Assessing the risk of human-to-wildlife pathogen transmission for conservation and public health.

The SARS-CoV-2 pandemic has led to increased concern over transmission of pathogens from humans to animals, and its potential to threaten conservation and public health. To assess this threat, we reviewed published evidence of human-to-wildlife transmission events, with a focus on how such events could threaten animal and human health. We identified 97 verified examples, involving a wide range of pathogens; however, reported hosts were mostly non-human primates or large, long-lived captive animals. Relatively few documented examples resulted in morbidity and mortality, and very few led to maintenance of a human pathogen in a new reservoir or subsequent "secondary spillover" back into humans. We discuss limitations in the literature surrounding these phenomena, including strong evidence of sampling bias towards non-human primates and human-proximate mammals and the possibility of systematic bias against reporting human parasites in wildlife, both of which limit our ability to assess the risk of human-to-wildlife pathogen transmission. We outline how researchers can collect experimental and observational evidence that will expand our capacity for risk assessment for human-to-wildlife pathogen transmission.

Physical activity, health status and risk of hospitalization in patients with severe chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a leading cause of death and 70% of the cost of COPD is due to hospitalizations. Self-reported daily physical activity and health status have been reported as predictors of a hospitalization in COPD but are not routinely assessed. OBJECTIVES: We tested the hypothesis that self-reported daily physical activity and health status assessed by a simple question were predictors of a hospitalization in a well-characterized cohort of patients with severe emphysema. METHODS: Investigators gathered daily physical activity and health status data assessed by a simple question in 597 patients with severe emphysema and tested the association of those patient-reported outcomes to the occurrence of a hospitalization in the following year. Multiple logistic regression analyses were used to determine predictors of hospitalization during the first 12 months after randomization. RESULTS: The two variables tested in the hypothesis were significant predictors of a hospitalization after adjusting for all univariable significant predictors: >2 h of physical activity per week had a protective effect [odds ratio (OR) 0.60; 95% confidence interval (95% CI) 0.41-0.88] and self-reported health status as fair or poor had a deleterious effect (OR 1.57; 95% CI 1.10-2.23). In addition, two other variables became significant in the multivariate model: total lung capacity (every 10% increase) had a protective effect (OR 0.88; 95% CI 0.78-0.99) and self-reported anxiety had a deleterious effect (OR 1.75; 95% CI 1.13-2.70). CONCLUSION: Self-reported daily physical activity and health status are independently associated with COPD hospitalizations. Our findings, assessed by simple questions, suggest the value of patient-reported outcomes in developing risk assessment tools that are easy to use.

Is survival better at hospitals with higher "end-of-life" treatment intensity?

BACKGROUND: Concern regarding wide variations in spending and intensive care unit use for patients at the end of life hinges on the assumption that such treatment offers little or no survival benefit. OBJECTIVE: To explore the relationship between hospital "end-of-life" (EOL) treatment intensity and postadmission survival. RESEARCH DESIGN: Retrospective cohort analysis of Pennsylvania Health Care Cost Containment Council discharge data April 2001 to March 2005 linked to vital statistics data through September 2005 using hospital-level correlation, admission-level marginal structural logistic regression, and pooled logistic regression to approximate a Cox survival model. SUBJECTS: A total of 1,021,909 patients > or =65 years old, incurring 2,216,815 admissions in 169 Pennsylvania acute care hospitals. MEASURES: EOL treatment intensity (a summed index of standardized intensive care unit and life-sustaining treatment use among patients with a high predicted probability of dying [PPD] at admission) and 30- and 180-day postadmission mortality. RESULTS: There was a nonlinear negative relationship between hospital EOL treatment intensity and 30-day mortality among all admissions, although patients with higher PPD derived the greatest benefit. Compared with admission at an average intensity hospital, admission to a hospital 1 standard deviation below versus 1 standard deviation above average intensity resulted in an adjusted odds ratio of mortality for admissions at low PPD of 1.06 (1.04-1.08) versus 0.97 (0.96-0.99); average PPD: 1.06 (1.04-1.09) versus 0.97 (0.96-0.99); and high PPD: 1.09 (1.07-1.11) versus 0.97 (0.95-0.99), respectively. By 180 days, the benefits to intensity attenuated (low PPD: 1.03 [1.01-1.04] vs. 1.00 [0.98-1.01]; average PPD: 1.03 [1.02-1.05] vs. 1.00 [0.98-1.01]; and high PPD: 1.06 [1.04-1.09] vs. 1.00 [0.98-1.02]), respectively. CONCLUSIONS: Admission to higher EOL treatment intensity hospitals is associated with small gains in postadmission survival. The marginal returns to intensity diminish for admission to hospitals above average EOL treatment intensity and wane with time.

