Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK.
QJM. 2013 Oct;106(10):883-5. doi: 10.1093/qjmed/hct068. Epub 2013 Apr 5.
Chronic obstructive pulmonary disease (COPD) is a common cause of disability and a leading cause of admissions to hospital because of exacerbations of the condition. Early intervention with antibiotics and steroids can prevent admissions, but it can be difficult for patients to recognize the early signs of exacerbation and to access timely clinical care. One solution to these barriers to early management is the use of telemonitoring of symptoms and physiological signs. Patients regularly record these and they are made available to clinicians, by the Internet, who based on scoring algorithms are alerted and may then be able to detect early signs of deterioration and intervene. However, the evidence to date for the effectiveness and cost-effectiveness of this approach has not been strong. While early research shows promise, most interventions have been complex and involved additional clinical support rendering interpretation of the impact of telemonitoring alone difficult. The results of larger well-designed trials are awaited. Key to the success of future telemonitoring interventions will be establishment of the utility of different physiological measures and the construction of accurate predictive algorithms which can take into account individuals' risk factors, patterns of symptom and physiological parameters and recent therapy changes.
慢性阻塞性肺疾病（COPD）是一种常见的致残原因，也是因病情恶化而住院的主要原因。早期使用抗生素和类固醇进行干预可以预防住院，但患者可能难以识别病情恶化的早期迹象，也难以获得及时的临床护理。解决这些早期管理障碍的一种方法是使用症状和生理指标的远程监测。患者定期记录这些指标，并通过互联网提供给临床医生，医生可以根据评分算法获得警报，从而可能检测到病情恶化的早期迹象并进行干预。然而，迄今为止，这种方法的有效性和成本效益的证据并不充分。虽然早期的研究显示出了希望，但大多数干预措施都很复杂，并且需要额外的临床支持，这使得单独解释远程监测的影响变得困难。更大规模精心设计的试验的结果正在等待中。未来远程监测干预成功的关键将是确定不同生理指标的实用性，并构建准确的预测算法，这些算法可以考虑到个体的风险因素、症状和生理参数的模式以及最近的治疗变化。
