36 research outputs found
Fluoroquinolone resistance during 2000–2005 : An observational study
<p>Abstract</p> <p>Background</p> <p>Moxifloxacin is a respiratory fluoroquinolone with a community acquired pneumonia indication. Unlike other fluoroquinolones used in our healthcare system, moxifloxacin's urinary excretion is low and thus we hypothesized that increased use of moxifloxacin is associated with an increase in fluoroquinolone resistance amongst gram negative uropathogens.</p> <p>Methods</p> <p>All antibiograms for Gram negative bacteria were obtained for 2000 to 2005. The defined daily dose (DDD) for each fluoroquinolone was computed according to World Health Organization criteria. To account for fluctuation in patient volume, DDD/1000 bed days was computed for each year of study. Association between DDD/1000 bed days for each fluoroquinolone and the susceptibility of Gram negative bacteria to ciprofloxacin was assessed using Pearson's Correlation Coefficient, r.</p> <p>Results</p> <p>During the study period, there were 48,261 antibiograms, 347,931 DDD of fluoroquinolones, and 1,943,338 bed days. Use of fluoroquinolones among inpatients decreased from 237.2 DDD/1000 bed days in 2000 to 115.2 DDD/1000 bed days in 2005. With the exception of <it>Enterobacter aerogenes</it>, moxifloxacin use was negatively correlated with sensitivity among all 13 Gram negative species evaluated (r = -0.07 to -0.97). When the sensitivities of all Gram negative organisms were aggregated, all fluoroquinolones except moxifloxacin were associated with increased sensitivity (r = 0.486 to 1.000) while moxifloxacin was associated with decreased sensitivity (r = -0.464).</p> <p>Conclusion</p> <p>Moxifloxacin, while indicated for empiric treatment of community acquired pneumonia, may have important negative influence on local antibiotic sensitivities amongst Gram negative organisms. This effect was not shared by other commonly used members of the fluoroquinolone class.</p
Consistent patterns of common species across tropical tree communities
Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe
S3 detection as a diagnostic and prognostic aid in emergency department patients with acute dyspnea
STUDY OBJECTIVE: Dyspneic emergency department (ED) patients present a diagnostic dilemma. Recent technologic advances have made it possible to capture information about pathologic heart sounds at ECG recording. This study evaluates the effect of an S3 captured by acoustic cardiography on emergency physician diagnostic accuracy and confidence in their diagnosis of acute decompensated heart failure, as well as the patient's prognosis. METHODS: Dyspneic ED patients older than 40 years who were not dialysis dependent were prospectively enrolled in this multinational study. Treating emergency physicians, initially blinded to all laboratory and acoustic cardiography results, estimated acute decompensated heart failure probability from 0% to 100% on a visual analog scale. The emergency physician repeated the visual analog scale after acoustic cardiography results were provided. Physician diagnostic accuracy for and confidence in acute decompensated heart failure were evaluated against a reference standard diagnosis, as determined by 2 independent cardiologists blinded to acoustic cardiography. Patients were followed through 90 days to determine the relationship of the S3 to adverse events. RESULTS: Nine hundred ninety-five patients with acoustic cardiography results were enrolled from March to October 2006 at 7 US and 2 international sites. Median age was 63 years, 55% were men, and 44% were white. The reference diagnosis was acute decompensated heart failure in 41.5%. After initial history and physical examination, the treating physician's initial sensitivity, specificity, and accuracy for acute decompensated heart failure as a possible diagnosis were 89.0% (95% confidence interval [CI] 85.5% to 91.8%), 58.2% (95% CI 54.0% to 62.2%), and 71.0% (95% CI 68.4% to 73.8%), respectively. Acoustic cardiography had an accuracy of 68% (95% CI 65.4% to 71.3%), sensitivity of 40.2% (95% CI 35.5% to 45.1%), and specificity of 88.5% (95% CI 85.5% to 90.9%). Emergency physician confidence and diagnostic accuracy were influenced by adding information about the presence or absence of S3. In a multivariable model, the S3 added no independent prognostic information for 30-day (odds ratio 1.20; 95% CI 0.67 to 2.14) or 90-day events (odds ratio 1.22; 95% CI 0.78 to 1.90). CONCLUSION: In patients presenting with acute dyspnea, the acoustic cardiography S3 was specific for acute decompensated heart failure and affected physician confidence but did not improve diagnostic accuracy for acute decompensated heart failure, largely because of its low sensitivity. Further, the acoustic cardiography S3 provided no significant independent prognostic information
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Early Serial Echocardiographic and Ultrasonographic Findings in Critically Ill Patients With COVID-19.
