Psoriasis in childhood and adolescence: evaluation of demographic and clinical features

BACKGROUND: The present study was aimed to define the gender ratio, familial occurrence, age of onset, precipitating factors, clinical types, nail and joint involvement of psoriasis in childhood and adolescence in Turkey. METHODS: A total of 61 children with psoriasis under 18 years old were evaluated retrospectively, for age, gender, age of disease onset, family history, concomitant disease, the clinical type of psoriasis, clinical localization, nail and joint involvement and treatment modalities. RESULTS: Of the patients, 23 (37.70%) were boys and 38 (62.30%) were girls. Mean age was 9.28 +/- 4.02 years in girls and 11.18 +/- 3.85 years in boys (9.96 +/- 4.03 years in all children). Mean age at the onset of the disease was 6.81 +/- 4.11 years in girls and 7.03 +/- 4.28 years in boys (6.89 +/- 4.14 years in all patients). In 14 (23%) cases, a positive family history was detected. The most frequent probable triggering factors were upper respiratory tract infections (14.8%) and positive throat culture for A group ss-hemolytic streptococcus (21.3%). Frequency of emotional stress and psychiatric morbidity were 54% and 9.8%, respectively. The most frequent localizations at onset were trunk (44.3%), extremities (54.0%), and scalp (36.0%). Three children (4.9%) had a history of dissemination from psoriatic diaper rash. In total, 51 (83.6%) patients presented with psoriasis vulgaris, eight (13.1%) with generalized pustular psoriasis, and the remaining two (3.3%) with erythrodermic psoriasis. CONCLUSION: The incidence of psoriasis among dermatological patients in childhood and adolescence was 3.8%. The disease tends to appear earlier in girls than boys. The authors suggested that stress and upper respiratory infections are the most important triggering factors in childhood and adolescence psoriasis.     

Does prophylactic sotalol and magnesium decrease the incidence of atrial fibrillation following coronary artery bypass surgery: a propensity-matched analysis

Background  

Atrial fibrillation can occur in up to 40% of patients undergoing coronary surgery.     

Dysgeusia related to urinary obstruction from benign prostatic disease: a case control and qualitative study

Anecdotal reports suggest that dysgeusia may be related to a variety of systemic factors, including bladder outflow obstruction. This is a hospital-based case-controlled study involving 111 patients who were admitted to urological wards for transurethral resection of the prostate for benign prostatic disease with age- and sex-matched control of 137 subjects. We used a semi-structured questionnaire by a trained interviewer at admission (preoperative), at the postoperative period and at follow-up between 4–6 months (median 5 months). Analysis used unpaired t-test and X₂ test. The incidence of dysgeusia was 22% in the study group and 13% in the control group (P=N.S.). However, strikingly, the dysgeusia in the study group was relieved promptly by relief of urinary obstruction in 100% of cases and did not return within the follow-up period. The mechanism of the dysgeusia associated with dysuria in benign prostatic disease is unknown, but we suggest that the dysgeusia could be from the stress of dysuria or due to a release of an unknown chemical from the urinary tract or an overflow of neural impulse from pontine/cortical micturition centres to the taste centres. An association between dysgeusia and dysuria has not been described before.     

Decision trees based on automatic learning and their use in cardiology

Computerized information systems, especially decision support systems, have become an increasingly important role in medical applications, particularly in those where important decision must be made effectively and reliably. But the possibility of using computers in medical decision making is limited by many difficulties, including the complexity of conventional computer languages, methodologies and tools. Thus a conceptual simple decision making model with the possibility of automating learning should be used. In this paper we introduce a cardiological knowledge-based system based on the decision tree approach supporting the mitral valve prolapse determination. Prolapse is defined as the displacement of a bodily part from its normal position. The term mitral valve prolaps (PMV), therefore, implies that the mitral leaflets are displaced relative to some structure, generally taken to be the mitral annulus. The implications of the PMV are the following: disturbed normal laminar blood flow, turbulence of the blood flow, injury of the chordae tendinae, the possibility of thrombus's composition, bacterial endocarditis, and finally hemodynamic changes defined as mitral insufficiency and mitral regurgitation. Uncertainty persists about how it should be diagnosed and about its clinical importance. It is our deep belief that the echocardiography enables properly trained experts armed with proper criteria to evaluate PMV almost 100%. But unfortunately, there are some problems concerned with the use of echocardiography. In that manner we have decided to start a research project aimed at finding new criteria and enabling the general practitioner to evaluate PMV using conventional methods and to select potential patients from the general population. To empower one to perform needed activities we have developed a computer tool called ROSE (computeRised prOlaps Syndrom dEtermination) based on algorithms of automatic learning. This tool supports the definition of new criteria and the selection of potential PMV-patients.