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Background: There has recently been considerable interest in better understanding how blood pressure should be managed after an episode of hospitalized AKI, but there are scant data regarding the associations between blood pressure measured after AKI and subsequent adverse outcomes. We hypothesized that among AKI survivors, higher blood pressure measured three months after hospital discharge would be associated with worse outcomes. We also hypothesized these associations between blood pressure and outcomes would be similar among those who survived non-AKI hospitalizations.Methods: We quantified how systolic blood pressure (SBP) observed three months after hospital discharge was associated with risks of subsequent hospitalized AKI, loss of kidney function, mortality, and heart failure events among 769 patients in the prospective ASSESS-AKI cohort study who had hospitalized AKI. We repeated this analysis among the 769 matched non-AKI ASSESS-AKI enrollees. We then formally tested for AKI interaction in the full cohort of 1538 patients to determine if these associations differed among those who did and did not experience AKI during the index hospitalization.Results: Among 769 patients with AKI, 42 % had subsequent AKI, 13 % had loss of kidney function, 27 % died, and 18 % had heart failure events. SBP 3 months post-hospitalization did not have a stepwise association with the risk of subsequent AKI, loss of kidney function, mortality, or heart failure events. Among the 769 without AKI, there was also no stepwise association with these risks. In formal interaction testing using the full cohort of 1538 patients, hospitalized AKI did not modify the association between post-discharge SBP and subsequent risks of adverse clinical outcomes.Conclusions: Contrary to our first hypothesis, we did not observe that higher stepwise blood pressure measured three months after hospital discharge with AKI was associated with worse outcomes. Our data were consistent with our second hypothesis that the association between blood pressure measured three months after hospital discharge and outcomes among AKI survivors is similar to that observed among those who survived non-AKI hospitalizations. [ABSTRACT FROM AUTHOR]

Background: Acute kidney injury (AKI) and obesity are independent risk factors for chronic kidney disease (CKD). This study aimed to determine if obesity modifies risk for CKD outcomes after AKI.Methods: This prospective multisite cohort study followed adult survivors after hospitalization, with or without AKI. The primary outcome was a combined CKD event of incident CKD, progression of CKD and kidney failure, examined using time-to-event Cox proportional hazards models, adjusted for diabetes status, age, pre-existing CKD, cardiovascular disease status and intensive care unit admission, and stratified by study center. Body mass index (BMI) was added as an interaction term to examine effect modification by body size.Results: The cohort included 769 participants with AKI and 769 matched controls. After median follow-up of 4.3 years, among AKI survivors, the rate of the combined CKD outcome was 84.7 per1000-person-years with BMI ≥30 kg/m2, 56.4 per 1000-person-years with BMI 25-29.9 kg/m2, and 72.6 per 1000-person-years with BMI 20-24.9 kg/m2. AKI was associated with a higher risk of combined CKD outcomes; adjusted-HR 2.43 (95%CI 1.87-3.16), with no evidence that this was modified by BMI (p for interaction = 0.3). After adjustment for competing risk of death, AKI remained associated with a higher risk of the combined CKD outcome (subdistribution-HR 2.27, 95%CI 1.76-2.92) and similarly, there was no detectable effect of BMI modifying this risk.Conclusions: In this post-hospitalization cohort, we found no evidence for obesity modifying the association between AKI and development or progression of CKD. [ABSTRACT FROM AUTHOR]

