Comparison of enoxaparin and unfractionated heparin in endovascular interventions for the treatment of peripheral arterial occlusive disease: a randomized controlled trial

Summary. Background: Although unfractionated heparin (UFH) is an effective antithrombotic agent in endovascular interventions for the treatment of peripheral occlusive arterial disease (PAOD), it produces a highly variable anticoagulant response. Intravenous (i.v.) enoxaparin might be an effective and safe alternative. Patients and methods: In a prospective, open‐label, randomized, single‐center trial, 210 patients with PAOD (Fontaine stage IIb to IV) were randomly assigned in a 1 (UFH): 2 (enoxaparin) fashion to receive an i.v. bolus of 60 units UFH per kg body weight or 0.5 mg enoxaparin per kg body weight, respectively, before endovascular intervention. The primary composite endpoint assessed the clinical performance of enoxaparin by comparing the peri‐interventional rate of thromboembolia/occlusion (efficacy) of endovascularly reconstructed areas, of bleeding according to the Global Utilization of Streptokinase and t‐PA for Occluded Coronary Arteries (GUSTO) criteria (safety) and of any necessary re‐intervention for any percutaneous transluminal angioplasty (PTA)‐related bleeding. The secondary endpoint evaluated anti‐factor (F)Xa levels during intervention. Results: The primary composite endpoint showed a better performance of enoxaparin (10.5% vs. 2.5% absolute difference – 8.0%; P < 0.05). The concomitant use of acetylsalicylic acid (ASA) significantly (P < 0.05) increased the risk of a complication in the UFH group, but not in the enoxaparin group. Within 15 min, anti‐Xa levels were reached by 63.7% of patients treated with enoxaparin and only by 39.1% with UFH. Conclusion: Enoxaparin has a better performance than UFH in endovascular interventions for the treatment of PAOD. In patients with concomitant use of ASA, the risk of complications with UFH increases significantly compared with enoxaparin.     

Diabetes Patients' Experiences With the Implementation of Insulin Therapy and Their Perceptions of Computer-Assisted Self-Management Systems for Insulin Therapy

Background

Computer-assisted decision support is an emerging modality to assist patients with type 2 diabetes mellitus (T2DM) in insulin self-titration (ie, self-adjusting insulin dose according to daily blood glucose levels). Computer-assisted insulin self-titration systems mainly focus on helping patients overcome barriers related to the cognitive components of insulin titration. Yet other (eg, psychological or physical) barriers could still impede effective use of such systems.

Objective

Our primary aim was to identify experiences with and barriers to self-monitoring of blood glucose, insulin injection, and insulin titration among patients with T2DM. Our research team developed a computer-assisted insulin self-titration system, called PANDIT. The secondary aim of this study was to evaluate patients’ perceptions of computer-assisted insulin self-titration. We included patients who used PANDIT in a 4-week pilot study as well as patients who had never used such a system.

Methods

In-depth, semi-structured interviews were conducted individually with patients on insulin therapy who were randomly recruited from a university hospital and surrounding general practices in the Netherlands. The interviews were transcribed verbatim and analyzed qualitatively. To classify the textual remarks, we created a codebook during the analysis, in a bottom-up and iterative fashion. To support examination of the final coded data, we used three theories from the field of health psychology and the integrated model of user satisfaction and technology acceptance by Wixom and Todd.

Results

When starting insulin therapy, some patients feared a lifelong commitment to insulin therapy and disease progression. Also, many barriers arose when implementing insulin therapy (eg, some patients were embarrassed to inject insulin in public). Furthermore, patients had difficulties increasing the insulin dose because they fear hypoglycemia, they associate higher insulin doses with disease progression, and some were ignorant of treatment targets. Patients who never used a computer-assisted insulin self-titration system felt they had enough knowledge to know when their insulin should be adjusted, but still believed that the system advice would be useful to confirm their reasoning. Furthermore, the time and effort saved with automated insulin advice was considered an advantage. Patients who had used PANDIT found the system useful if their glycemic regulation improved. Nevertheless, for some patients, the absence of personal contact with their caregiver was a drawback. While guidelines state that adjustment of basal insulin dose based on fasting plasma glucose values is sufficient, both patients who had and those who had not used PANDIT felt that such a system should take more patient data into consideration, such as lifestyle and diet factors.

Conclusions

Patients encounter multiple obstacles when implementing insulin therapy. Computer-assisted insulin self-titration can increase patient awareness of treatment targets and increase their confidence in self-adjusting the insulin dose. Nevertheless, some barriers may still exist when using computer-assisted titration systems and these systems could also introduce new barriers.