3.51); MTHFR C677T (AIS), 1.58 (95% CI, 1.20 to 2.08); antiphospholipid antibodies (AIS), 6.95 (95% CI, 3.67 to 13.14); elevated lipoprotein(a), 6.27 (95% CI, 4.52 to 8.69), and combined thrombophilias, 11.86 (95% CI, 5.93 to 23.73). In the 6 exclusively perinatal AIS studies, summary ORs were as follows: factor V, 3.56 (95% CI, 2.29 to 5.53); and factor II, 2.02 (95% CI, 1.02 to 3.99). CONCLUSIONS: The present meta-analysis indicates that thrombophilias serve as risk factors for incident stroke. However, the impact of thrombophilias on outcome and recurrence risk needs to be further investigated.

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)0.021
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.046
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.022
Bibliometrics0.0060.006
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.040
GPT teacher head0.333
Teacher spread0.293 · 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 designNot applicable
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

Citations441
Published2010
Admission routes1
Has abstractyes

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