Adjuvant Vitamin D Injection in Elderly Patients Before Intertrochanteric Fracture Surgery: A Randomised Controlled Trial

Background

There are multiple recommended protocols for Vitamin D (VitD) supplementation in elderly; however, only a few studies achieved to examine the role of VitD supplements before intertrochanteric fracture surgery on mortality and complications after surgery.

Methods

This single-center block-randomized double-blinded trial was conducted on 80 patients with intertrochanteric fractures and a sufficient level of 25 (OH) VitD. The intervention group received an intramuscular 300,000 IU VitD ampule before surgery. The primary outcome was a 6-month mortality rate, and the secondary outcomes were 1- and 2-year mortality rates and Harris Hip Score (HHS) in 6, 12, and 24 months after surgery. Chi-square, t-test, repeated measure ANOVA, and Cox regression survival model was used for statistical analysis.

Results

40 patients were allocated to each group. Demographic, clinical characteristics, and preoperative evaluations were not significantly different between the groups. Mortality rate 6-month after the surgery was 7.5% and 10% for the intervention and placebo groups respectively (P value = .71), 15% and 12.5% at 1-year (P value = .83), and 25% and 27.5% at 2-year (P value = .98). Based on the Cox regression model, only age was significantly associated with mortality (HR = 1.229, P value <.001). Significant HHS changes from baseline through 24 months after surgery were observed within both groups; however, mean differences were not significantly different between groups.

Conclusions

A single preoperative 300,000 IU VitD did not significantly impact 2-year survival and HHS in patients with intertrochanteric fractures and sufficient serum VitD level.

Clostridium difficile infection in cancer patients with hospital acquired diarrhea at the teaching hospitals in Iran: Multilocus sequence typing analysis (MLST) and Antimicrobial resistance pattern

BACKGROUND

This study aimed to investigate the phenotype and genotype characterization of Clostridium difficile isolates among cancer patients with hospital-acquired diarrhea in 4 teaching hospitals in Isfahan, Iran.

STUDY DESIGN

This was a cross sectional study conducted on adult (>18 years old) between April 2015 and May 2017.

METHODS

Over two years, 67 diarrheic fecal samples were collected. C. difficile isolates were characterized according to the presence of toxin genes and antibiotic resistance. Multilocus sequence typing (MLST) was performed to evaluate the genetic relationships between different lineages of toxigenic strains.

RESULTS

Seven toxigenic and 12 non- toxigenic strains were detected among stool samples. Patients with a history of previous surgery during hospitalization were more than 7 times likely to develop Clostridium difficile infection (CDI). All isolates were susceptible to metronidazole, vancomycin and fusidic acid. Toxigenic C. difficile strains were divided into 3 different sequence types. The detected types were ST-54, ST-2 and ST-37, while none of the isolates was identified as ST-1 or ST-11.

CONCLUSIONS

This is the first description of the MLST analysis of C. difficile strains isolated from cancer patients in Iran. All of the studied population were exposed to multiple antibiotics and chemotherapeutic agents. Further research and clinical studies are recommended in the treatment through good antimicrobial stewardship and prevention of C. difficile infection in all healthcare settings.

Novel synchronization of discrete-time chaotic systems using neural network observer

This paper presents a new approach to solve the synchronization problem of a large class of discrete chaotic systems. The chaotic systems can be reformulated as an appropriate class of linear parameter varying (LPV) systems. The synchronization problem for this class of nonlinear systems is revisited from a control perspective and it is argued that the problem can be viewed as an observer design problem. Then, based on the LPV representation, a neural network observer-based approach is proposed to solve the synchronization problem. The simulation results show the advantages of combining the LPV techniques and the neural networks to determine the appropriate observer gain within the context of chaotic system synchronization.