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Record W3087208669

Intrauterine Bakri balloon for management of postpartum hemorrhage using multicenter data

2020· article· en· W3087208669 on OpenAlexaboutno aff
Huili Zhang

Bibliographic record

VenueGynecology & Obstetrics Case report · 2020
Typearticle
Languageen
FieldMedicine
TopicMaternal and fetal healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBalloonSurgeryObstetrics
DOInot available

Abstract

fetched live from OpenAlex

Objective: To evaluate the effect of intrauterine Bakri balloon for the management of postpartum hemorrhage (PPH). Methods: This prospective cohort study included all women with postpartum bleeding who underwent intrauterine Bakri balloon from November 2018 to September 2019 in 31 tertiary public hospitals in China. Women were divided in four groups according to the blood loss before using the intrauterine Bakri balloon. Maternal characteristics, laboratory indices, medical/surgical interventions and maternal outcomes were recorded. Results: Overall, 732 women treated by Bakri balloon to control bleeding and 720 women were enrolled (180 after vaginal delivery and 540 during or after cesarean delivery). The success rate was 97.6% (17/720). The group with a hemorrhage ≥ 1000 mL before using Bakri balloon had significantly more blood loss after balloon insertion (562.74 ±628.565 ml) compared with other three groups (230.38 i?± 206.856 ml, 328.92 i?±i? 347.429 ml and 487.93 ± 554.007 ml) (P < 0.05). The maternal hemoglobin (97.11 ± 21.13 g/L) was lower than that in the group with hemorrhage ≤400 ml (110.83 ± 14.98 g/L), 401-800 ml group (111.26 ± 15.21g/L), 800 - 1000 ml group (108.99 ±21.09 g/L). Conclusion: The early usage of the Bakri balloon is more effective for the management of PPH. Biography: Huili Zhang got her Ph.D. degree from Guangzhou medical university, during this time she worked on the newborn lung disease at MGH for two years. After graduation, she is working as a grade two resident in obstetrics and gynecology at the Third Affiliated Hospital of Guangzhou Medical University. As a resident, she has trained how to treat women during prenatal and postnatal periods, deliver infant, perform cesarean section or other surgical procedure as needed to preserve patients’ health deliver infant safely. In addition, she has no difficulty communicating in English with her foreign friends as her teachers come from Canada, America and the UK. She is also skilled in reading documents relating to clinical and scientific research. In her free time, she enjoys playing basketball, jogging and cycling by the park

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.112
GPT teacher head0.358
Teacher spread0.247 · 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 designCase report
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

Citations0
Published2020
Admission routes1
Has abstractyes

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