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Enregistrement W4232876276 · doi:10.1111/tog.12358

Editorial

2017· editorial· en· W4232876276 sur OpenAlexaboutno aff
Mark S. Roberts

Notice bibliographique

RevueThe Obstetrician & Gynaecologist · 2017
Typeeditorial
Langueen
DomaineMedicine
ThématiqueEctopic Pregnancy Diagnosis and Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésComputer science

Résumé

récupéré en direct d'OpenAlex

I am writing this editorial while attending the Annual Professional Development conference at the RCOG and can't help noticing how often the subject of obesity comes up. The UK is apparently the fattest nation in Europe with the Republic of Ireland having nothing to be proud about either; all credit to Poland whose inhabitants are positively svelte by comparison. Mohammed Khairy and Madhurima Rajkhowa focus their review on obesity-related infertility. Various professional bodies have stipulated a body mass index of <30−35 kg/m2 before assisted reproduction techniques can be offered. The authors consider the evidence, ethics and interventions. Pradeep Jayaram and colleagues give us a detailed review of caesarean scar ectopic pregnancy. This is a condition that seems to have been increasingly recognised but until recently there was little advice on non-tubal ectopic pregnancy and it was not covered in the latest guidance from the National Institute for Health and Care Excellence (NICE; CG154). It has a greater risk of severe morbidity compared with tubal ectopic pregnancy, partly due to a delayed diagnosis. TOG has published articles on interstitial and abdominal pregnancy and the new RCOG Green-top Guideline, released in November 2016 (GTG 21), not only sets out diagnostic criteria for caesarean section ectopic pregnancy but also covers abdominal, cervical, ovarian, cornual and interstitial pregnancy. It is a heightened awareness that will lead to earlier diagnosis. This article goes into more detail than GTG 21, making it a valuable resource for clinicians. Sana Usman and colleagues discuss the role of magnesium sulfate for neuroprotection in preterm deliveries. While magnesium sulfate (MgSO4) has long been validated as safe and important in the control and prevention of eclampsia, the evidence to support the prevention of cerebral palsy associated with preterm deliveries has taken longer to establish. What seems clear now is that MgSO4 has a modest neuroprotective effect and is currently recommended for use in deliveries less than 30−32 weeks of gestation. The timing, dose and duration of treatment remains undefined; however, most recommend a standard pre-eclampsia protocol used within 4 hours of delivery. The article by Nicholas Reed and Azmat Sadozye considers radiotherapy in gynaecological malignancy. Planning and targeting of treatment has been improved by new imaging modalities and better radiotherapy techniques. The mainstay of radiotherapy is still adjunctive, or in other words after primary surgery. The exception being primary treatment for some cervical and vaginal cancers. For those without an oncology interest, we still need to be aware of ‘late effects’, such as ovarian failure and the psychosexual consequences of vaginal brachytherapy. Susanna Crowe and Sanjula Sharma present a practical guide to quality improvement. They point out that it is not only our duty to engage with processes to enhance the patient experience but also that quality assurance and improvement are embedded as key elements in professional revalidation and a mandatory requirement for trainees. Kevin Cooper and Lucky Saraswat present part 1 of a comprehensive review of the surgical management of heavy menstrual bleeding. For those who cannot wait for part 2, it is available online as an early view article. In part 1 the authors describe endometrial ablation techniques, continuing the debate of ‘which is the best ablation method?’ The article should be considered alongside the 2016 NICE clinical guideline for heavy menstrual bleeding (CG44), with reference to endometrial ablation in section 1.6. The dangers of diabetic ketoacidosis are exacerbated in pregnancy due to challenges with respect to diagnosis, management and prevention. Not only is the incidence of pregnancy-associated diabetes increasing, pregnancy physiology also increases susceptibility to ketoacidosis. Therefore, we welcomed the proposal for the paper by Manoj Mohan and colleagues. The TOG team have supplemented this with an infographic, which is available online. Desiree Kolomainen and colleagues discuss the surgical (and non-surgical) management of bowel obstruction in gynaecological cancer. These patients have often had ovarian cancer treated several years earlier and present as an emergency to the colorectal surgical team with either recurrent disease or adhesion-related obstruction. Decisions for surgery ideally require multidisciplinary and palliative care input bearing in mind the risks and possible short-term benefit. There is no level 1 evidence or national guideline available and surgery is usually performed with palliative intent. This article is particularly useful when faced with an acute admission in general gynaecology and/or to inform surgical colleagues. In this issue we also have the MBRRACE-UK 2016 summary update and key messages from Professor Marian Knight. The overall maternal death rate in the UK was unchanged from the last report, at 8.54 per 100 000. However, specifically highlighted is the need for improved joint working between maternity and cardiac services for women presenting (and often re-presenting) with cardiac symptoms. The summary does recognise good practice in evidence-based care with low death rates related to hypertension. Professor James Drife uses his academic skills to research medical graduate reunions! Perhaps medical reunions have been replaced by virtual real-time reunions or what some call ‘Facebook Friends’. Editorial board Mark Roberts MD MRCOG Royal Victoria Infirmary, Newcastle Upon Tyne Mohamed Abdel-Fattah FRCOG University of Aberdeen, Aberdeen George Attilakos MD MRCOG University College London Hospitals NHS Foundation Trust, London George Attilakos MD MRCOG University College London Hospitals NHS Foundation Trust, London Philippa Corson MRCOG North Middlesex Hospital, London (Trainee Representative) Kate Harding FRCOG Guy's and St Thomas' NHS Foundation Trust, London Justin Konje FMCOG (Nig) FWACS MRCOG University of Leicester, Leicester (Lead CPD Editor) Bid Kumar FRCOG Wrexham Maelor Hospital, Wrexham Kate Langford MA MD MBA FRCOG Guy's and St Thomas' NHS Foundation Trust, London Jo Morrison BM BCh MA MRCOG DPhil (Oxon) Musgrove Park Hospital, Taunton Nicola Mullin MFFP FRCOG Countess of Chester Hospital NHS Foundation Trust, Chester Surabhi Nanda MRCOG Liverpool Women's NHS Foundation Trust, Liverpool Thomas Tang MD MRCOG Regional Fertility Centre, Royal Maternity Hospital, Belfast Ephia Yasmin MRCOG University College London Hospitals NHS Foundation Trust, London Jason Waugh MRCOG (Emeritus Editor) Royal Victoria Infirmary, Newcastle Upon Tyne International advisory board Richard Brown MBBS DFSRH FRCOG FACOG McGillUniversityHealthCentre,Montreal,Canada, Amr El-Shalakany MSc MD FRCOG Ain Shams University Maternity Hospital, Cairo, Egypt Carman Lai MRCOG FHKCOG FHKAM (O&G) Cert RCOG (Maternal and Fetal Medicine) Queen Mary Hospital, University of Hong Kong, Hong Kong Henry Murray MRCOG Australia Dimitrios Koleskas MRCOG Euroclinic, Athens, Greece N Rajamaheswari MD DGO MCh (Urology) Director, Urogynaecology Research Center Pvt Ltd, India Duru Shah MD FCPS FICS FICOG DGO DFP FICMCH Jaslok Hospital, Sir Hurkinsondas Hospital and Breach Candy Research Centers, India David Shaker FRCSEd FRCOG FRANZCOG University of Queensland, Rockhampton Base Hospital and Mater Private Hospital, Australia

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,024
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,086
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,024
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,018
Tête enseignante GPT0,301
Écart entre enseignants0,284 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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