Setting the revisit interval in primary care

OBJECTIVE: Although longitudinal care constitutes the bulk of primary care, physicians receive little guidance on the fundamental question of how to time follow-up visits. We sought to identify important predictors of the revisit interval and to describe the variability in how physicians set these intervals when caring for patients with common medical conditions. DESIGN: Cross-sectional survey of physicians performed at the end of office visits for consecutive patients with hypertension, angina, diabetes, or musculoskeletal pain. PARTICIPANTS/SETTING: One hundred sixty-four patients under the care of 11 primary care physicians in the Dartmouth Primary Care Cooperative Research Network. MEASUREMENTS: The main outcome measures were the variability in mean revisit intervals across physicians and the proportion of explained variance by potential determinants of revisit intervals. We assessed the relation between the revisit interval (dependent variable) and three groups of independent variables, patient characteristics (e.g., age, physician perception of patient health), identification of individual physician, and physician characterization of the visit (e. g., routine visit, visit requiring a change in management, or visit occurring on a "hectic" day), using multiple regression that accounted for the natural grouping of patients within physician. MAIN RESULTS: Revisit intervals ranged from 1 week to over 1 year. The most common intervals were 12 and 16 weeks. Physicians' perception of fair-poor health status and visits involving a change in management were most strongly related to shorter revisit intervals. In multivariate analyses, patient characteristics explained about 18% of the variance in revisit intervals, and adding identification of the individual provider doubled the explained variance to about 40%. Physician characterization of the visit increased explained variance to 57%. The average revisit interval adjusted for patient characteristics for each of the 11 physicians varied from 4 to 20 weeks. Although all physicians lengthened revisit intervals for routine visits and shortened them when changing management, the relative ranking of mean revisit intervals for each physician changed little for different visit characterizations-some physicians were consistently long and others were consistently short. CONCLUSION: Physicians vary widely in their recommendations for office revisits. Patient factors accounted for only a small part of this variation. Although physicians responded to visits in predictable ways, each physician appeared to have a unique set point for the length of the revisits interval.     

Venobronchial fistula: an unusual complication of long-term central venous access

A venobronchial fistula developed between the azygous vein and the upper aspect of the right main bronchus 12 months after completion of the treatment of a stage IIIB non-small-cell lung cancer in a 54-year-old man. The fistula contained the tip of the catheter placed for chemotherapy perfusion. The reported case presented risk factors previously identified for such a complication. In addition, some clinical particularities were present, suggesting new potent risk factors and some preventive means for safe long-term central venous catheterization.     

In vivo tracking in cardiac stem cell-based therapy

Cell-based therapy has been heralded as a promising, novel therapeutic strategy for cardiovascular diseases. Despite a rapid transition from animal studies to clinical trials, there remain numerous unresolved, and at times, controversial issues with respect to underlying molecular mechanisms. In parallel, recent advances in the field of molecular imaging has provided a means to bridge the gap in knowledge through in vivo stem cells tracking. Herein, we review current in vivo imaging techniques and future directions for tracking the effects of cell-based therapy.     

The Relationship Between Static and Dynamic Risk Factors and Reconviction in a Sample of U.K. Child Abusers

This study examined how well historical information and psychometric data predicted sexual recidivism in a sample of child abusers about to undergo group-based cognitive behavioral treatment in the community. Static, historical factors, as measured by the Static-99 (R. K. Hanson & D. Thornton, 2000), significantly predicted recidivism over the 6-year follow-up period. High-risk men were over 5 times more likely to be reconvicted for a sexual offence compared to low-risk men. Adding psychometric measures of dynamic risk (e.g., pro-offending attitudes, socio-affective problems) significantly increased the accuracy of risk prediction beyond the level achieved by the actuarial assessment of static factors. This result indicates the importance of considering dynamic risk factors in any comprehensive risk protocol.     

Stature estimation based on hand length and foot length

This study was carried out to estimate the relationship between hand length, foot length and stature using multiple linear regression analyses based on a sample of male and female adult Turks residing in Adana. Measurements of hand length, foot length and stature were taken from 155 adult Turks (80 male, 75 female) aged 17-23 years. The participants were students of the Medical Faculty of Cukurova University. A multiple linear regression model was fitted to the observed data. Stature was taken as the response or dependent variable, hand length and foot length were taken as explanatory variables or regressors. All possible (simple and multiple) linear regression models for each of males, females and both genders together were tested for the best model. The multiple linear regression model for both genders together was found to be the best model with the highest values for the coefficients of determination R2 = 0.861 and R2adjusted = 0.859, and multiple correlation coefficient R = 0.928.     

Isolation of a fastidious Bergeyella species associated with cellulitis after a cat bite and a phylogenetic comparison with Bergeyella zoohelcum strains

Bergeyella zoohelcum is an uncommon zoonotic pathogen typically associated with cat or dog bites. Previously, only five cases of B. zoohelcum infection have been reported. We report the isolation and characterization of a fastidious Bergeyella species from acute cellulitis in the upper extremity of a 60-year-old woman. The organism was too fastidious for identification and susceptibility testing with traditional culture methods. The isolate was characterized further by PCR amplification and sequencing of the 16S rRNA gene with broad-range eubacterial primers. Phylogenetic analysis of the 16S ribosomal DNA sequence indicated that this isolate was a member of the species B. zoohelcum (previously Weeksella zoohelcum), a gram-negative bacillus that is rarely associated with infections in humans. Despite sharing a close genetic relationship with other B. zoohelcum strains, this isolate was extremely fastidious in nature, raising the possibility that similar strains from cat or dog bite wound infections have been underreported.     

Identification of the severe acute respiratory syndrome coronavirus by simultaneous multigene DNA sequencing

The recent severe acute respiratory syndrome (SARS) outbreak resulted in calls for an accurate diagnostic test that can be used not only for routine testing but also for generating nucleotide sequences to monitor the epidemic. Although the identity of the SARS coronavirus (SARS-CoV) genome was confirmed by DNA sequencing, it is impractical to sequence the entire 29-kb SARS-CoV genome on a routine basis. Therefore, alternative assay methods such as the enzyme-linked immunosorbent assay and PCR have been pursued for routine testing, primarily to resolve probable cases. We report here a modification of standard DNA sequencing technology for accurate identification of SARS-CoV in routine testing. Instead of requiring the sequencing of the whole SARS-CoV genome, our modification enables the simultaneous sequencing of three regions of the SARS-CoV genome, the spike protein-encoding gene (35 nucleotides), gene M (43 nucleotides), and gene N (45 nucleotides), in a single electropherogram. Comparing these nucleotide sequences to DNA databank entries (National Institutes of Health) conclusively identified them as SARS-CoV sequences.