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Record W2767002508 · doi:10.1093/eurheartj/ehx526

The natural history and surgical outcome of patients with scimitar syndrome: a multi-centre European study

2017· article· en· W2767002508 on OpenAlexaff
Vladimiro L. Vida, Alvise Guariento, Ornella Milanesi, Darío Gregori, Giovanni Stellin, Fabio Zucchetta, Lorenza Zanotto, Massimo A. Padalino, Biagio Castaldi, Sasa Bosiznik, R Crepaz, Joseph Stuefer, Flor de Maria Garcia Gonzales, Aldo R. Castañeda, Giancarlo Crupi, Gabriella Agnoletti, Sara Bondanza, Maurizio Marasini, L. Zannini, Gianfranco Butera, Alessandro Frigiola, Alessandro Varrica, Enrico Chiappa, Mara Pilati, Adriano Carotti, Matteo Trezzi, Daniela Prandstraller, Gaetano Gargiulo, Maria Giovanna Russo, Giuseppe Santoro, Giuseppe Caianiello, Isabella Spadoni, Bruno Murzi, Luigi Arcieri, Marco Pozzi, Giulio Porcedda, Håkan Berggren, Thierry Carrel, Alexander Kadner, Sertaç Çïçek, Yılmaz Zorman, José Fragata, Andreia Gordo, Mark G. Hazekamp, Vladimír Soják, Viktor Hraška, Boulos Asfour, Bohdan Maruszewski, Michał Kozłowski, D Métras, René Prêtre, Jean Rubay, Heikki Sairanen, George E. Sarris, Christian Schreiber, Masamichi Ono, Bart Meyns, Klaartje Van den Bossche, T Tláskal, Mauro Lo Rito, Shi Joon Yoo, Glen S. Van Arsdell, Christopher T. Calderone, Yoichi Iwamoto, Juan León-Wyss, Sylvie Di Filippo, C Leconte, Barbara J.M. Mulder, Tjark Ebels, Sara C. Arrigoni, Emanuela Valsangiacomo, Hitendu Dave, Igor E. Konstantinov, Andreas Gamillscheg, Doros Gabriela, Ulrike Herberg, Yves Dulac, Julio Edmerger, Alberto Zarate Fuentes, Juan Miguel Gil Jaúrena, Ilaria Bo, Olivier Ghez, Micheal L Rigby, Emile Bacha, David Kalfa, Simone Speggiorin, Frances Bu’Lock, Mamdouh Al‐Ahmadi, Giovanni Di Salvo, Rafał Surmacz, Illya Yemets, Yaroslav Mykychak, Ignacio Lugones, Duke E. Cameron, Luca A. Vricella, Carlos J. Troconis, Gaetano Thiene, Annalisa Angelini, Lucia Zanotto

Bibliographic record

VenueEuropean Heart Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicCongenital Diaphragmatic Hernia Studies
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineInterquartile rangeAsymptomaticScimitar syndromeNatural historyOdds ratioInternal medicineSurgeryCardiac surgeryConfidence intervalLung

Abstract

fetched live from OpenAlex

Aims: Treatment decisions in patients with scimitar syndrome (SS) are often challenging, especially in patients with isolated SS who are often asymptomatic and who might be diagnosed accidentally. We queried a large multi-institutional registry of SS patients to evaluate the natural history of this condition and to determine the efficacy of surgical treatment in terms of survival and clinical status. Methods and results: We collected data on 485 SS patients from 51 institutions; 279 (57%) patients were treated surgically (STPs) and 206 (43%) were clinically monitored (CMPs). Median age at last follow-up was 11.6 years (interquartile range 4-22 years). Overall survival probability at 30 years of age was 88% [85-92% confidence intervals (CI)] and was lower in patients with associated congenital heart disease (CHD) (P < 0.001) and pulmonary hypertension (P < 0.001). Most patients were asymptomatic at last follow-up (279/451, 62%); STPs were more frequently asymptomatic than CMPs (73% vs. 47%, P < 0.001), with fewer cardiac [odds ratio (OR) 0.42, 95% CI 0.22-0.82] and respiratory symptoms (OR 0.08, 95% CI 0.02-0.28). Many STPs (63/254, 25%) had stenosis/occlusion of the scimitar drainage, and this was associated with a younger age at surgery (OR 0.4, CI 0.21-0.78). Conclusion: Patients with SS have a high overall survival. Survival probability was lower in patients with associated CHDs and in patients with pulmonary hypertension. Surgical treatment of SS is beneficial in reducing symptoms, however, given the significant risk of post-operative scimitar drainage stenosis/occlusion, it should be tailored to a comprehensive haemodynamic evaluation and to the patient's age.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.292
Teacher spread0.244 · 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 teacher head, 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

Citations41
Published2017
Admission routes1
Has abstractyes

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