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Record W4318777216 · doi:10.1186/s12884-023-05409-8

Perinatal characteristics and neonatal outcomes of singletons and twins in Chinese very preterm infants: a cohort study

2023· article· en· W4318777216 on OpenAlexafffund
Min Yang, Lingyu Fang, Yanchen Wang, Yun Cao, Jianhua Sun, Joseph Ting, Xiafang Chen, Xiaobo Fan, Jiale Dai, Xiao-Mei Tong, Dongmei Chen, Jimei Wang, Shoo K. Lee, Chao Chen, Lizhong Du, Wenhao Zhou, Falin Xu, Xiuying Tian, Huayan Zhang, Yong Bae Ji, Zhankui Li, Jingyun Shi, Xindong Xue, Chuanzhong Yang, Sannan Wang, Ling Liu, Xirong Gao, Hui Wu, Changyi Yang, Shuping Han, Ruobing Shan, Hong Jiang, Gang Qiu, Qiufen Wei, Rui Cheng, Wenqing Kang, Mingxia Li, Yiheng Dai, Lili Wang, Jiang-Qin Liu, Zhenlang Lin, Yuan Shi, Xiuyong Cheng, Jiahua Pan, Qin Zhang, Xing Lin Feng, Qin Zhou, Long Li, Pingyang Chen, Ling Yang, Deyi Zhuang, Yongjun Zhang, Jinxing Feng, Li Li, Xin-Zhu Lin, Yinping Qiu, Kun Liang, Li Ma, Liping Chen, Liyan Zhang, Hongxia Song, Zhaoqing Yin, Mingyan Hei, Huiwen Huang, Dong Li, Guofang Ding, Qianshen Zhang, Xiaolu Ma

Bibliographic record

VenueBMC Pregnancy and Childbirth · 2023
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsMedicineOdds ratioObstetricsPediatricsGestational ageCaesarean sectionPopulationConfidence intervalRespiratory distressNeonatal intensive care unitBirth weightPregnancyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The prevalence of preterm birth has been rising, and there is a paucity of nationwide data on the perinatal characteristics and neonatal outcomes of twin deliveries of very preterm infants (VPIs) in China. This study compared the perinatal characteristics and outcomes of singletons and twins admitted to neonatal intensive care units (NICUs) in China. METHODS: The study population comprised all infants born before 32 weeks in the Chinese Neonatal Network (CHNN) between January 2019 and December 2019. Three-level and population-average generalized estimating equation (GEE)/alternating logistic regression (ALR) models were used to determine the association of twins with neonatal morbidities and the use of NICU resources. RESULTS: During the study period, there were 6634 (71.2%) singletons and 2680 (28.8%) twins, with mean birth weights of 1333.70 g and 1294.63 g, respectively. Twins were significantly more likely to be delivered by caesarean section (p < 0.01), have antenatal steroid usage (p = 0.048), have been conceived by assisted reproductive technology (ART) (p < 0.01), have a higher prevalence of maternal diabetes (p < 0.01) and be inborn (p < 0.01) than singletons. In addition, twins had a lower prevalence of small for gestational age, maternal hypertension, and primigravida mothers than singletons (all p < 0.01). After adjusting for potential confounders, twins had higher mortality rates (adjusted odds ratio [AOR] 1.28, 95% confidence interval [CI] 1.10-1.49), higher incidences of short-term composite outcomes (AOR 1.28, 95% CI 1.09-1.50), respiratory distress syndrome (RDS) (AOR 1.30, 95% CI 1.12-1.50), and bronchopulmonary dysplasia (BPD) (AOR 1.10, 95% CI 1.01-1.21), more surfactant usage (AOR 1.22, 95% CI 1.05-1.41) and prolonged hospital stays (adjusted mean ratio 1.03, 95% CI 1.00-1.06), compared to singletons. CONCLUSION: Our work suggests that twins have a greater risk of mortality, a higher incidence of RDS and BPD, more surfactant usage, and longer NICU stays than singletons among VPIs in China.

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)0.000
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 score0.010
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.011
GPT teacher head0.266
Teacher spread0.255 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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