Eculizumab Use in Scleroderma Renal Crisis With Thrombotic Microangiopathy: A Case Report

A Black woman in her 40s with past medical history significant for obesity treated with Roux-en-Y bypass surgery and a history of Raynaud’s phenomenon, presented with acute pulmonary edema secondary to severe malignant hypertension and critically accelerated acute kidney injury, with evidence of systemic microangiopathic hemolytic anemia in the setting of clinical suspicion of systemic sclerosis sine scleroderma. Renin-angiotensin system blockade (angiotensin-converting enzyme inhibitor) was immediately started at the maximum possible dose in the setting of scleroderma renal crisis. Despite better control of blood pressure and volume status, kidney function continued to rapidly decline, thus a decision was made to go ahead with a kidney biopsy on day 3 of admission, which revealed severe features of scleroderma renal crisis with active thrombotic microangiopathy. The multidisciplinary team elected to treat the patient with terminal complement blockade using eculizumab in addition to high dose lisinopril and blood pressure control. Her serum creatinine peaked at 9.3 mg/dL shortly after eculizumab initiation, but improved soon after, dropping to 2.8 mg/dL after completion of the final eculizumab dose and 1.8 mg/dL 3 years later

Detection of Drug–Drug Interactions Inducing Acute Kidney Injury by Electronic Health Records Mining

International audienceBackground and Objective : While risk of acute kidney injury (AKI) is a well documented adverse effect of some drugs, few studies have assessed the relationship between drug–drug interactions (DDIs) and AKI. Our objective was to develop an algorithm capable of detecting potential signals on this relationship by retrospectively mining data from electronic health records.Material and methods : Data were extracted from the clinical data warehouse (CDW) of the Hôpital Européen Georges Pompidou (HEGP). AKI was defined as the first level of the RIFLE criteria, that is, an increase ≥50 % of creatinine basis. Algorithm accuracy was tested on 20 single drugs, 10 nephrotoxic and 10 non-nephrotoxic. We then tested 45 pairs of non-nephrotoxic drugs, among the most prescribed at our hospital and representing distinct pharmacological classes for DDIs.Results : Sensitivity and specificity were 50 % [95 % confidence interval (CI) 23.66–76.34] and 90 % (95 % CI 59.58–98.21), respectively, for single drugs. Our algorithm confirmed a previously identified signal concerning clarithromycin and calcium-channel blockers (unadjusted odds ratio (ORu) 2.92; 95 % CI 1.11–7.69, p = 0.04). Among the 45 drug pairs investigated, we identified a signal concerning 55 patients in association with bromazepam and hydroxyzine (ORu 1.66; 95 % CI 1.23–2.23). This signal was not confirmed after a chart review. Even so, AKI and co-prescription were confirmed for 96 % (95 % CI 88–99) and 88 % (95 % CI 76–94) of these patients, respectively.Conclusion : Data mining techniques on CDW can foster the detection of adverse drug reactions when drugs are used alone or in combination