Development and validation of hospital "end-of-life" treatment intensity measures.

BACKGROUND: Health care utilization among decedents is increasingly used as a measure of health care efficiency, but decedent-based measures may be biased estimates of care received by "dying" patients. OBJECTIVE: To develop and validate new measures of hospital "end-of-life" treatment intensity. RESEARCH DESIGN: Retrospective cohort study using Pennsylvania Health Care Cost Containment Council (PHC4) discharge data (April 2001-March 2005) and Centers for Medicare and Medicaid Services (CMS) data (January 1999-December 2003). SUBJECTS: Patients 65 and older admitted to 174 Pennsylvania acute care hospitals. MEASURES: Hospital-specific standardized ratios of intensive care unit (ICU) and life-sustaining treatment (LST) use among terminal admissions (decedents) and admissions with a high probability of dying, and spending and use of hospitals, ICUs, and physicians among patients in their last 6 months of life. RESULTS: There was marked between-hospital variation in the use of the ICU and LSTs among decedents and admissions with high probability of dying. All hospital decedent and high probability of dying measures were highly correlated (P < 00001). In principal components factor analysis, all 4 of the last-6-months cohort-based measures, the decedent and high-risk admission-based ICU measures, and 8 of the 12 decedent and high probability of dying LST measures loaded onto a single factor, explaining 42% of the variation in the data. CONCLUSIONS: Hospitals' end-of-life intensity varies in the use of specific life-sustaining treatments that are somewhat emblematic of aggressive end-of-life care. End-of-life intensity is a relatively stable hospital attribute that is robust to multiple measurement approaches.

Integrating health status and survival data: the palliative effect of lung volume reduction surgery.

RATIONALE: In studies that address health-related quality of life (QoL) and survival, subjects who die are usually censored from QoL assessments. This practice tends to inflate the apparent benefits of interventions with a high risk of mortality. Assessing a composite QoL-death outcome is a potential solution to this problem. OBJECTIVES: To determine the effect of lung volume reduction surgery (LVRS) on a composite endpoint consisting of the occurrence of death or a clinically meaningful decline in QoL defined as an increase of at least eight points in the St. George's Respiratory Questionnaire total score from the National Emphysema Treatment Trial. METHODS: In patients with chronic obstructive pulmonary disease and emphysema randomized to receive medical treatment (n = 610) or LVRS (n = 608), we analyzed the survival to the composite endpoint, the hazard functions and constructed prediction models of the slope of QoL decline. MEASUREMENTS AND MAIN RESULTS: The time to the composite endpoint was longer in the LVRS group (2 years) than the medical treatment group (1 year) (P < 0.0001). It was even longer in the subsets of patients undergoing LVRS without a high risk for perioperative death and with upper-lobe-predominant emphysema. The hazard for the composite event significantly favored the LVRS group, although it was most significant in patients with predominantly upper-lobe emphysema. The beneficial impact of LVRS on QoL decline was most significant during the 2 years after LVRS. CONCLUSIONS: LVRS has a significant effect on the composite QoL-survival endpoint tested, indicating its meaningful palliative role, particularly in patients with upper-lobe-predominant emphysema.

Organizational determinants of hospital end-of-life treatment intensity.

