Effectiveness and safety of endoscopy-assisted versus conventional open lateral neck dissection: A meta-analysis
Bibliographic record
Abstract
The objective of this study was to systematically evaluate the effectiveness and safety of endoscopic-assisted lateral neck dissection (EALND) compared with conventional open lateral neck dissection (COLND) for the treatment of thyroid cancer with positive lymph node metastases. Medical literature databases including PubMed, Embase, the Cochrane Library, CNKI, Wan Fang and VIP were systematically searched for articles that compared EALND and COLND for the treatment of thyroid carcinoma with lymph node metastasis, up to June 2019. The quality of included studies was evaluated using the Newcastle-Ottawa Scale (NOS). Meta-analysis was performed using RevMan 5.3 software after two evaluators independently screened the literature, extracted information and evaluated the methodological quality of included studies according to inclusion and exclusion criteria, resulting in the selection of seven studies with a total of 372 patients from six non-RCTs and an RCT. The results of meta-analysis showed that EALND was associated with a longer operative time (MD = 24.86, 95∗CI：21.76 to 27.96, P＜0.05), with a shorter postoperative stay (MD = -1.45, 95％CI：-2.70 to -0.21，P = 0.02), reduced length of scar (MD = -8.14，95％CI：-8.41 to -7.88, P＜0.00001) and a lower incidence of neck discomfort (OR = 0.19, 95％CI：0.07 to 0.58, P = 0.003) compared with COLND. The incidences in both groups of transient hypocalcemia (OR = 0.66，95％CI：0.28 to 1.55，P = 0.343), transient hoarseness (OR = 0.58，95％CI：0.17 to 1.93，P = 0.38)，chylous fistula (OR = 0.69，95％CI：0.26 to 1.83，P = 0.45), choking on water (OR = 0.24，95％CI：0.04 to 1.31，P = 0.10) and the number of lymph nodes retrieved from the lateral cervical region (MD = 0.14，95％CI：-0.36 to 0.65，P = 0.59) were not statistically significant. It was concluded that EALND was safe and feasible compared with COLND, despite the longer operation time. The incision was more aesthetically pleasing and the postoperative recovery was quicker, which makes EALND a clinical procedure worthy of use in such cases.
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How this classification was reachedexpand
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 | 0.017 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.053 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".