BACKGROUND: Cardiac function of critically ill patients with COVID-19 generally has been reported from clinically obtained data. Echocardiographic deformation imaging can identify ventricular dysfunction missed by traditional echocardiographic assessment. RESEARCH QUESTION: What is the prevalence of ventricular dysfunction and what are its implications for the natural history of critical COVID-19? STUDY DESIGN AND METHODS: This is a multicenter prospective cohort of critically ill patients with COVID-19. We performed serial echocardiography and lower extremity vascular ultrasound on hospitalization days 1, 3, and 8. We defined left ventricular (LV) dysfunction as the absolute value of longitudinal strain of < 17% or left ventricle ejection fraction (LVEF) of < 50%. Primary clinical outcome was inpatient survival. RESULTS: We enrolled 110 patients. Thirty-nine (35.5%) died before hospital discharge. LV dysfunction was present at admission in 38 patients (34.5%) and in 21 patients (36.2%) on day 8 (P = .59). Median baseline LVEF was 62% (interquartile range [IQR], 52%-69%), whereas median absolute value of baseline LV strain was 16% (IQR, 14%-19%). Survivors and nonsurvivors did not differ statistically significantly with respect to day 1 LV strain (17.9% vs 14.4%; P = .12) or day 1 LVEF (60.5% vs 65%; P = .06). Nonsurvivors showed worse day 1 right ventricle (RV) strain than survivors (16.3% vs 21.2%; P = .04). INTERPRETATION: Among patients with critical COVID-19, LV and RV dysfunction is common, frequently identified only through deformation imaging, and early (day 1) RV dysfunction may be associated with clinical outcome
Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illnessResearch in context
Summary: Background: Multiple organ dysfunction syndrome (MODS) disproportionately drives morbidity and mortality among critically ill patients. However, we lack a comprehensive understanding of its pathobiology. Identification of genes associated with a persistent MODS trajectory may shed light on underlying biology and allow for accurate prediction of those at-risk. Methods: Secondary analyses of publicly available gene-expression datasets. Supervised machine learning (ML) was used to identify a parsimonious set of genes associated with a persistent MODS trajectory in a training set of pediatric septic shock. We optimized model parameters and tested risk-prediction capabilities in independent validation and test datasets, respectively. We compared model performance relative to an established gene-set predictive of sepsis mortality. Findings: Patients with a persistent MODS trajectory had 568 differentially expressed genes and characterized by a dysregulated innate immune response. Supervised ML identified 111 genes associated with the outcome of interest on repeated cross-validation, with an AUROC of 0.87 (95% CI: 0.85–0.88) in the training set. The optimized model, limited to 20 genes, achieved AUROCs ranging from 0.74 to 0.79 in the validation and test sets to predict those with persistent MODS, regardless of host age and cause of organ dysfunction. Our classifier demonstrated reproducibility in identifying those with persistent MODS in comparison with a published gene-set predictive of sepsis mortality. Interpretation: We demonstrate the utility of supervised ML driven identification of the genes associated with persistent MODS. Pending validation in enriched cohorts with a high burden of organ dysfunction, such an approach may inform targeted delivery of interventions among at-risk patients. Funding: H.R.W.′s NIH R35GM126943 award supported the work detailed in this manuscript. Upon his death, the award was transferred to M.N.A. M.R.A., N.S.P, and R.K were supported by NIH R21GM151703. R.K. was supported by R01GM139967
High-Sensitivity C-Reactive Protein is a Prognostic Biomarker of Six-Month Disability after Traumatic Brain Injury: Results from the TRACK-TBI Study
Systemic inflammation impacts outcome after traumatic brain injury (TBI), but most TBI biomarker studies have focused on brain-specific proteins. C-reactive protein (CRP) is a widely used biomarker of inflammation with potential as a prognostic biomarker after TBI. The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study prospectively enrolled TBI patients within 24 h of injury, as well as orthopedic injury and uninjured controls; biospecimens were collected at enrollment. A subset of hospitalized participants had blood collected on day 3, day 5, and 2 weeks. High-sensitivity CRP (hsCRP) and glial fibrillary acidic protein (GFAP) were measured. Receiver operating characteristic analysis was used to evaluate the prognostic ability of hsCRP for 6-month outcome, using the Glasgow Outcome Scale-Extended (GOSE). We included 1206 TBI subjects, 122 orthopedic trauma controls (OTCs), and 