Improving cognitive function with intermittent dose escalation of curcumin extract in chemotherapy-induced cognitive impairment patients: a randomized controlled trial
Bibliographic record
Abstract
Abstract Chemotherapy-induced cognitive impairment (CICI) is an impairment of memory, learning power, concentration, reasoning, executive function, attention, and visuospatial during and after chemotherapy exposures. No proven safe and effective therapeutic regimen are available to improve cognitive function in CICI patients. To evaluate the safety and effectiveness of curcumin extract to improve cognitive function in CICI patients. This study was a double-blind randomized controlled trial clinical trial in patients with cervical carcinoma who underwent a carboplatin-paclitaxel chemotherapy regimen from March to October 2021 at single center hospital. Subjects divided into two groups that received curcumin and placebo caplets by dose escalation method from 240 to 400 mg intermittently (14 days on and 7 days off) between chemotherapy cycles. Cognitive function was evaluated pre- and post-therapy using the AFI questionnaire, Stroop test, and MoCA-Ina. A total of 78 subjects were equally divided into the treatment and control groups. The percentage of drop-out, mortality, and adverse drug response were relatively comparable between each treatment arm. The group of subjects receiving curcumin extract experienced clinically and statistically significant improvements in cognitive function based on the Stroop test (∆ median 8.57 vs. 2.46; Z − 4.503 vs. − 1.762; p < 0.0001 vs. 0.078) and MoCA- Ina (∆ mean 1.53 vs. 0.72; Z − 2.99 vs. − 2.05; p < 0.003 vs. 0.04) versus placebo in between-group and between-subject analyses, respectively. Administration of curcumin extract with intermittent dose escalation regimen proved to be safe and able to improve cognitive function of CICI patients clinically and statistically significant.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".