Background: Malaria and HIV are common infections in Africa and cause substantial morbidity and mortality in pregnant women. We aimed to assess the association of malaria with anemia in pregnant women and to explore the joint effects of malaria and HIV infection on anemia in pregnant women.Methods: We used nationally representative, cross-sectional demographic and health surveys (DHS) that were conducted between 2012 and 2017 across 7 countries of sub-Saharan Africa (Burundi, the Democratic Republic of the Congo, Gambia, Ghana, Mali, Senegal and Togo). The outcome variables were anemia (defined as a hemoglobin concentration < 110 g/L), and hemoglobin concentration on a continuous scale, in pregnant women at the time of the interview. We used generalized linear mixed-effects models to account for the nested structure of the data. We adjusted models for individual covariates, with random effects of the primary sampling unit nested within a country.Results: A total of 947 pregnant women, ages, 15-49 y, were analyzed. Prevalence of malaria only, HIV only, and malaria- HIV coinfection in pregnant women was 31% (95% CI: 28.5 to 34.5%, n = 293), 1.3% (95% CI: 0.77 to 2.4%, n = 13) and 0.52% (95% CI: 0.02 to 1.3%, n = 5) respectively. Overall prevalence of anemia was 48.3% (95% CI: 45.1 to 51.5%). The anemia prevalence in pregnant women with malaria infection only was 56.0% (95% CI: 50.1 to 61.7%); HIV infection only, 62.5% (95% CI: 25.9 to 89.8%); malaria- HIV coinfection, 60.0 (95% CI: 17.0-92.7%) and without either infection, 44.6% (95% CI: 40.7 to 48.6%). In the fully adjusted models, malaria infection was associated with 27% higher prevalence of anemia (95% CI of prevalence ratio: 1.12 to 1.45; p = 0.004), and 3.4 g/L lower hemoglobin concentration (95% CI: - 5.01 to - 1.79; p = 0.03) compared to uninfected pregnant women. The prevalence of HIV infection and malaria-HIV coinfection was too low to allow meaningful analysis of their association with anemia or hemoglobin concentration.Conclusion: Malaria was associated with an increased prevalence of anemia during pregnancy. [ABSTRACT FROM AUTHOR]

Background: Area-level socioeconomic characteristics have been shown to be related to health status and mortality however, little is known about the association between residential community characteristics in relation to postpartum women's health.Methods: Data from the longitudinal, multi-site Community Child Health Network (CCHN) study were used. Postpartum women (n = 2510), aged 18-40 were recruited from 2008 to 2012 within a month of delivery. Socioeconomic data was used to create deprivation indices. Census data were analysed using principal components analysis (PCA) and logistic regression to assess the association between deprivation indices (DIs) and various health indicators.Results: PCA resulted in two unique DIs that accounted for 67.5% of the total variance of the combined all-site area deprivation. The first DI was comprised of variables representing a high percentage of Hispanic or Latina, foreign-born individuals, dense households (more than one person per room of residence), with less than a high-school education, and who spent more than 30% of their income on housing costs. The second DI was comprised of a high percentage of African-Americans, single mothers, and high levels of unemployment. In a multivariate logistic regression model, using the quartiles of each DI, women who reside in the geographic area of Q4-Q2 of the second DI, were almost twice as likely to have more than three adverse health conditions compared to those who resided in the least deprived areas. (Q2vs.Q1:OR = 2.09,P = 0.001,Q3vs.Q1:OR = 1.89,P = 0.006,Q4vs.Q1:OR = 1.95,P = 0.004 respectively).Conclusions: Our results support the utility of examining deprivation indices as predictors of maternal postpartum health. [ABSTRACT FROM AUTHOR]

Background: Surfactant protein A (SP-A) contributes to lung immunity by regulating inflammation and responses to microorganisms invading the lung. The huge genetic variability of SP-A in humans implies that this protein is highly important in tightly regulating the lung immune response. Proteomic studies have demonstrated that there are differential responses of the macrophages to SP-A1 and SP-A2 and that there are sex differences implicated in these responses. Methods: Purified SP-A variants were used for administration to alveolar macrophages from SP-A knockout (KO) mice for in vitro studies, and alveolar macrophages from humanized SP-A transgenic mice were isolated for ex vivo studies. The actin cytoskeleton was examined by fluorescence and confocal microscopy, and the macrophages were categorized according to the distribution of polymerized actin. Results: In accordance with previous data, we report that there are sex differences in the response of alveolar macrophages to SP-A1 and SP-A2. The cell size and F-actin content of the alveolar macrophages are sex- and agedependent. Importantly, there are different subpopulations of cells with differential distribution of polymerized actin. In vitro, SP-A2 destabilizes actin in female, but not male, mice, and the same tendency is observed by SP-A1 in cells from male mice. Similarly, there are differences in the distribution of AM subpopulations isolated from SP-A transgenic mice depending on sex and age. Conclusions: There are marked sex- and age-related differences in the alveolar macrophage phenotype as illustrated by F-actin staining between SP-A1 and SP-A2. Importantly, the phenotypic switch caused by the different SP-A variants is subtle, and pertains to the frequency of the observed subpopulations, demonstrating the need for single-cell analysis approaches. The differential responses of alveolar macrophages to SP-A1 and SP-A2 highlight the importance of genotype in immune regulation and the susceptibility to lung disease and the need for development of individualized treatment options. [ABSTRACT FROM AUTHOR]

