Predictors of Post-operative ABG Changes to Pre-operative Levels in Kidney Transplant Patients, a Cross-Sectional Study
Bibliographic record
Abstract
Background: Kidney transplant is the treatment of choice for chronic renal failure (CRF), significantly improving patient outcomes. Fluid administration during surgery can lead to the accumulation of acid ions and electrolytes, inducing pH changes from the pre-operative to post-operative period, which may compromise transplant success. The impact of acid-base balance changes on transplant outcomes is crucial, yet research on predictors and arterial blood gas (ABG) changes post-kidney transplant is limited. Understanding ABG changes can enhance perioperative management, early detection of complications, and long-term graft function, thereby optimizing patient care and increasing transplant success rates. Objectives: To assess ABG changes before and after kidney transplant and identify predictors of post-operative acidosis in patients with renal failure through cross-sectional studies. Methods: In a retrospective cohort study, we included 97 patients who had undergone kidney transplant. During surgery, patients received crystalloid fluids, with 49 receiving only normal saline and 48 receiving only Ringer's lactate. Data collection involved the insertion of an arterial line after anesthesia induction, and the first ABG sample was obtained as a pre-operative measure. A post-operative measure was taken at the end of the surgery. Ethical considerations were followed throughout the study. Statistical analysis included paired t-test or Wilcoxon signed-rank test to compare pre- and post-operative ABG measures, with a significance level set at a P-value less than 0.05. Results: Total of 97 patients, which 65 (69.4%) were male and 32 (30.6%) were female and mean age was 38.6 ± 12.2. Variables significantly associated with post-op acidosis were fluid administered (OR: 3.25, 95% CI: 1.45 - 4.58), post-op central venous pressure (CVP) (OR: 2.31, 95% CI: 1.23 - 2.62, p < 0.05), post-op base excess (BE) (OR: 2.16, 95% CI: 1.50 - 2.95, P < 0.05). HCO₃ (P = 0.010), BE (P = 0.002), pH (P = 0.023) were significantly lower in the normal saline group compared to the Ringer's group. Post-op pH and BE was also associated with increased post-op CVP. Post-op acidosis and post-op CVP were significantly associated with post-op BE. Conclusions: Post-operative ABG changes, including decreases in pH and HCO3, are key indicators of transplant outcomes, reflecting graft function and patient stability. These findings highlight the critical need for prompt management of ABG abnormalities to optimize transplant success and minimize complications, making vigilant monitoring a vital part of post-transplant care.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".