Registry of First-line Treatments in Patients With Critical Limb Ischemia

Critical Limb Ischemia

critical limb ischemia, endovascular treatment, open surgical repair, diabetic foot

The principal research question is which treatment modality between open surgical, endovascular and conservative therapy is the most effective in terms of limb salvage, survival and reinterventions in patients with critical limb ischemia

The target population consists of patients suffering from critical limb ischemia (CLI) lasting more than 2 weeks. CLI is defined as rest pain or tissue loss (Fontaine stages III-IV or Rutherford classes 4 to 6) and/or ankle-brachial index \< 0.40. Patient with acute limb-threatening ischemia, bone fractures in the relevant areas, nonatherosclerotic disease (e.g. arteriitis) and documented hypercoagulable diseases will be excluded from this study. There will be no experimental or control groups. The comparison groups will be: Group 1: Best endovascular treatment (angioplasty +/- stent) Group 2: Best surgical treatment \[bypass (vein or prosthetic)\] Group 3: Femoral artery patchplasty +/- profundoplasty (+/- endovascular treatment) Group 4: Best conservative treatment The proposed sample size amounts to 1200 patients. To be assessed for eligibility (n=1200) To be allocated to trial (n=1000) To be analysed (n=900) In CRITISCH registry, randomization or blinding is not feasible, because optimized standard care will be performed as established at each participating centre (best medical treatment). Data storage, validation, monitoring, update, backup and analysis will be performed centrally following established procedures. Web-based software will be used to develop a data model representing the data structure. The data validation will include standard data validation techniques such as the manual review of selected variables and the routine check of missing and outlying data points. Regional staff will be instructed and supervised by study nurse, who will perform the study monitoring. Assessment of relevant prognostic factors during the statistical analysis will prevent biased results due to the non-randomized design and the potential structural inequality.

Germany