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确定易受影响的术后人群:PAIN-OUT 登记处的两步聚类分析。

Finding the vulnerable postoperative population: A two-step cluster analysis of the PAIN-OUT registry.

机构信息

Department of Anesthesiology, Consorci Sanitari Integral, Hospital Sant Joan Despí Moisès Broggi and Hospital General de l'Hospitalet, Barcelona, Spain.

Ciber Fisiopatología Obesidad y Nutrición (CIBERobn), Instituto Salud Carlos III, Madrid, Spain.

出版信息

Eur J Pain. 2022 Sep;26(8):1732-1745. doi: 10.1002/ejp.1997. Epub 2022 Jul 7.

Abstract

BACKGROUND

Identifying predictors of poor postoperative outcomes is crucial for planning personalized pain treatments. The aim of this study was to examine pain outcomes using cluster analysis in N = 2678 patients from the PAIN-OUT registry at first postoperative day.

METHODS

Indicator variables of the clustering analysis assessed multiple domains, such as clinical and surgical conditions, analgesic-anaesthetic variables, desire for more pain treatment and outcome variables of the International Pain Outcome Questionnaire (IPO) summarized as factor scores.

RESULTS

Two-step cluster identified the three-cluster solution as the optimal. Two empirical groups (C1 and C2) included patients with good postoperative outcomes discriminated by peripheral nerve block use, while the other cluster (C3) grouped patients with the worst outcomes, where all patients desired more pain treatment. C3 comprised about 20% of the participants, mostly lower limb, abdominal and spine procedures. The best predictors of belonging to C3 included younger age, being male, preoperative opioid use, bone and fracture reduction procedures, institution, number of comorbidities and morphine equivalents in the recovery room.

CONCLUSIONS

IPO factor scores can be used to select pain outcomes phenotypes in large clinical databases. Most of the predictors were present before the recovery period so perioperative planning should focus in the preoperative and intraoperative periods.

SIGNIFICANCE

Improvement of postoperative pain requires assessment methods that go beyond pain intensity scores. We perform a cluster analysis among PAIN-OUT patients that revealed a cluster of vulnerable postoperative patients, using a novel composite measure of postoperative outcomes: the factor scores of the International Pain Outcomes Questionnaire. By changing the focus from pain intensity to multidimensional pain outcomes, male gender and number of comorbidities appeared as new risk factors for worse postoperative outcomes. The study also identified procedures that require urgent quality improvements.

摘要

背景

识别术后不良结局的预测因素对于制定个性化疼痛治疗方案至关重要。本研究旨在使用 PAIN-OUT 登记处首次术后日的 2678 例患者的聚类分析来评估疼痛结局。

方法

聚类分析的指标变量评估了多个领域,如临床和手术条件、镇痛-麻醉变量、对更多疼痛治疗的需求以及国际疼痛结局问卷(IPO)的结局变量,这些变量被总结为因子分数。

结果

两步聚类确定了三聚类解决方案是最佳的。两个经验性组(C1 和 C2)包括使用外周神经阻滞的术后结局良好的患者,而另一个组(C3)则包括术后结局最差的患者,所有患者都希望接受更多的疼痛治疗。C3 组约占参与者的 20%,主要是下肢、腹部和脊柱手术。属于 C3 的最佳预测因素包括年龄较小、男性、术前使用阿片类药物、骨和骨折复位手术、机构、合并症数量和恢复室中的吗啡等效物。

结论

IPO 因子分数可用于在大型临床数据库中选择疼痛结局表型。大多数预测因素在恢复期间之前就存在,因此围手术期计划应侧重于术前和术中期间。

意义

改善术后疼痛需要超越疼痛强度评分的评估方法。我们对 PAIN-OUT 患者进行聚类分析,揭示了一组易受术后影响的患者,使用术后结局的新综合衡量标准:国际疼痛结局问卷的因子分数。通过将重点从疼痛强度转移到多维疼痛结局,男性性别和合并症数量成为术后不良结局的新危险因素。该研究还确定了需要紧急质量改进的手术。

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