Suction assisted surgical extraction of subcutaneous lipoma
Bibliographic record
Abstract
Background: Lipomas are the most common benign mesenchymal tumours in the body. Patients seek their removal due to disfigurement, discomfort or cancerphobia. Historically, open surgical removal was the mainstay of their treatment but striving for less scarring, liposuction is the only new FDA approved alternative. Methods: 56 patients with subcutaneous lipoma of size 3 cm - 10 cm and fulfilling eligibility criteria were selected for this hospital based prospective cohort study after informed consent and Institutional Ethical Committee approval from June 2016 to July 2018. 3 mm irrigation cannula, 5 mm suction cannula, Suction holding tool and Luer lock syringe were used. Lipoma infiltrated with modified Klein solution. Lipoma suctioned out & through the same port, capsule in the cavity was pulled out employing long forceps. Results observed with regards to operative time, post-operative scars, post operative pain and recurrence. Result: A total of 56 patients were enrolled, operated, and observed. Mean duration of lipoma removal surgery was 47.32 minutes. 67.85% patients had pain score 1 after 2 hours of surgery. 100% of patients had healthy scars. 80.4% patients had 0 Vancouver Scarscore after 6 month follow up and only 1 patient had recurrence in 5 months. Conclusions: Our study showed good results in view of postoperative pain and quality of scar. Use of 5 mm cannula gave visually negligible scar with less than 2% recurrence rate. Even though the mean duration of surgery was 47 mins which is more compared to open excision, the good cosmetic result with minimal to no scar prevails over it.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Case report | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Case report | high |
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".