Which comorbid conditions should we be analyzing as risk factors for healthcare-associated infections?

OBJECTIVETo determine which comorbid conditions are considered causally related to central-line associated bloodstream infection (CLABSI) and surgical-site infection (SSI) based on expert consensus.DESIGNUsing the Delphi method, we administered an iterative, 2-round survey to 9 infectious disease and infection control experts from the United States.METHODSBased on our selection of components from the Charlson and Elixhauser comorbidity indices, 35 different comorbid conditions were rated from 1 (not at all related) to 5 (strongly related) by each expert separately for CLABSI and SSI, based on perceived relatedness to the outcome. To assign expert consensus on causal relatedness for each comorbid condition, all 3 of the following criteria had to be met at the end of the second round: (1) a majority (&gt;50%) of experts rating the condition at 3 (somewhat related) or higher, (2) interquartile range (IQR)≤1, and (3) standard deviation (SD)≤1.RESULTSFrom round 1 to round 2, the IQR and SD, respectively, decreased for ratings of 21 of 35 (60%) and 33 of 35 (94%) comorbid conditions for CLABSI, and for 17 of 35 (49%) and 32 of 35 (91%) comorbid conditions for SSI, suggesting improvement in consensus among this group of experts. At the end of round 2, 13 of 35 (37%) and 17 of 35 (49%) comorbid conditions were perceived as causally related to CLABSI and SSI, respectively.CONCLUSIONSOur results have produced a list of comorbid conditions that should be analyzed as risk factors for and further explored for risk adjustment of CLABSI and SSI.Infect Control Hosp Epidemiol 2017;38:449–454</jats:sec

The effect of adding comorbidities to current centers for disease control and prevention central-line–associated bloodstream infection risk-adjustment methodology

BACKGROUNDRisk adjustment is needed to fairly compare central-line–associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes.METHODSUsing a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank.RESULTSOverall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51–0.59) for the ICU-type model and 0.64 (95% CI, 0.60–0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model.CONCLUSIONSOur risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals.Infect Control Hosp Epidemiol 2017;38:1019–1024</jats:sec

Electronically available patient claims data improve models for comparing antibiotic use across hospitals: Results from 576 US facilities

BACKGROUND: The Centers for Disease Control and Prevention (CDC) uses standardized antimicrobial administration ratios (SAARs)-that is, observed-to-predicted ratios-to compare antibiotic use across facilities. CDC models adjust for facility characteristics when predicting antibiotic use but do not include patient diagnoses and comorbidities that may also affect utilization. This study aimed to identify comorbidities causally related to appropriate antibiotic use and to compare models that include these comorbidities and other patient-level claims variables to a facility model for risk-adjusting inpatient antibiotic utilization. METHODS: The study included adults discharged from Premier Database hospitals in 2016-2017. For each admission, we extracted facility, claims, and antibiotic data. We evaluated 7 models to predict an admission\u27s antibiotic days of therapy (DOTs): a CDC facility model, models that added patient clinical constructs in varying layers of complexity, and an external validation of a published patient-variable model. We calculated hospital-specific SAARs to quantify effects on hospital rankings. Separately, we used Delphi Consensus methodology to identify Elixhauser comorbidities associated with appropriate antibiotic use. RESULTS: The study included 11 701 326 admissions across 576 hospitals. Compared to a CDC-facility model, a model that added Delphi-selected comorbidities and a bacterial infection indicator was more accurate for all antibiotic outcomes. For total antibiotic use, it was 24% more accurate (respective mean absolute errors: 3.11 vs 2.35 DOTs), resulting in 31-33% more hospitals moving into bottom or top usage quartiles postadjustment. CONCLUSIONS: Adding electronically available patient claims data to facility models consistently improved antibiotic utilization predictions and yielded substantial movement in hospitals\u27 utilization rankings

Significant regional differences in antibiotic use across 576 US hospitals and 11 701 326 adult admissions, 2016-2017