209 healthy controls (HCs). Longitudinal biomarker sampling was performed in 254 hospitalized TBI subjects and 19 OTCs. hsCRP rose between days 1 and 5 for TBI and OTC subjects, and fell by 2 weeks, but remained elevated compared with HCs (p < 0.001). Longitudinally, hsCRP was significantly higher in the first 2 weeks for subjects with death/severe disability (GOSE <5) compared with those with moderate disability/good recovery (GOSE ≥5); AUC was highest at 2 weeks (AUC = 0.892). Combining hsCRP and GFAP at 2 weeks produced AUC = 0.939 for prediction of disability. Serum hsCRP measured within 2 weeks of TBI is a prognostic biomarker for disability 6 months later. hsCRP may have utility as a biomarker of target engagement for anti-inflammatory therapies
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Life After Mild Traumatic Brain Injury: Widespread Structural Brain Changes Associated With Psychological Distress Revealed With Multimodal Magnetic Resonance Imaging
Traumatic brain injury (TBI) can alter brain structure and lead to onset of persistent neuropsychological symptoms. This study investigates the relationship between brain injury and psychological distress after mild TBI using multimodal magnetic resonance imaging.
A total of 89 patients with mild TBI from the TRACK-TBI (Transforming Research and Clinical Knowledge in Traumatic Brain Injury) pilot study were included. Subscales of the Brief Symptoms Inventory 18 for depression, anxiety, and somatization were used as outcome measures of psychological distress approximately 6 months after the traumatic event. Glasgow Coma Scale scores were used to evaluate recovery. Magnetic resonance imaging data were acquired within 2 weeks after injury. Perivascular spaces (PVSs) were segmented using an enhanced PVS segmentation method, and the volume fraction was calculated for the whole brain and white matter regions. Cortical thickness and gray matter structures volumes were calculated in FreeSurfer; diffusion imaging indices and multifiber tracts were extracted using the Quantitative Imaging Toolkit. The analysis was performed considering age, sex, intracranial volume, educational attainment, and improvement level upon discharge as covariates.
PVS fractions in the posterior cingulate, fusiform, and postcentral areas were found to be associated with somatization symptoms. Depression, anxiety, and somatization symptoms were associated with the cortical thickness of the frontal-opercularis and occipital pole, putamen and amygdala volumes, and corticospinal tract and superior thalamic radiation. Analyses were also performed on the two hemispheres separately to explore lateralization.
This study shows how PVS, cortical, and microstructural changes can predict the onset of depression, anxiety, and somatization symptoms in patients with mild TBI
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The Temporal Relationship of Mental Health Problems and Functional Limitations following mTBI: A TRACK-TBI and TED Study
Mental health problems, such as depression and anxiety, are often associated with functional limitations after traumatic brain injury (TBI), prompting researchers to explore which of these TBI-related sequelae tends to precede the other. Past studies among patients with injuries ranging in severity have predominantly reported that functional impairments predict subsequent psychological concerns, rather than the other way around; however, it remains unclear whether this directionality holds for individuals with mild TBI (mTBI). The present study utilized a cross-lagged panel design within a structural equation modeling analytical framework to explore the longitudinal relationships of symptoms of depression and anxiety to functional status among 717 adult mTBI patients, with assessments occurring at 2 weeks and 3 months post-injury. Symptoms of both depression and anxiety significantly predicted subsequent functional limitations (λs = -0.21 and -0.25), whereas the reverse effects were nonsignificant (λs = -0.05 and -0.03); thus, psychological concerns appeared to function as a precursor to functional impairment. This pattern was particularly pronounced among patients with normal head computed tomography (CT) results; however, results were less clear cut among those subjects whose injuries were accompanied by intracranial abnormalities detected on CT imaging, suggesting the possibility of a more reciprocal relationship in the case of CT-positive mTBI. These results may serve to partially explain the incidence of persistent functional limitations observed among subsets of mTBI patients in past studies. Findings likewise highlight the importance of assessment and treatment for mental health problems after mTBI as an important factor to promote psychological well-being and functional recovery