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Record W2080312096 · doi:10.1186/1532-429x-14-s1-p118

Quantification of ductal blood flow with magnetic resonance imaging in newborns with obstructive left heart disease

2012· article· en· W2080312096 on OpenAlexaff
Marcelo Felipe Kozak, Luc Mertens, Ashley Ho, Shi‐Joon Yoo, Lars Grosse‐Wortmann

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2012
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsAngiologyMedicineMagnetic resonance imagingCardiologyBlood flowInternal medicineRadiology

Abstract

fetched live from OpenAlex

Patients with congenital obstructive left heart lesions often depend on ductal blood flow to supplement their systemic circulation. Echocardiography (ECHO) is routinely used to assess duct patency and shunt direction, but may be of limited value in shunt quantification. We hypothesized that ECHO assessment of net direction and magnitude of blood flow across a patent ductus arteriosus (PDA) is unreliable as compared to cardiac magnetic resonance (CMR). From 2003 to 2011, 40 newborns with obstructive left heart lesions had undergone ECHO and MRI prior to any intervention to alleviate the obstruction. Twelve out of these 40 patients matched the inclusion criteria: 1) on prostaglandin infusion, 2) ECHO and MRI performed within 2 days, and 3) oxygen saturation difference between the two tests within 10%. We retrospectively compared the shunt quantification across the PDA by both methods: Phase contrast flow velocity mapping by CMR and velocity time integral (VTI) by ECHO. Age ranged between 0 and 9 days; other characteristics are detailed in the table. There was no significant difference between net flow measurements by CMR or ECHO-VTI (p = 0.18). However, there was poor agreement among methods with a wide confidence interval (figure) and a low intra-class correlation coefficient of -0.29. Also, when comparing CMR measurements with a semi-quantitative analysis by an experienced echocardiographer, we found that the net flow direction was estimated correctly by echocardiography in 2/3 of cases. The correlation between visual flow quantification by echocardiography (mild, moderate, severe) and CMR net flow in the 8 patients rated to have a net right-to-left shunt by both methods was poor (Kendall’s rank correlation coefficient 0.13, p NS). PDA net right-to-left shunt by CMR correlated with the ratio of systolic to diastolic flow duration (Rho = 0.66; p = 0.02), but not with oxygen saturation (Rho = -0.45; p = 0.14); age (Rho = 0.27; p = 0.39), PDA diameter (Rho = -0.22; p = 0.5), and heart rate (Rho = -0.08; p = 0.8). Figure 1 In patients with obstructive left heart lesions, ECHO based estimates of shunt magnitude across a PDA are unreliable. This is true for semiquantitative visual assessment and for flow estimation by VTI. The presence of a large caliber PDA does not imply the presence of a large amount of net shunting. A longer relative duration of systole allows for more ductal right-to-left shunting.

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)0.006
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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