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Background: Surgical Site Infection is an index of health care system of any hospital. Surgical material is a risk factor for SSI that can be easily changed. One of such measures is the use of antimicrobial suture technology which involves the impregnation of synthetic, absorbable, polymeric sutures with the antiseptic, Triclosan. Triclosan-coated sutures inhibit bacterial colonization of wide-spectrum of pathogens. This study was designed to assess the efficacy of triclosan coated sutures in reducing incidence of surgical site infection in Indian population.Methods: This is a retrospective ‘real-world’ study of 150 patients who underwent surgery and wound closure with triclosan-coated suture from May 2015 to December 2015 at Hospital, Mohali. Incidence of SSI was recorded, and nature of wound was categorized. Data was subject to descriptive analysis.Results: 99.3% of wounds sutured with triclosan coated sutures did not have surgical site infection. The single case of SSI encountered was categorized as superficial-incisional. All the evaluated cases were categorized as ‘clean’ at the time of discharge.Conclusions: Triclosan-coated sutures were responsible for the reported reduction in SSI, particularly in adult patients with clean wounds. This study justifies that in addition to the mandated core measures of surgical care, adjunctive evidence-based interventions such as Triclosan-coated sutures should be considered in the comprehensive effort to decrease risk of surgical site infection and improve outcome at both patient and institutional levels.

The vehicular ad-hoc networks are the networks made of vehicles in the movement. The vehicular movement management is the important task for the automatically driven vehicles, where the traffic management module must be capable of handling the traffic movement and track the traffic hurdles. In this paper, the primary focus has been kept on the traffic hurdles detection in the movement of the traffic in the VANET cluster. The proposed model is based upon the distance calculation and non-moving hurdle prediction. Afterwards the proposed model floods the information in the VANET cluster about the detected vehicular hurdle. The proposed model has been evaluated on the basis of transmission delay, network load and data loss. The experimental results have proved the efficiency of the proposed model in handling the network during the hurdle detection and updation situations.