Yongue Gabriella, Mollier Josephine, Anin Sheba, Ibeto Linda, Ross Claire, Ayim Francis, Guha Sharmistha
Department of Obstetrics & Gynaecology, West Middlesex University Hospital, Middlesex, UK.
Imperial College School of Medicine, London, UK.
Int J Gynaecol Obstet. 2022 Jun;157(3):588-597. doi: 10.1002/ijgo.13932. Epub 2021 Oct 12.
To create a risk scoring system comprised of clinical and radiological characteristics that can predict the likelihood of antibiotic treatment failure of tubo-ovarian abscesses. The score should guide clinicians in identifying patients to whom early intervention should be offered instead of a prolonged trial of antibiotics.
A multicenter, retrospective cohort study carried out between January 1, 2013 and September 30, 2019, identified consecutive patients with tubo-ovarian abscess. Using a chronological split, patients were allocated to two groups for the development and subsequent validation of the postulated scoring system. Univariate and bivariate analyses were performed to identify statistically significant variables for the failure of intravenous antibiotic treatment.
In total, 214 consecutive patients with tubo-ovarian abscesses were identified. Data from the first 150 patients were used for the development of the postulated scoring system; data from the subsequent 64 patients were used for validation. Statistically significant clinical features between those having successful and unsuccessful management were: temperature (median = 37.1℃ vs 38.2℃, P = 0.0001), C-reactive protein (151 mg/L vs 243 mg/L, P = 0.0001), and tubo-ovarian abscess diameter (6.0 cm vs 8.0 cm, P = 0.0001). These parameters were used to create a risk prediction score. A score of four or more was predictive of requiring surgical/radiological intervention of tubo-ovarian abscess (P < 0.001). The score had a sensitivity of 69% and a specificity of 88%, with area under the curve (AUC) = 0.859.
Currently, there is no guidance for clinicians on when to operate on a tubo-ovarian abscess. Our prediction score is simple, using only three easily obtained clinical characteristics.
创建一个由临床和放射学特征组成的风险评分系统，以预测输卵管卵巢脓肿抗生素治疗失败的可能性。该评分应指导临床医生识别那些应接受早期干预而非延长抗生素试验治疗的患者。
一项多中心回顾性队列研究于2013年1月1日至2019年9月30日进行，纳入连续的输卵管卵巢脓肿患者。采用时间顺序划分，将患者分为两组，用于所假定评分系统的开发及后续验证。进行单变量和双变量分析，以确定静脉抗生素治疗失败的统计学显著变量。
共识别出214例连续的输卵管卵巢脓肿患者。前150例患者的数据用于开发所假定的评分系统；后64例患者的数据用于验证。治疗成功与失败患者之间具有统计学显著差异的临床特征为：体温（中位数=37.1℃对38.2℃，P = 0.0001）、C反应蛋白（151 mg/L对243 mg/L，P = 0.0001）和输卵管卵巢脓肿直径（6.0 cm对8.0 cm，P = 0.0001）。这些参数用于创建风险预测评分。评分4分及以上可预测需要对输卵管卵巢脓肿进行手术/放射学干预（P < 0.001）。该评分的敏感性为69%，特异性为88%，曲线下面积（AUC）= 0.859。
目前，对于临床医生何时对输卵管卵巢脓肿进行手术尚无指导。我们的预测评分很简单，仅使用三个易于获取的临床特征。