BACKGROUND: Quantifying the amount and diversity of antibiotic use in United States hospitals assists antibiotic stewardship efforts but is hampered by limited national surveillance. Our study aimed to address this knowledge gap by examining adult antibiotic use across 576 hospitals and nearly 12 million encounters in 2016-2017. METHODS: We conducted a retrospective study of patients aged ≥ 18 years discharged from hospitals in the Premier Healthcare Database between 1 January 2016 and 31 December 2017. Using daily antibiotic charge data, we mapped antibiotics to mutually exclusive classes and to spectrum of activity categories. We evaluated relationships between facility and case-mix characteristics and antibiotic use in negative binomial regression models. RESULTS: The study included 11 701 326 admissions, totaling 64 064 632 patient-days, across 576 hospitals. Overall, patients received antibiotics in 65% of hospitalizations, at a crude rate of 870 days of therapy (DOT) per 1000 patient-days. By class, use was highest among β-lactam/β-lactamase inhibitor combinations, third- and fourth-generation cephalosporins, and glycopeptides. Teaching hospitals averaged lower rates of total antibiotic use than nonteaching hospitals (834 vs 957 DOT per 1000 patient-days; P \u3c .001). In adjusted models, teaching hospitals remained associated with lower use of third- and fourth-generation cephalosporins and antipseudomonal agents (adjusted incidence rate ratio [95% confidence interval], 0.92 [.86-.97] and 0.91 [.85-.98], respectively). Significant regional differences in total and class-specific antibiotic use also persisted in adjusted models. CONCLUSIONS: Adult inpatient antibiotic use remains high, driven predominantly by broad-spectrum agents. Better understanding reasons for interhospital usage differences, including by region and teaching status, may inform efforts to reduce inappropriate antibiotic prescribing

miR-16 and miR-21 Expression in the Placenta Is Associated with Fetal Growth

BACKGROUND: Novel research has suggested that altered miRNA expression in the placenta is associated with adverse pregnancy outcomes and with potentially harmful xenobiotic exposures. We hypothesized that aberrant expression of miRNA in the placenta is associated with fetal growth, a measurable phenotype resulting from a number of intrauterine factors, and one which is significantly predictive of later life outcomes. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed 107 primary, term, human placentas for expression of 6 miRNA reported to be expressed in the placenta and to regulate cell growth and development pathways: miR-16, miR-21, miR-93, miR-135b, miR-146a, and miR-182. The expression of miR-16 and miR-21 was markedly reduced in infants with the lowest birthweights (p<0.05). Logistic regression models suggested that low expression of miR-16 in the placenta predicts an over 4-fold increased odds of small for gestational age (SGA) status (p = 0.009, 95% CI = 1.42, 12.05). Moreover, having both low miR-16 and low miR-21 expression in the placenta predicts a greater increase in odds for SGA than having just low miR-16 or miR-21 expression (p<0.02), suggesting an additive effect of both of these miRNA. CONCLUSIONS/SIGNIFICANCE: Our study is one of the first to investigate placental miRNA expression profiles associated with birthweight and SGA status. Future research on miRNA whose expression is associated with in utero exposures and markers of fetal growth is essential for better understanding the epigenetic mechanisms underlying the developmental origins of health and disease

Life Events, Coping, and Posttraumatic Stress Symptoms among Chinese Adolescents Exposed to 2008 Wenchuan Earthquake, China

PURPOSE: To examine the relationship between negative life events, coping styles, and symptoms of post-traumatic stress disorder (PTSD) among adolescent survivors exposed to 2008 Wenchuan Earthquake, China. METHODS: A survey was conducted in a sample of 2250 adolescent students from two schools in Dujiangyan District, a seriously damaged area, 20 kilometers away from the epicenter, 6 months after the earthquake. Participants completed a self-administered questionnaire including demographics, negative life events, coping styles, and PTSD symptoms. RESULTS: Academic pressure was the strongest predictor of adolescents' PTSD symptoms among all negative life events. Main effects of negative life events, positive coping and negative coping on PTSD symptoms were significant in both younger adolescents and older adolescents, while the moderator effects of two coping styles were found significant only within older adolescents. CONCLUSIONS: Coping may play a role to moderate the relationship between post-earthquake negative life events and PTSD symptom, but the function seems to depend on the age of participants. Psychosocial coping skills training may be important in the prevention and intervention of mental health problems in adolescent survivors of traumatic earthquake