Background: Adverse drug reactions are a leading cause of death in the United States. Safe and effective management of complex medication regimens is a skill for which recent medical school graduates may be unprepared when they transition to residency. We wished to assess the impact of a medication safety curriculum on student competency when evaluating medication therapeutic appropriateness as well as evaluate students' ability to transfer curricular material to management of patients in clinical settings. Methods: To prepare 3rd and 4th year medical students to critically evaluate medication safety and appropriateness, we developed a medication reconciliation/optimization curriculum and embedded it within a Patient-Centered Medical Home longitudinal elective. This curriculum is comprised of a medication reconciliation workshop, in-class and individual case-based assignments, and authentic patient encounters in which medication management skills are practiced and refined. Pre- and post-course competency and skills with medication reconciliation/optimization are evaluated by assessing student ability to identify and resolve medication-related problems (MRPs) in case-based assignments using paired difference tests. A group of students who had wished to enroll in the elective but whose schedule did not permit it, served as a comparison group. Results: Students completing the curriculum (n = 45) identified 75 % more MRPs in case assignments compared to baseline. No changes from baseline were apparent in the comparison group. Enrolled students were able to transfer their skills to the care of authentic patients; these students identified an average of 2.5 MRPs per patient from a panel of individuals that had recently transitioned from hospital to home. Moreover, patient questionnaires (before and several months following the medication encounters with assigned students) indicated that patients felt more knowledgeable about several medication parameters as a result of the student-led medication encounter. Patients also indicated that students helped them overcome barriers to medication adherence (e.g. cost, transportation, side effects). Conclusions: Novice learners may have difficulty transitioning from knowledge of basic pharmacology facts to application of that information in clinical practice. Our curriculum appears to bridge that gap in ways that may positively impact patient care. [ABSTRACT FROM AUTHOR]

Background: In many clinical biomarker studies, Lin’s concordance correlation coefficient (CCC) is commonly used to assess the level of agreement of a biomarker measured under two different conditions. However, measurement of a specific biomarker typically cannot provide accurate numerical values below the lower limit of detection (LLD) of the assay, which results in left-censored data. Most researchers discard the data below the LLD or apply simple data imputation methods in the presence of left-censored data, such as replacing values below the LLD with a fixed number less than or equal to the LLD. This is not statistically optimal, because it often leads to biased estimates and overestimates the precision. Methods: We describe a simple method using a bivariate normal distribution in this situation and apply SAS statistical software to arrive at the maximum likelihood (ML) estimate of the parameters and construct the estimate of the CCC. We conduct a computer simulation study to investigate the statistical properties of the ML method versus the data deletion and simple data imputation method. We also contrast the methods with real data using two urine biomarkers, Interleukin 18 and Cystatin C. Results: The computer simulation studies confirm that the ML procedure is superior to the data deletion and simple data imputation procedures. In all of the simulated scenarios, the ML method yields the smallest relative bias and the highest percentage of the 95% confidence intervals that include the true value of the CCC. In the first simulation scenario (sample size of 100 paired data points, 25% left-censoring for both members of the pair, true CCC of 0.238), the relative bias is −1.43% for the ML method, −40.97% for the data deletion method, and it ranges between −12.94% and −21.72% for the simple data imputation methods. Similarly, when the left-censoring for one of the members of the data pairs increases from 25% to 40%, the relative bias displays the same pattern for all methods. Conclusions: When estimating the CCC from paired biomarker data in the presence of left-censored values, the ML method works better than data deletion and simple data imputation methods. [ABSTRACT FROM AUTHOR]

