Nursing Care and Clinical Considerations in the Management of Suction Drains
Bibliographic record
Abstract
Background: Suction drains are widely used in postoperative care to prevent fluid accumulation, support wound healing, and allow early detection of complications. However, their routine use remains controversial due to associated risks and inconsistent evidence of benefit. Aim: This article aims to review the nursing care and clinical considerations involved in the management of suction drains, emphasizing indications, contraindications, techniques, and multidisciplinary roles. Methods: A narrative review approach was used, synthesizing current clinical evidence and nursing practice guidelines related to suction drain use, management, and complications. Results: Suction drains were shown to be effective when used selectively based on surgical and patient-related factors. Proper insertion technique, vigilant monitoring, accurate documentation, and early removal significantly reduced complications such as infection, blockage, and fistula formation. Nursing care was identified as central to safe drain management. Conclusion: Selective use and meticulous nursing management optimize patient outcomes and minimize drain-related risks.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".