BACKGROUND: There is substantial hospital-level variation in end-of-life (EOL) treatment intensity. OBJECTIVE: To explore the association between organizational factors and EOL treatment intensity in Pennsylvania (PA) hospitals. RESEARCH DESIGN: Cross-sectional mixed-mode survey of Chief Nursing Officers of PA hospitals linked to hospital-level measures of EOL treatment intensity calculated from PA Health Care Cost Containment Council (PHC4) hospital discharge data. HOSPITALS: One hundred sixty-four hospitals, of which 124 (76%) responded to the survey. MEASURES: : The dependent variable was an index of hospital EOL treatment intensity; the independent variables included administrative data-derived structural and market characteristics and 29 survey-derived hospital or ICU programs, policies, or practices. RESULTS: : In models restricted to independent variables drawn from administrative sources (available for all 164 hospitals), bed size (P < 0.001), proportion of admissions among black patients (P < 0.001), and county-wide hospital market competitiveness (Herfindahl-Hirschman index) (P = 0.001) were independently associated with greater EOL treatment intensity (adjusted R = 0.5136). In models that additionally included hospital programs, policies, and practices (available for 124 hospitals), only an ICU long length of stay review committee (P = 0.03) was independently associated with greater EOL treatment intensity (adjusted R = 0.5357). CONCLUSIONS: Information about hospital and ICU programs, policies, and practices believed relevant to the treatment of patients near the end of life offers little additional explanatory power in understanding hospital-level variation in EOL treatment intensity than administratively-derived variables alone. Future studies should explore the contribution of more difficult to measure social norms in shaping hospital practice patterns.

Factors associated with alcohol use, depression, and their co-occurrence during pregnancy.

BACKGROUND: Alcohol use and depression each adversely affect birth outcomes, but the impact of their co-occurrence among pregnant women is not well understood. In this study, we examined factors associated with alcohol use, depression, and their co-occurrence during pregnancy. METHODS: We analyzed datasets from 2 longitudinal studies conducted nearly 20 years apart in the same outpatient prenatal clinic of an urban women's hospital. Participants included 278 women recruited from 1982 to 1985 for the Maternal Health Practices and Child Development (MHPCD) Study and 209 women recruited from 2000 to 2002 for the Health Outcomes from Prenatal Education (HOPE) Study. Both studies selected women on the basis of their level of alcohol use early in pregnancy. We used multinomial logistic regression models to test multiclassification prediction of alcohol use, depression, and their co-occurrence during pregnancy. RESULTS: In the second and third trimesters, more MHPCD participants than HOPE participants consumed alcohol (67% vs. 20%), experienced depression (85% vs. 34%), and had co-occurring drinking and depression (56% vs. 10%) (p < 0.001 for each). For the MHPCD cohort, smoking predicted alcohol use. There were no significant predictors for depression alone or the co-occurrence. For the HOPE cohort, older age and smoking were predictors of alcohol use, smoking and less education were predictors of depression, and illicit drug use was a predictor of the co-occurrence of alcohol use and depression (p < 0.05 for all relationships). CONCLUSIONS: Smoking, older age, lower education, and illicit substance use predicted alcohol and/or probable depression in the second and third trimesters among women who drank in the first trimester.

Prevalence of urinary tract infection in childhood: a meta-analysis.

BACKGROUND: Knowledge of baseline risk of urinary tract infection can help clinicians make informed diagnostic and therapeutic decisions. We conducted a meta-analysis to determine the pooled prevalence of urinary tract infection (UTI) in children by age, gender, race, and circumcision status. METHODS: MEDLINE and EMBASE databases were searched for articles about pediatric urinary tract infection. Search terms included urinary tract infection, cystitis, pyelonephritis, prevalence and incidence. We included articles in our review if they contained data on the prevalence of UTI in children 0-19 years of age presenting with symptoms of UTI. Of the 51 articles with data on UTI prevalence, 18 met all inclusion criteria. Two evaluators independently reviewed, rated, and abstracted data from each article. RESULTS: Among infants presenting with fever, the overall prevalence (and 95% confidence interval) of UTI was 7.0% (CI: 5.5-8.4). The pooled prevalence rates of febrile UTIs in females aged 0-3 months, 3-6 months, 6-12 months, and >12 months was 7.5%, 5.7%, 8.3%, and 2.1% respectively. Among febrile male infants less than 3 months of age, 2.4% (CI: 1.4-3.5) of circumcised males and 20.1% (CI: 16.8-23.4) of uncircumcised males had a UTI. For the 4 studies that reported UTI prevalence by race, UTI rates were higher among white infants 8.0% (CI: 5.1-11.0) than among black infants 4.7% (CI: 2.1-7.3). Among older children (<19 years) with urinary symptoms, the pooled prevalence of UTI (both febrile and afebrile) was 7.8% (CI: 6.6-8.9). CONCLUSIONS: Prevalence rates of UTI varied by age, gender, race, and circumcision status. Uncircumcised male infants less than 3 months of age and females less than 12 months of age had the highest baseline prevalence of UTI. Prevalence estimates can help clinicians make informed decisions regarding diagnostic testing in children presenting with signs and symptoms of urinary tract infection.