Background: High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronicallymediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. Methods/Design: A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Discussion: Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. [ABSTRACT FROM AUTHOR]

Background: Airway hyperresponsiveness (AHR), a primary characteristic of asthma, involves increased airway smooth muscle contractility in response to certain exposures. We sought to determine whether common genetic variants were associated with AHR severity. Methods: A genome-wide association study (GWAS) of AHR, quantified as the natural log of the dosage of methacholine causing a 20% drop in FEV1, was performed with 994 non-Hispanic white asthmatic subjects from three drug clinical trials: CAMP, CARE, and ACRN. Genotyping was performed on Affymetrix 6.0 arrays, and imputed data based on HapMap Phase 2, was used to measure the association of SNPs with AHR using a linear regression model. Replication of primary findings was attempted in 650 white subjects from DAG, and 3,354 white subjects from LHS. Evidence that the top SNPs were eQTL of their respective genes was sought using expression data available for 419 white CAMP subjects. Results: The top primary GWAS associations were in rs848788 (P-value 7.2E-07) and rs6731443 (P-value 2.5E-06), located within the ITGB5 and AGFG1 genes, respectively. The AGFG1 result replicated at a nominally significant level in one independent population (LHS P-value 0.012), and the SNP had a nominally significant unadjusted P-value (0.0067) for being an eQTL of AGFG1. Conclusions: Based on current knowledge of ITGB5 and AGFG1, our results suggest that variants within these genes may be involved in modulating AHR. Future functional studies are required to confirm that our associations represent true biologically significant findings. [ABSTRACT FROM AUTHOR]

Background: Viewing Plasmodium in Romanovsky-stained blood has long been considered the gold standard for diagnosis and a cornerstone in management of the disease. This method however, requires a subjective evaluation by trained, experienced diagnosticians and establishing proficiency of diagnosis is fraught with many challenges. Reported here is an evaluation of a diagnostic system (a "device" consisting of a microscope, a scanner, and a computer algorithm) that evaluates scanned images of standard Giemsa-stained slides and reports species and parasitaemia. Methods: The device was challenged with two independent tests: a 55 slide, expert slide reading test the composition of which has been published by the World Health Organization ("WHO55" test), and a second test in which slides were made from a sample of consenting subjects participating in a malaria incidence survey conducted in Equatorial Guinea (EGMIS test). These subjects' blood was tested by malaria RDT as well as having the blood smear diagnosis unequivocally determined by a worldwide panel of a minimum of six reference microscopists. Only slides with unequivocal microscopic diagnoses were used for the device challenge, n = 119. Results: On the WHO55 test, the device scored a "Level 4" using the WHO published grading scheme. Broken down by more traditional analysis parameters this result was translated to 89% and 70% sensitivity and specificity, respectively. Species were correctly identified in 61% of the slides and the quantification of parasites fell within acceptable range of the validated parasitaemia in 10% of the cases. On the EGMIS test it scored 100% and 94% sensitivity/specificity, with 64% of the species correct and 45% of the parasitaemia within an acceptable range. A pooled analysis of the 174 slides used for both tests resulted in an overall 92% sensitivity and 90% specificity with 61% species and 19% quantifications correct. Conclusions: In its current manifestation, the device performs at a level comparable to that of many human slide readers. Because its use requires minimal additional equipment and it uses standard stained slides as starting material, its widespread adoption may eliminate the current uncertainty about the quality of microscopic diagnoses worldwide. [ABSTRACT FROM AUTHOR]

