Khan Sarosh, Demir Ozan, Mehmood Muhammad, Nabi Ibraheam, Kharoud Damandeep, Crawford Iveta, Smith Sheila, Fawaz Samer, Sajjad Uzma, Xue Qiang, Singh Arvind, Karamasis Grigoris V, Keeble Thomas, Davies John, Kabir Alamgir, Aggarwal Rajesh, Jagathesan Rohan, Cook Christopher
Essex Cardiothoracic Centre, Basildon, Essex, SS16 5NL, United Kingdom; Anglia Ruskin School of Medicine & MTRC, Anglia Ruskin University, Chelmsford, Essex CM1 1SQ, United Kingdom.
Essex Cardiothoracic Centre, Basildon, Essex, SS16 5NL, United Kingdom; Anglia Ruskin School of Medicine & MTRC, Anglia Ruskin University, Chelmsford, Essex CM1 1SQ, United Kingdom.
Int J Cardiol. 2025 Mar 1;422:132952. doi: 10.1016/j.ijcard.2024.132952. Epub 2025 Jan 4.
Transcatheter aortic valve replacement (TAVR) is increasingly in demand for treating severe aortic stenosis in a variety of surgical risk profiles. This means increasing wait times and elevated morbidity and mortality on the waitlist. To address this, we developed the SWIFT TAVR algorithm to prioritize patients based on clinical risk and reduce wait times.
The SWIFT algorithm, implemented in Microsoft Excel, calculates a clinical risk score from three parameters: left ventricular ejection fraction (LVEF), peak aortic valve gradient, and syncope. Scores categorize patients into four prioritisation profiles: high (9-10 points), intermediate (4-8 points), low (2-3 points), and minimal (0-1 point). The study prospectively applied the SWIFT algorithm to patients in 2022 (SWIFT group) and retrospectively to a 2021 cohort (CONTROL group). Outcomes measured were wait times from consultation to procedure and major adverse cardiac events (MACE) while awaiting TAVR.
A total of 228 patients were included (117 SWIFT, 111 CONTROL). There was no significant difference in baseline characteristics between groups (p > 0.05). Overall wait times were significantly shorter in the SWIFT group (21 vs 28 weeks, p < 0.001), particularly for high-risk patients (12 vs 31 weeks, p < 0.001). MACE rates were similar (9 % vs 10 %, p = 0.722).
The SWIFT algorithm significantly reduced wait times, particularly for high-risk patients, without increasing MACE rates. This automated, risk-based prioritisation tool improves equity and efficiency in TAVR waitlist management and is globally applicable. Further randomized studies are warranted to validate these findings.
经导管主动脉瓣置换术（TAVR）在治疗各种手术风险状况的严重主动脉瓣狭窄方面的需求日益增加。这意味着等待时间延长，以及等待名单上的发病率和死亡率上升。为了解决这个问题，我们开发了SWIFT TAVR算法，根据临床风险对患者进行优先排序，以减少等待时间。
在Microsoft Excel中实施的SWIFT算法根据三个参数计算临床风险评分：左心室射血分数（LVEF）、主动脉瓣峰值梯度和晕厥。分数将患者分为四个优先排序类别：高（9 - 10分）、中（4 - 8分）、低（2 - 3分）和极低（0 - 1分）。该研究前瞻性地将SWIFT算法应用于2022年的患者（SWIFT组），并回顾性地应用于2021年的队列（对照组）。测量的结果是从咨询到手术的等待时间以及等待TAVR期间的主要不良心脏事件（MACE）。
共纳入228例患者（117例SWIFT组，111例对照组）。两组之间的基线特征无显著差异（p > 0.05）。SWIFT组的总体等待时间显著更短（21周对28周，p < 0.001），特别是高危患者（12周对31周，p < 0.001）。MACE发生率相似（9%对10%，p = 0.722）。
SWIFT算法显著减少了等待时间，特别是对于高危患者，且未增加MACE发生率。这种基于风险的自动优先排序工具提高了TAVR等待名单管理的公平性和效率，并且在全球范围内都适用。有必要进行进一步的随机研究来验证这些发现。
