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Background: Fournier's gangrene (FG) is an extensive fulminant infection of the genitals, perineum or the abdominal wall. The aim of this study is to share our experience with the management of this difficult infectious disease. Methods: Thirty-three male patients were admitted to our clinic with the diagnosis of FG between February 1988 and December 2003. The patient's age, etiology and predisposing factors, microbiological findings, duration of hospital stay, treatment, and outcome were analyzed. The patients were divided into two groups. The first 21 patients (Group I) were treated with broadspectrum triple antimicrobial therapy, broad debridement, exhaustive cleaning, and then they underwent split-thickness skin grafts or delayed closure as needed. The other 12 patients (Group II) were treated with unprocessed honey (20-50 mL daily) and broadspectrum triple antimicrobial therapy without debridement. Their wounds were cleaned with saline and then dressed with topical unprocessed honey. The wounds were inspected daily and the honey was reapplied after cleaning with normal saline. Then, the patients' scrotum and penis were covered with their own new scrotal skin. Results: The mean age of the patients was 53.9 ± 9.56 years (range = 23-71). The source of the gangrene was urinary in 23 patients, cutaneous in seven patients, and perirectal in three patients. The predisposing factors included diabetes mellitus for 11 patients, alcoholism for 10 patients, malnutrition for nine patients, and medical immunosuppression (chemotherapy, steroids, malignancy) for three patients. The mean duration of hospital stay was 41 ± 10.459 (range = 14-54) days. Two patients in Group I died from severe sepsis. The clinical and cosmetic results were better in Group II than Group I. Conclusions: Necrotizing fasciitis of the perineum and genitalia is a severe condition with a high morbidity and mortality. Traditionally, good management is based on aggressive debridement, broad-spectrum antibiotics, and intensive supportive care but unprocessed honey might revolutionize the treatment of this dreadful disease by reducing its cost, morbidity, and mortality.

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Per-operative 50 mg/kg magnesium sulphate infusion is effective in reducing post-operative pain in patients undergoing LC.

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ObjectiveWe aim to deliver a framework with 2 main objectives: 1) facilitating the design of theory-driven, adaptive, digital interventions addressing chronic illnesses or health problems and 2) producing personalized intervention delivery strategies to support self-management by optimizing various intervention components tailored to people’s individual needs, momentary contexts, and psychosocial variables.Materials and MethodsWe propose a template-based digital intervention design mechanism enabling the configuration of evidence-based, just-in-time, adaptive intervention components. The design mechanism incorporates a rule definition language enabling experts to specify triggering conditions for interventions based on momentary and historical contextual/personal data. The framework continuously monitors and processes personal data space and evaluates intervention-triggering conditions. We benefit from reinforcement learning methods to develop personalized intervention delivery strategies with respect to timing, frequency, and type (content) of interventions. To validate the personalization algorithm, we lay out a simulation testbed with 2 personas, differing in their various simulated real-life conditions.ResultsWe evaluate the design mechanism by presenting example intervention definitions based on behavior change taxonomies and clinical guidelines. Furthermore, we provide intervention definitions for a real-world care program targeting diabetes patients. Finally, we validate the personalized delivery mechanism through a set of hypotheses, asserting certain ways of adaptation in the delivery strategy, according to the differences in simulation related to personal preferences, traits, and lifestyle patterns.ConclusionWhile the design mechanism is sufficiently expandable to meet the theoretical and clinical intervention design requirements, the personalization algorithm is capable of adapting intervention delivery strategies for simulated real-life conditions.