Clinical evaluation of a newly developed automated hemodialysis system as a clinical trial

Abstract Background To cope with the increasing number of patients on long-term hemodialysis (HD), especially those with diabetic nephropathy, we designed a fully automated HD system to decrease staff workload and hence human errors related to HD treatment. In this study, we evaluated this new system as a clinical trial. Methods Based on a dialysis machine combined with a central dialysate delivery system (CDDS), the new system is characterized by the use of back ultrafiltrated dialysate (BUD) as a substitute fluid for priming, bonus shot and blood return, and the attachment of double endotoxin retentive filters (ETRFs). Results The subjects comprised 61 patients from five HD facilities enrolled in a randomized, open-labeled crossover study after giving written informed consent. A total of 348 HD treatments for 58 of the 61 patients were studied under a protocol designed in accordance with good clinical practice (GCP) guidelines and approved by the respective institutional review boards. No severe adverse effects were observed with either the test or control systems. The incidence of clinical events, including blood pressure decline, residual blood, and error in fluid removal, was not statistically significant in either group. Neither endotoxins nor bacteria were detected in the dialysate passing through the double filters. Conclusions This study confirmed the safety and effectiveness of an automated HD system based on CDDS. (This Clinical Trial No. is 21500BZZ00045000

Identification of Marker Genes for Differential Diagnosis of Chronic Fatigue Syndrome

Chronic fatigue syndrome (CFS) is a clinically defined condition characterized by long-lasting disabling fatigue. Because of the unknown mechanism underlying this syndrome, there still is no specific biomarker for objective assessment of the pathological fatigue. We have compared gene expression profiles in peripheral blood between 11 drug-free patients with CFS and age- and sex-matched healthy subjects using a custom microarray carrying complementary DNA probes for 1,467 stress-responsive genes. We identified 12 genes whose mRNA levels were changed significantly in CFS patients. Of these 12 genes, quantitative real-time PCR validated the changes in 9 genes encoding granzyme in activated T or natural killer cells (GZMA), energy regulators (ATP5J2, COX5B, and DBI), proteasome subunits (PSMA3 and PSMA4), putative protein kinase c inhibitor (HINT ), GTPase (ARHC), and signal transducers and activators of transcription 5A (STAT5A). Next, we performed the same microarray analysis on 3 additional CFS patients and 20 other patients with the chief complaint of long-lasting fatigue related to other disorders (non-CFS patients) and found that the relative mRNA expression of 9 genes classified 79% (11/14) of CFS and 85% (17/20) of the non-CFS patients. Finally, real-time PCR measurements of the levels of the 9 involved mRNAs were done in another group of 18 CFS and 12 non-CFS patients. The expression pattern correctly classified 94% (17/18) of CFS and 92% (11/12) of non-CFS patients. Our results suggest that the defined gene cluster (9 genes) may be useful for detecting pathological responses in CFS patients and for differential diagnosis of this syndrome