Blood Samples of Peripheral Venous Catheter or The Usual Way: Do Infusion Fluid Alters the Biochemical Test Results?
Bibliographic record
Abstract
BACKGROUND: Most blood tests require venous blood samples. Puncturing the vein also causes pain, infection, or damage to the blood, and lymph flow, or long-term healing. This study aimed to determine and compare the biochemical laboratory value of the blood samples that were provided through: peripheral vein infusion (PVI) receiving continuous intravenous fluid; and the usual method of blood sampling. METHODS: This is an interventional, quasi-experimental, and controlled study. The selected study sample included 60 patients, who were hospitalized during 2014, in the Internal Medicine, part of Martyrs of Persian Gulf, teaching hospital at Bushehr. Three blood samples were taken from each patient that were provided through PVI line (5 ml blood collected at beginning of IVC and then another 5 cc), and another case was prepared by common blood sampling (control). All the samples were analyzed in terms of sodium, potassium, urea and creatinine using SPSS Ver.19 software, by paired t-test and Pearson's correlation coefficients. RESULTS: There was a statistically significant difference between the amount of sodium and potassium in the first blood samples taken from the intravenous infusion line and vein puncture .However, no significant differences were found among the biochemical amount in the second blood samples taken from the intravenous infusion line and vein puncture. CONCLUSIONS: We can use blood samples taken from peripheral intravenous infusion lines after 5cc discarding from the first part of the sample for measuring the value of sodium, potassium, urea and creatinine.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".