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Record W6925025436 · doi:10.17605/osf.io/k5nup

Does dietitian involvement during pregnancy improve birth outcomes? A systematic review

2022· other· en· W6925025436 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

VenueOpen Science Framework · 2022
Typeother
Languageen
FieldComputer Science
TopicNumerical Methods and Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsPregnancyPsychological interventionPrenatal careLow birth weightMedical nutrition therapyIntervention (counseling)Incidence (geometry)Health care

Abstract

fetched live from OpenAlex

Healthy pregnancies can be achieved through sufficient weight gain, balanced diets, appropriate vitamin and mineral supplementation, avoidance of alcohol and harmful substances, as well as food safety (Procter et al., 2014). While most prenatal care providers do not have substantial training in nutrition, we believe that registered dietitians being healthcare professionals, can assist pregnant patients in attaining optimal birth outcomes. In Canada and the US, registered dietitians are not required members of health care teams for prenatal care, but can be referred to for medical nutrition therapy to assist women with weight gain, hyperemesis, multiple gestations, poor dietary patterns, and chronic disease (Procter et al, 2014). Given their expertise in nutrition and the importance of nutrition during pregnancy, registered dietitians have the potential to positively influence birth outcomes. However, studies supporting their roles have not been comprehensively evaluated (Pari-Keener et al., 2020) and existing studies have been inconsistent. Some studies have supported that interventions provided by dietitians improve infant birth outcomes. Research by Vesco et al. suggests that intensive dietary intervention initiated by dietitians is associated with a decrease in prevalence of large-for-gestational age infants (9%) compared to groups receiving only one-time dietary advice (26%) (2014). Additionally, research by Crowther et al. shows a significantly low incidence of large-for-gestational age (13%) and macrosomia (10%) infants as a result of dietitian involvement compared to its control group (22% and 21%) (2005). However, other studies indicate no effect on infant or maternal outcomes (Koivusalo et al., 2016; Dodd, Deussen & Louise, 2019). So far, no systematic review has directly studied the effect of dietitian involvement on birth outcomes. Thus, this review will examine the extent to which dietitian involvement during pregnancy is associated with improved birth outcomes. References Crowther, C. A., Hiller, J. E., Moss, J. R., McPhee, A. J., Jeffries, W. S., Robinson, J. S., & Australian Carbohydrate Intolerance Study in Pregnant Women (ACHOIS) Trial Group (2005). Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. The New England journal of medicine, 352(24), 2477–2486. https://doi.org/10.1056/NEJMoa042973 Dodd, J. M., Deussen, A. R., & Louise, J. (2019). A Randomised Trial to Optimise Gestational Weight Gain and Improve Maternal and Infant Health Outcomes through Antenatal Dietary, Lifestyle and Exercise Advice: The OPTIMISE Randomised Trial. Nutrients, 11(12), 2911. https://doi.org/10.3390/nu11122911 Koivusalo, S. B., Rönö, K., Klemetti, M. M., Roine, R. P., Lindström, J., Erkkola, M., Kaaja, R. J., Pöyhönen-Alho, M., Tiitinen, A., Huvinen, E., Andersson, S., Laivuori, H., Valkama, A., Meinilä, J., Kautiainen, H., Eriksson, J. G., & Stach-Lempinen, B. (2016). Gestational Diabetes Mellitus Can Be Prevented by Lifestyle Intervention: The Finnish Gestational Diabetes Prevention Study (RADIEL): A Randomized Controlled Trial. Diabetes care, 39(1), 24–30. https://doi.org/10.2337/dc15-0511 Pari-Keener, M., Gallo, S., Stahnke, B., McDermid, J. M., Al-Nimr, R. I., Moreschi, J. M., Hakeem, R., Handu, D., & Cheng, F. W. (2020). Maternal and Infant Health Outcomes Associated with Medical Nutrition Therapy by Registered Dietitian Nutritionists in Pregnant Women with Malnutrition: An Evidence Analysis Center Systematic Review. Journal of the Academy of Nutrition and Dietetics, 120(10), 1730–1744. https://doi.org/10.1016/j.jand.2019.10.024 Procter, S. B., & Campbell, C. G. (2014). Position of the Academy of Nutrition and Dietetics: nutrition and lifestyle for a healthy pregnancy outcome. Journal of the Academy of Nutrition and Dietetics, 114(7), 1099–1103. https://doi.org/10.1016/j.jand.2014.05.005 Vesco, K. K., Karanja, N., King, J. C., Gillman, M. W., Leo, M. C., Perrin, N., McEvoy, C. T., Eckhardt, C. L., Smith, K. S., & Stevens, V. J. (2014). Efficacy of a group-based dietary intervention for limiting gestational weight gain among obese women: a randomized trial. Obesity (Silver Spring, Md.), 22(9), 1989–1996. https://doi.org/10.1002/oby.20831

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0150.009
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.328
Teacher spread0.309 · 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