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Record W3091534674 · doi:10.1111/pan.14004

COVID‐19 and congenital heart disease: <i>Cardiopulmonary interactions for the worse!</i>

2020· letter· en· W3091534674 on OpenAlexaboutno aff
Rohan Magoon

Bibliographic record

VenuePediatric Anesthesia · 2020
Typeletter
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakHeart diseaseSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Cardiopulmonary bypassCardiologyDiseaseIntensive care medicineCoronavirus InfectionsInternal medicineVirologyOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Pediatric AnesthesiaVolume 30, Issue 10 p. 1160-1161 CORRESPONDENCE COVID-19 and congenital heart disease: Cardiopulmonary interactions for the worse! Rohan Magoon, Corresponding Author Rohan Magoon [email protected] orcid.org/0000-0003-4633-8851 Department of Cardiac Anaesthesia, Atal Bihari Vajpayee Institute of Medical Sciences (ABVIMS), Dr. Ram Manohar Lohia Hospital, New Delhi, India Correspondence Rohan Magoon, Department of Cardiac Anaesthesia, Atal Bihari Vajpayee Institute of Medical Sciences (ABVIMS), Dr. Ram Manohar Lohia Hospital, Baba Kharak Singh Marg, New Delhi 110001, India. Email: [email protected]Search for more papers by this author Rohan Magoon, Corresponding Author Rohan Magoon [email protected] orcid.org/0000-0003-4633-8851 Department of Cardiac Anaesthesia, Atal Bihari Vajpayee Institute of Medical Sciences (ABVIMS), Dr. Ram Manohar Lohia Hospital, New Delhi, India Correspondence Rohan Magoon, Department of Cardiac Anaesthesia, Atal Bihari Vajpayee Institute of Medical Sciences (ABVIMS), Dr. Ram Manohar Lohia Hospital, Baba Kharak Singh Marg, New Delhi 110001, India. Email: [email protected]Search for more papers by this author First published: 30 September 2020 https://doi.org/10.1111/pan.14004Citations: 17 Britta von Ungern-Sternberg Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookxLinkedInRedditWechat No abstract is available for this article. REFERENCES 1Lee-Archer P, von Ungern-Sternberg BS. Pediatric anesthetic implications of COVID-19 – a review of current literature. Paediatr Anaesth. 2020; 30(6): 136-141. 10.1111/pan.13889 Web of Science®Google Scholar 2Cristiani L, Mancino E, Matera L, et al. Will children reveal their secret? The coronavirus dilemma. Eur Respir J. 2020; 55:2000749. 10.1183/13993003.00749-2020 CASPubMedWeb of Science®Google Scholar 3Radke RM, Frenzel T, Baumgartner H, Diller G-P. Adult congenital heart disease and the COVID-19 pandemic. Heart. 2020; 106(17): 1302-1309. 10.1136/heartjnl-2020-317258 CASPubMedWeb of Science®Google Scholar 4Shekerdemian LS, Mahmood NR, Wolfe KK, et al. Characteristics and outcomes of children with coronavirus disease 2019 (COVID-19) infection admitted to US and Canadian pediatric intensive care units. JAMA Pediatr. 2020. https://doi.org/10.1001/jamapediatrics.2020.1948. [Online ahead of print] 10.1001/jamapediatrics.2020.1948 PubMedWeb of Science®Google Scholar 5 Covid-19 (corona virus): vulnerable groups with congenital heart disease; 2020. https://www.bcca-uk.org/pages/news_box.asp?NewsID=19495710. Accessed August 1, 2020. [Accessed 01 August 2020]. Google Scholar 6Bitsadze VO, Grigoreva K, Khizroeva JK, et al. Novel coronavirus infection and Kawasaki disease. J Matern-Fetal Neonatal Med. 2020; 1-5. https://doi.org/10.1080/14767058.2020.1800633. [Online ahead of print] Web of Science®Google Scholar 7Worku E, Gill D, Brodie D, Lorusso R, Combes A, Shekar K. Provision of ECPR during COVID-19: evidence, equity, and ethical dilemmas. Crit Care. 2020; 24: 462. PubMedWeb of Science®Google Scholar Citing Literature Volume30, Issue10October 2020Pages 1160-1161 ReferencesRelatedInformation

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.284
Teacher spread0.257 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations20
Published2020
Admission routes1
Has abstractyes

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