A retrospective analysis of the investigative practices of acute limb ischaemia presenting with an unknown aetiology. Issue 3 (18th October 2021) - Nath, Karthik; Reyaldeen, Reza; Mack, Kathyrn; Sistla, Laxmi; Palamuthusingam, Dharmenaan; Zahir, Syeda Farah; Dave, Richa; Muller, Juanita; McCann, Andrew
Abstract: Background: Acute limb ischaemia (ALI) is a limb and life‐threatening condition with significant morbidity. There are currently no consensus recommendations for the investigative practices to determine the aetiology of ALI presenting without a known aetiology. We undertook a detailed analysis of all investigations performed to identify an underlying precipitant in those with unexplained ALI and formulated a suggested diagnostic algorithm for the evaluation of unexplained ALI. Methods: ALI cases presenting to a tertiary referral centre over a 3‐year period were reviewed, and known aetiologies, and investigations undertaken to determine the underlying aetiology of unexplained ALI were obtained. Results: Unexplained ALI was found in 27 of 222 patients (12%), of which 21 (78%) had a cause for ALI established after further investigations. Six patients had no cause identified despite extensive work‐up. Most patients with unexplained ALI had a cardioembolic source identified as the underlying cause (62%), and this included atrial fibrillation, infective endocarditis, cardiac myxoma and intra‐cardiac thrombus. Other causes of unexplained ALI were detected by computed tomography (CT) imaging and included newly diagnosed significant atherosclerotic disease (19%), embolism from isolated proximal large vessel thrombus (10%) and metastatic malignancy (10%). There were no cases attributed to inherited thrombophilias, myeloproliferative neoplasms or anti‐phospholipid syndrome. Conclusion: Among patients with unexplained ALI, the majority had a cardioembolic source highlighting the importance of comprehensive cardiac investigations. A subset of patients had alternative causes identified on CT imaging. These data support the use of a collaborative and integrative diagnostic algorithm in the evaluation of unexplained ALI.