Liposuction Infiltration: The Quito Formula – a New Approach Based On An Old Concept
Bibliographic record
Abstract
INTRODUCTION: Liposuction is a highly sought after surgical procedure. Despite its popularity, not all of the factors associated with its execution are well understood. No well-established guidelines exist for plastic surgeons regarding the subcutaneous infiltration of fluid and, thus, the procedure is often performed subjectively. OBJECTIVE: To establish the usefulness of the Quito formula (infiltrate volume = weight [kg] × percentage of body surface to be liposuctioned × 2.4 [mL]) for calculating the volume of fluid to be infiltrated subcutaneously during small-volume liposuction performed under epidural anesthesia. METHODS: A prospective study was conducted on a group of 50 patients who were candidates for liposuction on multiple body parts between November 2004 and February 2010. RESULTS: The maximum volume of infiltrate was 5000 mL and the maximum volume of aspirate was 4500 mL, with a 30% total aspirated area. No patient required blood transfusion, and there were no major complications. However, one patient presented with a small local infection, another with a sacral seroma and two patients had postdural puncture headaches. No patient showed clinical signs consistent with overhydration, dehydration, pulmonary embolism, fat embolism or lidocaine intoxication. CONCLUSIONS: When performing small-volume liposuction, subcutaneous infiltration using the Quito formula to calculate the volume of infiltrate proved to be useful, safe and objective.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".