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患者自控镇痛服务中剂量输送信息的时变分析。

Time-dependent analysis of dosage delivery information for patient-controlled analgesia services.

机构信息

Department of Biomedical Engineering, National Yang-Ming University, Taipei, Taiwan.

Department of Anesthesiology, Taipei Veterans General Hospital, Taipei, Taiwan.

出版信息

PLoS One. 2018 Mar 15;13(3):e0194140. doi: 10.1371/journal.pone.0194140. eCollection 2018.

Abstract

Pain relief always plays the essential part of perioperative care and an important role of medical quality improvement. Patient-controlled analgesia (PCA) is a method that allows a patient to self-administer small boluses of analgesic to relieve the subjective pain. PCA logs from the infusion pump consisted of a lot of text messages which record all events during the therapies. The dosage information can be extracted from PCA logs to provide easily understanding features. The analysis of dosage information with time has great help to figure out the variance of a patient's pain relief condition. To explore the trend of pain relief requirement, we developed a PCA dosage information generator (PCA DIG) to extract meaningful messages from PCA logs during the first 48 hours of therapies. PCA dosage information including consumption, delivery, infusion rate, and the ratio between demand and delivery is presented with corresponding values in 4 successive time frames. Time-dependent statistical analysis demonstrated the trends of analgesia requirements decreased gradually along with time. These findings are compatible with clinical observations and further provide valuable information about the strategy to customize postoperative pain management.

摘要

疼痛缓解在围手术期护理中一直起着至关重要的作用,也是医疗质量改进的重要组成部分。患者自控镇痛 (PCA) 是一种允许患者自行给予小剂量镇痛药以缓解主观疼痛的方法。输液泵的 PCA 日志包含大量记录治疗期间所有事件的文本消息。可以从 PCA 日志中提取剂量信息,以提供易于理解的特征。随着时间的推移分析剂量信息对了解患者疼痛缓解情况的变化有很大帮助。为了探索疼痛缓解需求的趋势,我们开发了 PCA 剂量信息生成器 (PCA DIG),以在治疗的前 48 小时内从 PCA 日志中提取有意义的消息。PCA 剂量信息包括消耗、输送、输注率以及需求与输送之间的比例,在 4 个连续的时间框架中呈现相应的值。时间依赖性统计分析表明,随着时间的推移,镇痛需求逐渐下降。这些发现与临床观察一致,并进一步提供了有关定制术后疼痛管理策略的有价值信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0a/5854274/bdc799369a29/pone.0194140.g001.jpg

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