Linking Fearfulness and Coping Styles in Fish

Consistent individual differences in cognitive appraisal and emotional reactivity, including fearfulness, are important personality traits in humans, non-human mammals, and birds. Comparative studies on teleost fishes support the existence of coping styles and behavioral syndromes also in poikilothermic animals. The functionalist approach to emotions hold that emotions have evolved to ensure appropriate behavioral responses to dangerous or rewarding stimuli. Little information is however available on how evolutionary widespread these putative links between personality and the expression of emotional or affective states such as fear are. Here we disclose that individual variation in coping style predicts fear responses in Nile tilapia Oreochromis niloticus, using the principle of avoidance learning. Fish previously screened for coping style were given the possibility to escape a signalled aversive stimulus. Fearful individuals showed a range of typically reactive traits such as slow recovery of feed intake in a novel environment, neophobia, and high post-stress cortisol levels. Hence, emotional reactivity and appraisal would appear to be an essential component of animal personality in species distributed throughout the vertebrate subphylum

The effect of cigarette smoking, alcohol consumption and fruit and vegetable consumption on IVF outcomes: A review and presentation of original data

Background - Lifestyle factors including cigarette smoking, alcohol consumption and nutritional habits impact on health, wellness, and the risk of chronic diseases. In the areas of in-vitro fertilization (IVF) and pregnancy, lifestyle factors influence oocyte production, fertilization rates, pregnancy and pregnancy loss, while chronic, low-grade oxidative stress may underlie poor outcomes for some IVF cases. Methods - Here, we review the current literature and present some original, previously unpublished data, obtained from couples attending the PIVET Medical Centre in Western Australia. Results - During the study, 80 % of females and 70 % of male partners completed a 1-week diary documenting their smoking, alcohol and fruit and vegetable intake. The subsequent clinical outcomes of their IVF treatment such as quantity of oocytes collected, fertilization rates, pregnancy and pregnancy loss were submitted to multiple regression analysis, in order to investigate the relationship between patients, treatment and the recorded lifestyle factors. Of significance, it was found that male smoking caused an increased risk of pregnancy loss (p = 0.029), while female smoking caused an adverse effect on ovarian reserve. Both alcohol consumption (β = 0.074, p < 0.001) and fruit and vegetable consumption (β = 0.034, p < 0.001) had positive effects on fertilization. Conclusion - Based on our results and the current literature, there is an important impact of lifestyle factors on IVF clinical outcomes. Currently, there are conflicting results regarding other lifestyle factors such as nutritional habits and alcohol consumption, but it is apparent that chronic oxidative stress induced by lifestyle factors and poor nutritional habits associate with a lower rate of IVF success

miR-210: fine-tuning the hypoxic response

Hypoxia is a central component of the tumor microenvironment and represents a major source of therapeutic failure in cancer therapy. Recent work has provided a wealth of evidence that noncoding RNAs and, in particular, microRNAs, are significant members of the adaptive response to low oxygen in tumors. All published studies agree that miR-210 specifically is a robust target of hypoxia-inducible factors, and the induction of miR-210 is a consistent characteristic of the hypoxic response in normal and transformed cells. Overexpression of miR-210 is detected in most solid tumors and has been linked to adverse prognosis in patients with soft-tissue sarcoma, breast, head and neck, and pancreatic cancer. A wide variety of miR-210 targets have been identified, pointing to roles in the cell cycle, mitochondrial oxidative metabolism, angiogenesis, DNA damage response, and cell survival. Additional microRNAs seem to be modulated by low oxygen in a more tissue-specific fashion, adding another layer of complexity to the vast array of protein-coding genes regulated by hypoxia