Saline Lock and Continuous Infusion Peripheral IV Duration
Bibliographic record
Abstract
Source: Yeung F, , Miller MR, , Ojha R, , et al. Saline-lock versus continuous infusion: maintaining peripheral intravenous catheter access in children. Hosp Pediatr. 2020;10(12):1038-1043; doi:10.1542/hpeds.2020-0137[OpenUrl][1][Abstract/FREE Full Text][2] Investigators from Children’s Hospital, London Health Sciences Centre, London, Ontario, Canada, conducted a prospective study to assess the effectiveness of 2 different techniques to maintain peripheral intravenous (PIV) patency in hospitalized children not requiring PIV fluids for hydration. Specifically, the investigators compared using a continuous infusion at a slow rate “to keep vein open” (TKO), or using a saline lock (SL). Study participants were patients, 0 to 17 years old, admitted to a tertiary care children’s hospital between September 2018 and February 2019 in whom a PIV was placed. During the first 3 months of the study, once fluids were no longer needed for patency, PIV patency … [1]: {openurl}?query=rft.jtitle%253DHosp%2BPediatr%26rft_id%253Dinfo%253Adoi%252F10.1542%252Fhpeds.2020-0137%26rft_id%253Dinfo%253Apmid%252F33172866%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=hosppeds&resid=10/12/1038&atom=%2Faapgrand%2F45%2F3%2F32.atom
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".