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Record W7016900344

铁代谢指标及膳食铁摄入指标与妊娠期糖尿病关系的Meta分析

2021· other· zh· W7016900344 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLanzhou University Institutional Repository · 2021
Typeother
Languagezh
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)Diabetes mellitusWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

目的收集文献进行荟萃分析,探讨血清铁代谢指标、膳食中铁摄入指标与妊娠期糖尿病(Gestational Diabetes Mellitus,GDM)的关系。\n\n方法使用计算机检索PubMed、Web of Science、Embase、Cochrane Library四大数据库网站,检索时限为建库至2020年9月的英文文献。收集评估血清铁代谢指标、膳食铁摄入指标及补充铁和GDM关系的前瞻性队列研究或病例对照研究,按照纳入和排除标准筛选文献。对纳入文献进行质量评估,提取各指标的数据如均数±标准差(Mean±SD)、相对危险度(Relative risk,RR)、比值比( OddsRatio,OR)等,通过stata 15.1软件进行数据分析。使用标准化均值差( Standard Mean Difference,SMD)、RR、OR和95%可信区间(Confidence Interval,CI)来计算合并效应量。同时为评估总合并效应是否可信进一步行亚组分析及敏感性分析。\n\n结果\n\n(1)共纳入40篇文献,其中病例对照研究21项,队列研究19项;12项研究来自亚洲地区,16项来自中东地区,12项来自欧美地区。所有文献的Newcastle-Ottawa Scale(NOS)质量评分均大于5分;其中,关于血清铁代谢标与GDM关系的文献共30篇,关于膳食铁摄入指标与GDM关系的文献4篇,关于补充铁与GDM关系的文献7篇;\n\n(2)GDM组患者血清铁[SMD=0.40<a href="https://www.baidu.com/s?tn=request_18_pg&wd=%CE%BCg%E5%9C%A8%E7%94%B5%E8%84%91%E4%B8%8A%E6%80%8E%E4%B9%88%E6%89%93&ie=utf-8&rsf=11630013&rsv_dl=0_prs_28608_1&rsv_pq=8e627f620002f06d&rsv_t=94c7FvUPgxx2Fs9D9ydwpxakefBeUIVUEugIa8iisUM2WrLR4XOXY0LwHngYxgedqX4uYw&oq=">μg</a>/dL,95%CI(0.16,0.64), p= 0.001]、铁蛋白[SMD=0.58ng/mL, 95%CI(0.35,0.81), p<0.001 ]、血红蛋白[SMD=0.48g/dL,95%CI(0.28,0.67),p<0.001]、转铁蛋白饱和度[SMD=0.52%,95%CI(0.35,0.70),p=0.018]、铁调素[SMD= 0.63ng/mL,95%CI(0.09,1.18),p=0.023]水平均高于非GDM组;GDM组患者总铁结合力[SMD=-0.53<a href="https://www.baidu.com/s?tn=request_18_pg&wd=%CE%BCg%E5%9C%A8%E7%94%B5%E8%84%91%E4%B8%8A%E6%80%8E%E4%B9%88%E6%89%93&ie=utf-8&rsf=11630013&rsv_dl=0_prs_28608_1&rsv_pq=8e627f620002f06d&rsv_t=94c7FvUPgxx2Fs9D9ydwpxakefBeUIVUEugIa8iisUM2WrLR4XOXY0LwHngYxgedqX4uYw&oq=">μg</a>/dL,95%CI (-1.05,-0.02)<a href="https://www.baidu.com/s?tn=request_18_pg&wd=%CE%BCg%E5%9C%A8%E7%94%B5%E8%84%91%E4%B8%8A%E6%80%8E%E4%B9%88%E6%89%93&ie=utf-8&rsf=11630013&rsv_dl=0_prs_28608_1&rsv_pq=8e627f620002f06d&rsv_t=94c7FvUPgxx2Fs9D9ydwpxakefBeUIVUEugIa8iisUM2WrLR4XOXY0LwHngYxgedqX4uYw&oq=">μg</a>/dL,p=0.001]水平显著低于非GDM组;转铁蛋白受体水平两组无差异(p>0.05)。\n\n<p style="margin-left:11.9500pt">(3)与低水平相比,高水平铁蛋白[OR=1.92, 95%CI (1.59,2.32) ,p<0.001]、血红蛋白[OR=1.30, 95%CI(1.04,1.63),p=0.023]与GDM的发生风险相关。进行参数调整后,高水平铁蛋白与GDM风险的关联仍存在[OR=2.25, 95%CI (1.67, 3.03),p<0.001];而进行参数调整后,血红蛋白与GDM风险的关联不存在[OR=1.17,95% CI(0.94,1.45), p=0.150]。\n\n(4)膳食中低、高血红素铁水平与GDM的发生风险均相关[OR= 1.25,95%CI(1.05,1.49),p=0.001和OR=2.27,95% CI (1.90, 2.71),p<0.0001]。经参数调整后,膳食中低、高血红素铁水平与GDM的发生风险仍存在关联性[OR=1.20,95%CI(1.00,1.44) , p=0.051和OR=1.71,95%CI(1.39,2.11),p<0.001]。膳食总铁水平、膳食非血红素铁水平均与GDM的发生风险无关。\n\n(5)孕期补充铁与GDM的发生风险无显著相关性[OR=1.23,95% CI(0.99,1.51),p=0.057]。\n\n结论\n\n(1)GDM患者血清铁、血红蛋白、铁蛋白、转铁蛋白饱和度、铁调素水平均高于非GDM组;总铁结合力水平低于非GDM组,而转铁蛋白受体两组间无差异;高血清铁蛋白、血红蛋白水平与GDM的发生风险相关。\n\n(2)膳食中高血红素铁水平与GDM的发生风险相关。随着血红素铁水平的升高,GDM风险增加;膳食总铁、非血红素铁水平与GDM的发生风险无关。\n\n(3)孕期补充铁与GDM的发生风险无关。\n\n\n\n关键词:铁,铁蛋白,铁摄入,妊娠期糖尿病

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.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0240.002

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 head0.010
GPT teacher head0.164
Teacher spread0.153 · 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