The Impact of Individualizing Sodium Bicarbonate Supplementation Strategies on World-Class Rowing Performance
Bibliographic record
Abstract
Contemporary meta-analyses have generally demonstrated a positive effect of sodium bicarbonate (NaHCO3) supplementation on exercise performance. However, despite these claims, there is limited data on contrasting individualized and standardized timing of NaHCO3 ingestion prior to exercise to further enhance performance outcomes. Purpose: To determine whether NaHCO3 ingestion timing impacts 2000-m rowing time-trial (TT) performance in elite-level rowers (Senior National team including Olympic/World Championships level) adhering to their own individualized pre-race strategies (e.g. nutrition, warm-up, etc.). Methods: Twenty three (n = 23) rowers across two research centers (using the exact same methods/protocols) completed three trials: NaHCO3 loading profile at rest to determine the individual’s time-to-peak bicarbonate concentration [HCO3-], followed by two randomized 0.3 g·kgBM-1 NaHCO3 supplementation experimental trials conducted at different time points (consensus timing (CON): TT performed 60 min post-NaHCO3 ingestion; and individualized peak (IP): TT performed at the rower’s individual peak [HCO3-] determined from the profiling trial post-NaHCO3 ingestion). Results: There was a significant mean difference of +2.9 (± 0.4) mmol·L-1 HCO3- for IP vs. CON (95% CI 2.0 to 3.8 mmol·L-1); p = 0.02; d = 1.08) at pre warm-up, but not immediately prior to the TT (post warm-up). Performance times were significantly different between IP (367.0 ± 10.5 s) versus CON (369.0 ± 10.3 s); p = 0.007; d = 0.15). Conclusions: The present study demonstrated a small but significant performance effect of an individualized NaHCO3 ingestion strategy. Similarities after warm-up between pre-TT sHCO3- values (CON ~ + 5.5 mmol·L-1; IP ~ + 6 mmol·L-1), however, would suggest this effect was not a result of any meaningful differences in blood alkalinity.
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 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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".