Effect of gastric residual volume monitoring on incidence of ventilator-associated pneumonia in mechanically ventilated patients admitted to intensive care unit
Bibliographic record
Abstract
Objectives: The value of gastric residual volume (GRV) monitoring in ventilator-associated pneumonia (VAP) has frequently been questioned in the past years. In this trial, the effect of GRV on the frequency of VAP was evaluated in critically ill patients under mechanical ventilation.
 Methods: This descriptive study was carried out on 150 adult patients admitted to the intensive care unit over a 14-month period, from October 2015 to January 2017. GRV was measured every three hours, and gastric intolerance was defined as GRV>250 cc. The incidence of vomiting and VAP, GRV, length of mechanical ventilation and ICU stay, APACHE II and SOFA scores, and mortality rate were noted.
 Results: The mean APACHEII and SOFA scores, ICU length of stay, and duration of mechanical ventilation in the GRV>250ml group were significantly higher than in the GRV≤250 ml group (P<0.05). Also, a significantly higher number of patients in the GRV>250ml group experienced infection (62.3%) and vomiting (71.7%) compared with the GRV≤250 group (P<0.01). The highest OR was observed for SOFA score >15 and APACHE II >30, which increased the risk of GVR>250 ml by 10.09 (1.01-99.97) and 8.78 (1.49-51.58), respectively. Moreover, the increase in GVR was found to be higher in the non-survivor than in the survivor group.
 Conclusion: Increased GRV did not result in increased rates of VAP, ICU length of stay, and mortality. Therefore, the routine measurement of GRV as an important element of the VAP prevention bundle is not recommended in critically ill patients.
 How to cite this:
 Faramarzi E, Mahmoodpoor A, Hamishehkar H, Shadvar K, Iranpour A, Sabzevari T, et al. Effect of gastric residual volume monitoring on incidence of ventilator-associated pneumonia in mechanically ventilated patients admitted to intensive care unit. Pak J Med Sci. 2020;36(1):---------. doi: https://doi.org/10.12669/pjms.36.1.1321
 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".