Mapping FACT-P and EORTC QLQ-C30 to patient health status measured by EQ-5D in metastatic hormone-refractory prostate cancer patients.

OBJECTIVES: To construct and validate a prediction model of preference-adjusted health status (EQ-5D) for metastatic hormone-refractory prostate cancer (HRPCA) patients using cancer-specific health-related quality of life (HRQoL) measures. METHODS: Data were obtained from a multicenter, multinational observational study of metastatic HRPCA patients conducted during 2002 to 2004. In addition to clinical and resource utilization, preference-adjusted health status (EQ-5D) and HRQoL (Functional Assessment of Cancer Therapy-Prostate [FACT-P] and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire [EORTC QLQ-C30]) data were collected. Predictive validity of ordinary least square (OLS) and median regressions of various model specifications were tested using cross-validation samples. The selected specification was then further refined and tested for alternative model specifications and restrictions. RESULTS: OLS regression with both HRQoL measures as individual components and patient demographics was the best-performing model. It explained 58.2% of the observed EQ-5D variation in the validation sample. A model including only the prostate cancer-specific HRQoL measure, FACT-P, explained 53.5% of the observed EQ-5D variation. CONCLUSIONS: The models developed have good predictive validity. These algorithms enable researchers to translate cancer-specific HRQoL measures to preference-adjusted health status in metastatic HRPCA patients. The findings will help perform health status adjustments in cost-utility analyses.

Annual costs associated with diagnosis of uterine leiomyomata.

OBJECTIVE: To describe the annual care, direct health care, and indirect work loss costs for women with a diagnosis of uterine leiomyomata. METHODS: We examined data from an employer claims database of 1.2 million beneficiaries (1999 to 2003). Analysis was restricted to women with at least 12 months of continuous coverage and ages 18 to 64 years with at least one diagnosis of leiomyomata (International Classification of Diseases, 9th Revision, 218.xx, 654.1x). We selected a comparison group of women without a leiomyoma diagnosis using a 1:1 match on age, employment, region, health plan type, and length of enrollment. We compared resource use, disability claims, and excess costs in the year after the index diagnosis. RESULTS: The average age of women diagnosed with leiomyomata in this study was 43.7 years. Women with leiomyomata (N = 5,122) had more clinic visits (relative risk [RR] 1.2, 95% confidence interval [CI] 1.2-1.2), diagnostic tests (RR 3.1, 95% CI 2.9-3.2), and procedures (RR 34.6, 95% CI 25.8-46.5) than controls (N = 5,122). Within 1 year of the diagnosis of leiomyomata, 42% of women had a complete blood count, 66% had pelvic imaging, and 30% had surgery (68% of surgical procedures involved hysterectomy). Women with leiomyomata were 3-fold more likely to have disability claims (RR 3.1, 95% CI 2.7-3.6). Estimated average annual excess cost for each woman with leiomyomata (adjusted for confounders) was Dollars 4,624 (Dollars 771 in work loss costs). Total costs for women with leiomyomata were 2.6 times greater than for controls. CONCLUSION: Diagnosed uterine leiomyomata are associated with increased resource use and with substantially higher health care and work loss costs. LEVEL OF EVIDENCE: II-3.