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Semen is the body fluid most commonly associated with sexual transmission of human immunodeficiency virus type-1 (HIV-1). Because the male genitourinary tract is distinct immunologically from blood, compartment-dependent factors may determine HIV-1 shedding in semen. To identify these factors, the authors obtained 411 semen and blood specimens from 149 men seen up to three times. Seminal plasma was assayed for HIV-1 RNA and semen was cocultured for HIV-1 and cytomegalovirus (CMV), which may up-regulate HIV-1 replication. The best multivariate model for predicting a positive semen HIV-1 coculture included two local urogenital factors, increased seminal polymorphonuclear cell count (odds ratio (OR) = 12.6 for each log10 increase/mL, 95% confidence interval (CI) 12.2, 134.5) and a positive CMV coculture (OR = 3.0, 95% CI 1.2, 7.7). The best multivariate model for predicting semen HIV-1 RNA included two systemic host factors, CD4+ cell counts <200/microliter (OR = 3.0, 95 percent CI 1.3, 6.9) and nucleoside antiretroviral therapy (monotherapy: OR = 0.5, 95% CI 0.3, 1.0; combination therapy: OR = 0.4, 95% CI 0.2, 0.9), and a positive CMV coculture (OR = 1.7, 95% CI 1.0, 3.0). Thus, both systemic and local genitourinary tract factors influence the risk of semen HIV-1 shedding. These findings suggest that measures of systemic virus burden alone may not predict semen infectivity reliably.

To compare validly the nosocomial infection rates (NIRs) in groups of patients studied from different time periods and/or different hospitals, one must control for the important factors that influence a patient's susceptibility to infection. The authors developed a method for assessing one component of nosocomial infection risk, based on patients' diagnoses and surgical procedures. This method classifies patients according to their risk of developing a nosocomial infection at each of four infection sites and at all four sites combined. Applying the method to data collected on 136,516 patients from 276 hospitals studied in the SENIC Project (Study on the Efficacy of Nosocomial Infection Control), the authors found that NIRs increased according to the predicted ranking of risk categories, even when the analyses were stratified individually by age, sex, hospital service and exposure to urinary catheterization or continuous ventilatory support. Depending on the site of infection, the rate increased as much as 100-fold from low-risk to high-risk categories. The data indicate that infection risk as assessed with this classification method will account for some of the variation in NIRs due to differences in patients' clinical conditions. Further analyses using multivariate techniques must be performed to explore in detail the relative importance of this risk classification in comparison with other risk factors and to determine which factors must be controlled in SENIC analyses.

The primary analyses of the SENIC Project (Study on the Efficacy of Nosocomial Infection Control) will test the association between the presence of infection surveillance and control programs (ISCPs) and changes in nosocomial infection rates (NIRs) as measured by retrospective chart review (RCR). If the establishment of an ISCP affects the quality or completeness of information important for diagnosing infection by RCR, the analyses could be biased (i.e., there could be an increased chance of a Type I or Type II error). To determine whether this type of "ISCP effect" on the accuracy of RCR is likely to occur, the authors carried out a prospective intervention study in one hospital where 1) nosocomial infections among a pre-ISCP cohort of patients were detected by prospective data collection (PDC), 2) the hospital's first ISCP was instituted, and 3) infections were identically studied by PDC exactly two years later. Several months after the end of the second PDC, a team of trained chart reviewers read the medical records of the patients in both study cohorts and abstracted all clinical data bits used for diagnosing nosocomial infection. By a nonparametric matched correlation analysis, no significant change was found in the amount of relevant clinical information recorded in the medical records, and sensitivity and specificity did not change significantly. The authors conclude that, if an ISCP effect on RCR accuracy is present at all, it must be small.

To assess the influence of physicians' diagnostic practices on the recognition of nosocomial infections, the authors analyzed data collected on 339,044 patients selected randomly from admissions in 1970 and 1975-1976 to 338 randomly selected hospitals representative of all acute-care US hospitals. Eight rates representing the frequency of cultures or chest x-rays among patients with or without signs of infection were calculated. These varied widely among hospitals, were highest in teaching hospitals and in the Northeast, but increased more among small hospitals and in the South and West. Rates of performing urine cultures and reporting colony counts were highly correlated with observed rates of nosocomial urinary tract infection. Analogous measures were moderately correlated with observed bacteremia rates and pneumonia rates but were only weakly associated with surgical wound infection rates. These data indicate that the nationwide increase in the use of these diagnostic tests increased the recognition of infectious diseases in US hospitals.

To predict the likelihood that a patient will develop a surgical wound infection from several risk factors, the authors used information collected on 58,498 patients undergoing operations in 1970 to develop a simple multivariate risk index. Analyzing 10 risk factors with stepwise multiple logistic regression techniques, they developed a model combining information on four of the risk factors to predict a patient's probability of getting a surgical wound infection. Then, with information collected on another sample of 59,352 surgical patients admitted in 1975-1976, the validity of this index as a predictor of surgical wound infection risk was verified. With the simplified index, a subgroup, consisting of half the surgical patients, can be identified in whom 90% of the surgical wound infections will develop. By the inclusion of factors measuring the risk due to the patient's susceptibility as well as that due to the level of wound contamination, the simplified index predicts surgical wound infection risk about twice as well as the traditional classification of wound contamination (Goodman-Kruskal G = 0.67 vs. 0.36, p less than 0.0001). Use of this new index might substantially increase the efficiency of routine surgical wound infection surveillance and control.

A series of acute herpetic infections occurred among nurses and patients in a pediatric intensive care unit (PICU). Epidemiologic study revealed two separate time clusters of infections, one in early summer and another six weeks later. Restriction endonuclease analysis of DNA extracted from virus isolates showed that each time cluster was associated with a different genetic strain of herpes simplex virus (HSV) type 1 and provided evidence of cross infection between patients and nurses. Three nurses had herpetic whitlow; the husband of one had acute gingivostomatitis; a fourth nurse had acute pharyngitis. They had no previous history of HSV infection and sequential antibody testing of affected nurses showed 19S antibody in all initially positive serums, confirming primary infection. The data provide clear evidence that PICU personnel risk acquiring serious herpetic infections from patients and vice versa unless specific precautions are taken. Restriction endonuclease analysis of HSV DNA was useful in the epidemiologic study of the infections.