Background: The incidence of acute kidney injury (AKI) has been increasing over time and is associated with a high risk of short-term death. Previous studies on hospital-acquired AKI have important methodological limitations, especially their retrospective study designs and limited ability to control for potential confounding factors. Methods: The Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study was established to examine how a hospitalized episode of AKI independently affects the risk of chronic kidney disease development and progression, cardiovascular events, death, and other important patient-centered outcomes. This prospective study will enroll a cohort of 1100 adult participants with a broad range of AKI and matched hospitalized participants without AKI at three Clinical Research Centers, as well as 100 children undergoing cardiac surgery at three Clinical Research Centers. Participants will be followed for up to four years, and will undergo serial evaluation during the index hospitalization, at three months post-hospitalization, and at annual clinic visits, with telephone interviews occurring during the intervening six-month intervals. Biospecimens will be collected at each visit, along with information on lifestyle behaviors, quality of life and functional status, cognitive function, receipt of therapies, interim renal and cardiovascular events, electrocardiography and urinalysis. Conclusions: ASSESS-AKI will characterize the short-term and long-term natural history of AKI, evaluate the incremental utility of novel blood and urine biomarkers to refine the diagnosis and prognosis of AKI, and identify a subset of high-risk patients who could be targeted for future clinical trials to improve outcomes after AKI. [ABSTRACT FROM AUTHOR]

Background: Sex differences have been described in a number of pulmonary diseases. However, the impact of ozone exposure followed by pneumonia infection on sex-related survival and macrophage function have not been reported. The purpose of this study was to determine whether ozone exposure differentially affects: 1) survival of male and female mice infected with Klebsiella pneumoniae, and 2) the phagocytic ability of macrophages from these mice. Methods: Male and female C57BL/6 mice were exposed to O3 or to filtered air (FA) (control) and then infected intratracheally with K. pneumoniae bacteria. Survival was monitored over a 14-day period, and the ability of alveolar macrophages to phagocytize the pathogen in vivo was investigated after 1 h. Results: 1) Both male and female mice exposed to O3 are significantly more susceptible to K. pneumoniae infection than mice treated with FA; 2) although females appeared to be more resistant to K. pneumoniae than males, O3 exposure significantly increased the susceptibility of females to K. pneumoniae infection to a greater degree than males; 3) alveolar macrophages from O3-exposed male and female mice have impaired phagocytic ability compared to macrophages from FA-exposed mice; and 4) the O3-dependent reduction in phagocytic ability is greater in female mice. Conclusion: O3 exposure reduces the ability of mice to survive K. pneumoniae infection and the reduced phagocytic ability of alveolar macrophages may be one of the contributing factors. Both events are significantly more pronounced in female mice following exposure to the environmental pollutant, ozone. [ABSTRACT FROM AUTHOR]

Background: In many clinical biomarker studies, Lin's concordance correlation coefficient (CCC) is commonly used to assess the level of agreement of a biomarker measured under two different conditions. However, measurement of a specific biomarker typically cannot provide accurate numerical values below the lower limit of detection (LLD) of the assay, which results in left-censored data. Most researchers discard the data below the LLD or apply simple data imputation methods in the presence of left-censored data, such as replacing values below the LLD with a fixed number less than or equal to the LLD. This is not statistically optimal, because it often leads to biased estimates and overestimates the precision., Methods: We describe a simple method using a bivariate normal distribution in this situation and apply SAS statistical software to arrive at the maximum likelihood (ML) estimate of the parameters and construct the estimate of the CCC. We conduct a computer simulation study to investigate the statistical properties of the ML method versus the data deletion and simple data imputation method. We also contrast the methods with real data using two urine biomarkers, Interleukin 18 and Cystatin C., Results: The computer simulation studies confirm that the ML procedure is superior to the data deletion and simple data imputation procedures. In all of the simulated scenarios, the ML method yields the smallest relative bias and the highest percentage of the 95% confidence intervals that include the true value of the CCC. In the first simulation scenario (sample size of 100 paired data points, 25% left-censoring for both members of the pair, true CCC of 0.238), the relative bias is -1.43% for the ML method, -40.97% for the data deletion method, and it ranges between -12.94% and -21.72% for the simple data imputation methods. Similarly, when the left-censoring for one of the members of the data pairs increases from 25% to 40%, the relative bias displays the same pattern for all methods., Conclusions: When estimating the CCC from paired biomarker data in the presence of left-censored values, the ML method works better than data deletion and simple data imputation methods.