A multicenter, randomized, blinded, controlled clinical trial investigating the effect of a novel infant formula on the body composition of infants: INNOVA 2020 study protocol
Bibliographic record
Abstract
Abstract Background Breastmilk is the ideal food for infants and exclusive breastfeeding is recommended. In the clinical trial aimed to evaluate a new starting formula on weight gain of infants up to 6 and 12 months. The novel formula was compared with a standard formula and breastfeeding, the latter being used as the reference method. Methods 210 infants (70/group) were enrolled in the study, and completed the intervention until 12 months of age. For the intervention period, infants were divided into three groups: group 1 received the formula 1 (Nutribén Innova®1 or INN), with a lower amount of protein, and enriched in α-lactalbumin protein, and with double amount of docosahexaenoic acid (DHA)/ arachidonic acid (ARA) than the standard formula; it also contained a thermally inactivated postbiotic ( Bifidobacterium animalis subsp. lactis , BPL1™ HT). Group 2 received the standard formula or formula 2 (Nutriben® or STD) and the third group was exclusively breastfed for exploratory analysis. During the study, visits were made at 21 days, 2, 4, 6, and 12 months of age, with ± 3 days for the visit at 21 days of age, ± 1 week for the visit at 2 months, and ± 2 weeks for the others. Discussion The findings of this study will provide evidence regarding the beneficial health effects of having a novel starting infant formula with reduced levels of protein, enriched in α-lactalbumin, and increased levels of DHA and ARA, and containing a postbiotic, compared with infants fed standard formula. Trial registration The trial was registered with Clinicaltrial.gov ( NCT05303077 ) on March 31, 2022, and lastly updated on April 7, 2022.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".