Correlates of patient satisfaction at varying points in time were assessed using a survey with 2-week and 3-month follow-up in a general medicine walk-in clinic, in USA. Five hundred adults presenting with a physical symptom, seen by one of 38 participating clinicians were surveyed and the following measurements were taken into account: patient symptom characteristics, symptom-related expectations, functional status (Medical Outcomes Study Short-Form Health Survey [SF-6]), mental disorders (PRIME-MD), symptom resolution, unmet expectations, satisfaction (RAND 9-item survey), visit costs and health utilization. Physician perception of difficulty (Difficult Doctor Patient Relationship Questionnaire), and Physician Belief Scale. Immediately after the visit, 260 (52%) patients were fully satisfied with their care, increasing to 59% at 2 weeks and 63% by 3 months. Patients older than 65 and those with better functional status were more likely to be satisfied. At all time points, the presence of unmet expectations markedly decreased satisfaction: immediately post-visit (OR: 0.14, 95% CI: 0.07-0.30), 2-week (OR: 0.07, 95% CI: 0.04-0.13) and 3-month (OR: 0.05, 95% CI: 0.03-0.09). Other independent variables predicting immediate after visit satisfaction included receiving an explanation of the likely cause as well as expected duration of the presenting symptom. At 2 weeks and 3 months, experiencing symptomatic improvement increased satisfaction while additional visits (actual or anticipated) for the same symptom decreased satisfaction. A lack of unmet expectations was a powerful predictor of satisfaction at all time-points. Immediately post-visit, other predictors of satisfaction reflected aspects of patient doctor communication (receiving an explanation of the symptom cause, likely duration, lack of unmet expectations), while 2-week and 3-month satisfaction reflected aspects of symptom outcome (symptom resolution, need for repeat visits, functional status). Patient satisfaction surveys need to carefully consider the sampling time frame as well as adjust for pertinent patient characteristics.

No abstract

Bartonella bacilliformis has caused debilitating illness since pre-Incan times, but relatively little is known about its epidemiology. A population-based, prospective cohort investigation was conducted in a Peruvian community with endemic bartonellosis. By use of house-to-house and hospital surveillance methods, cohort participants were monitored for evidence of bartonellosis. Of 690 participants, 0.5% had asymptomatic bacteremia at study initiation. After 2 years of follow-up, the incidence of infection was 12.7/100 person-years. The highest rates were in children <5 years old, and there was a linear decrease in incidence with increasing age. Seventy percent of cases were clustered in 18% of households. Age and bartonellosis in a family member were the best predictors of B. bacilliformis infection. There were multiple clinical presentations and significant subclinical infection. A cost-effective control strategy should include vector control and surveillance efforts focused on children and clusters of households with highest endemicity.

Bartonella bacilliformis causes bartonellosis, a potentially life-threatening emerging infectious disease seen in the Andes Mountains of South America. There are no generally accepted serologic tests to confirm the disease. We developed an indirect fluorescence antibody (IFA) test for the detection of antibodies toB. bacilliformis and then tested its performance as an aid in the diagnosis of acute bartonellosis. The IFA is 82% sensitive in detecting B. bacilliformis antibodies in acute-phase blood samples of laboratory-confirmed bartonellosis patients. When used to examine convalescent-phase sera, the IFA is positive in 93% of bartonellosis cases. The positive predictive value of the test is 89% in an area of Peru where B. bacilliformis is endemic and where the point prevalence of infection is 45%.

Abstract. Over 35,000 cases of Japanese encephalitis (JE) are reported worldwide each year. Culex tritaeniorhynchus is the primary vector of the JE virus, while wading birds are natural reservoirs and swine amplifying hosts. As part of a JE risk analysis, the ecological niche modeling programme, Maxent, was used to develop a predictive model for the distribution of Cx. tritaeniorhynchus in the Republic of Korea, using mosquito collection data, temperature, precipitation, elevation, land cover and the normalized difference vegetation index (NDVI). The resulting probability maps from the model were consistent with the known environmental limitations of the mosquito with low probabilities predicted for forest covered mountains. July minimum temperature and land cover were the most important variables in the model. Elevation, summer NDVI (July-September), precipitation in July, summer minimum temperature (May-August) and maximum temperature for fall and winter months also contributed to the model. Comparison of the Cx. tritaeniorhynchus model to the distribution of JE cases in the Republic of Korea from 2001 to 2009 showed that cases among a highly vaccinated Korean population were located in high-probability areas for Cx. tritaeniorhynchus. No recent JE cases were reported from the eastern coastline, where higher probabilities of mosquitoes were predicted, but where only small numbers of pigs are raised. The geographical distribution of reported JE cases corresponded closely with the predicted high-probability areas for Cx. tritaeniorhynchus, making the map a useful tool for health risk analysis that could be used for planning preventive public health measures.