骨盆腔器官脫垂的黃金治療為薦骨陰道固定手術，然而同時進行次全子宮切除手術是否對預後及併發症有所改善，至今仍無明確定論。本回溯性研究比較了88位接受機器人輔助薦骨陰道固定術的患者，探討同時進行次全子宮切除術是否能帶來額外好處。

研究結果顯示，合併次全子宮切除術並未顯著改善治療成功率或降低併發症風險，兩組在術後併發症發生率(16.7% vs. 18.4%)及12個月主觀成功率(96.6% vs. 92.2%)均無統計學差異。然而值得注意的是，接受次全子宮切除術的患者中，重度子宮脫垂的比例明顯較高(35.1% vs. 10.2%)，這種選擇偏差可能影響研究結果的客觀性，因為病況較嚴重的患者本身預後可能相對較差。

此外，中位數12個月的追蹤期間雖足以評估短期安全性，但對於評估長期療效仍稍嫌不足。考量到骨盆腔器官脫垂具有復發特性，需要更長期的追蹤才能真正評估兩種術式在持久性方面的差異。

儘管存在上述方法學限制，這項研究仍提供重要的臨床參考。在機器人手術技術持續進步的當代，研究結果支持採用個體化治療策略的臨床實務方向，根據患者的病況及個人偏好來制定適合的手術計畫，而非採用一體適用的標準化做法。

Introduction and Hypothesis
After the age of 80, the cumulative incidence of surgery of pelvic organ prolapse (POP) exceeds 15%. While concomitant supracervical hysterectomy (SCH) is very popular at the time of sacrocolpopexy in some parts of the world, it is rarely performed in many European countries. The aim of the present study was to compare the outcomes of robotic sarcrocolpopexy with or without SCH.

Methods
The charts of all consecutive patients who underwent minimally invasive sacrocolpopexy for POP at a single center between 2013 and 2023 were included in a retrospective study. The remaining patients were included for analysis and divided in two groups: with (HYST) vs. without (no HYST) supracervical hysterectomy.

Results
Out of 197 minimally invasive sacrocolpopexy, 88 were included in the present analysis: 39 in the HYST group and 49 in the no-HYST group. The only statistically significant difference at baseline between the two groups was the higher proportion of grade 3 or 4 uterine prolapse in the HYST group (35.1% vs. 10.2%; p = 0.01). The postoperative complications rates were similar in both groups (16.7% vs. 18.4%; p = 0.84). After a median follow-up of 12 months, the subjective success rate was similar (96.6% vs. 92.2%; p = 0.44). Most outcomes were not significantly different.

Conclusions
In the present study, we did not demonstrate a benefit for SCH at the time of sacrocolpopexy. However, we did not observe an increased morbidity in the HYST group, suggesting that it may not exist anymore beyond the learning curve in the robotic era.