A Systematic Review of Wearable Infection Detection Wristbands for Postoperative Patients: Evaluating the Efficacy of WBC and CRP Monitoring and AI-Assisted Early Detection
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 1,284
- 试验地点
- 1
- 主要终点
- Diagnostic Accuracy of Wearable Devices for Detection of Postoperative Infection
研究概览
简要总结
This systematic review aims to evaluate the efficacy, accuracy, and clinical applicability of wearable infection detection wristbands in postoperative patients across ophthalmology, orthopaedic surgery, and general surgery. The review focuses on devices capable of monitoring inflammatory biomarkers-particularly white blood cell (WBC) counts and C-reactive protein (CRP)-and examines the added value of artificial intelligence (AI) algorithms for early infection detection.
The study synthesizes available evidence on clinical outcomes, predictive accuracy, usability, and feasibility of biosensor-based infection surveillance in postoperative care. It is expected to provide an evidence-based framework for integrating wearable biosensors into perioperative management protocols and to guide future multicenter clinical validation studies.
详细描述
Postoperative infection remains one of the most common and serious complications following surgical procedures. Early detection of infection is critical for optimizing outcomes and reducing morbidity. Conventional laboratory monitoring using intermittent WBC and CRP testing is invasive and time-dependent, often delaying timely clinical intervention.
Recent advances in wearable biosensor technology have enabled continuous, non-invasive monitoring of physiological and biochemical parameters. Several wearable platforms are now capable of detecting early inflammatory changes through electrochemical or optical sensing, with CRP being the most validated biomarker. Integration of AI algorithms further enhances predictive performance by analyzing complex data patterns and providing early alerts to clinicians.
This systematic review adheres to PRISMA 2020 guidelines and aims to consolidate available clinical and experimental evidence on wearable biosensors capable of postoperative infection detection, emphasizing WBC and CRP monitoring wristbands and AI-assisted analysis. By synthesizing data from ophthalmology, orthopaedics, and general surgery, the review will assess diagnostic accuracy, clinical outcomes, and feasibility of these technologies in diverse healthcare contexts.
The findings are expected to inform future research directions, highlight existing technological gaps, and propose recommendations for clinical implementation and regulatory validation.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Adults aged 18 years or older.
- •Patients undergoing ophthalmologic, orthopedic, or general surgical procedures.
- •Postoperative patients monitored using a wearable infection detection device or biosensor capable of continuous or intermittent assessment of inflammatory biomarkers, including:
- •White blood cell (WBC) count and/or
- •C-reactive protein (CRP) levels.
- •Wearable devices may incorporate artificial intelligence or machine-learning algorithms for infection prediction.
- •Patients receiving standard postoperative care, including conventional laboratory testing and/or clinical monitoring, for comparison.
- •Ability to provide written informed consent.
排除标准
- •Patients aged <18 years.
- •Non-human studies (animal or in-vitro).
- •Use of wearable devices that monitor only physiological parameters (e.g., temperature, heart rate, oxygen saturation) without inflammatory biomarker assessment (WBC or CRP).
- •Patients who are hemodynamically unstable at the time of enrollment.
- •Inability or unwillingness to provide informed consent.
- •Duplicate enrollment or participation in another interventional study that may interfere with outcomes.
研究组 & 干预措施
Group Monitoring
Wearable infection detection wristbands / biosensors
干预措施: White Blood Cell (WBC) (Diagnostic Test)
Group Monitoring
Wearable infection detection wristbands / biosensors
干预措施: C-reactive Protein (CRP) (Diagnostic Test)
结局指标
主要结局
Diagnostic Accuracy of Wearable Devices for Detection of Postoperative Infection
时间窗: 1 week
Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of wearable devices for detecting postoperative infection, using standard clinical diagnosis as the reference standard.
Predictive Accuracy of AI-Integrated Wearable Monitoring for Early Postoperative Infection
时间窗: 1 week
Improvement in early postoperative infection prediction accuracy achieved by AI-integrated wearable monitoring compared with traditional laboratory-based monitoring methods.
Time to Postoperative Infection Detection Using Wearable Devices Compared With Standard Care
时间窗: 1 week
Time interval between clinical onset of postoperative infection and detection by wearable devices compared with detection by standard postoperative care protocols.
次要结局
- Time to Wound Healing(1 week)
- Secondary outcomes(1 week)
- Feasibility and Usability of Wearable Devices in Postoperative Monitoring(1 week)
- Methodological Quality and Risk of Bias of Wearable Device Validation(1 week)
研究者
Ehab Mohamed Elsayed Mohamed Saad
Lecturer
Benha University