Uncertainty analysis of chest X-ray lung height measurements and size matching for lung transplantation

Lung transplantation; Chest X-ray; PrecisionTrasplante de pulmón; Radiografía de tórax; PrecisiónTrasplantament de pulmó; Radiografia de tòrax; PrecisióBackground: Errors in measuring chest X-ray (CXR) lung heights could contribute to the occurrence of size-mismatched lung transplant procedures. Methods: We first used Bland-Altman analysis for repeated measures to evaluate contributors to measurement error of chest X-ray lung height. We then applied error propagation theory to assess the impact of measurement error on size matching for lung transplantation. Results: A total 387 chest X-rays from twenty-five donors and twenty-five recipients were measured by two raters. Individual standard deviation for lung height differences were independent of age, sex, donor vs. recipient, diagnostic group and race/ethnicity and all were pooled for analysis. Bias between raters was 0.27 cm (±0.03) and 0.22 cm (±0.06) for the right and left lung respectively. Within subject variability was the biggest contributor to error in measurement, 2.76 cm (±0.06) and 2.78 cm (±0.2) for the right and left lung height. A height difference of 4.4 cm or more (95% CI: ±4.2, ±4.6 cm) between the donor and the recipient right lung height has to be accepted to ensure matching for at least 95% of patients with the same true lung height. This difference decreases to ±1.1 cm (95% CI: ±0.9, ±1.3 cm) when the average from all available chest X-rays is used. The probability of matching a donor and a recipient decreases with increasing true lung height difference. Conclusions: Individual chest X-ray lung heights are imprecise for the purpose of size matching in lung transplantation. Averaging chest X-rays lung heights reduced uncertainty.This research was supported by the Washington University Institute of Clinical and Translational Sciences Grant UL1TR002345 from the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH). The content is solely the responsibility of the authors and does not necessarily represent the official view of the NIH

Antimicrobial stewardship for sepsis in the intensive care unit: Survey of critical care and infectious diseases physicians

OBJECTIVE: To evaluate the attitudes of infectious diseases (ID) and critical care physicians toward antimicrobial stewardship in the intensive care unit (ICU). DESIGN: Anonymous, cross-sectional, web-based surveys. SETTING: Surveys were completed in March-November 2017, and data were analyzed from December 2017 to December 2019. PARTICIPANTS: ID and critical care fellows and attending physicians. METHODS: We included 10 demographic and 17 newly developed, 5-point, Likert-scaled items measuring attitudes toward ICU antimicrobial stewardship and transdisciplinary collaboration. Exploratory principal components analysis (PCA) was used for data reduction. Multivariable linear regression models explored demographic and attitudinal variables. RESULTS: Of 372 respondents, 315 physicians had complete data (72% attendings, 28% fellows; 63% ID specialists, and 37% critical care specialists). Our PCA yielded a 3-item factor measuring which specialty should assume ICU antimicrobial stewardship (Cronbach standardized α = 0.71; higher scores indicate that ID physicians should be stewards), and a 4-item factor measuring value of ICU transdisciplinary collaborations (α = 0.62; higher scores indicate higher value). In regression models, ID physicians (vs critical care physicians), placed higher value on ICU collaborations and expressed discomfort with uncertain diagnoses. These factors were independently associated with stronger agreement that ID physicians should be ICU antimicrobial stewards. The following factors were independently associated with higher value of transdisciplinary collaboration: female sex, less discomfort with uncertain diagnoses, and stronger agreement with ID physicians as ICU antimicrobial stewards. CONCLUSIONS: ID and critical care physicians endorsed their own group for antimicrobial stewardship, but both groups placed high value on ICU transdisciplinary collaborations. Physicians who were more uncomfortable with uncertain diagnoses reported preference for ID physicians to coordinate ICU antimicrobial stewardship; however, physicians who were less uncomfortable with uncertain diagnoses placed greater value on ICU collaborations

Assessment of antibodies in the upper and lower human respiratory tract at steady state and after respiratory viral infection

OBJECTIVES: There is an increasing appreciation for the need to study mucosal antibody responses in humans. Our aim was to determine the utility of different types of samples from the human respiratory tract, specifically nasopharyngeal (NP) swabs obtained for diagnostic purposes and bronchoalveolar lavage (BAL) obtained in outpatient and inpatient settings. METHODS: We analysed antibody levels in plasma and NP swabs from 67 individuals with acute influenza as well as plasma and BAL from individuals undergoing bronchoscopy, including five control subjects as well as seven moderately and seven severely ill subjects with a respiratory viral infection. Levels of α2-macroglobulin were determined in BAL and plasma to assess plasma exudation. RESULTS: IgG and IgA were readily detectable in BAL and NP swabs, albeit at different ratios, while IgM levels were low. The total amount of antibody recovered from NP swabs varied greatly between study participants. Accordingly, the levels of influenza HA-specific antibodies varied, and individuals with lower amounts of total Ig in NP swabs had undetectable levels of HA-specific Ig. Similarly, the total amount of antibody recovered from BAL varied between study participants. However, severely ill patients showed evidence of increased plasma exudation, which may confound analysis of their BAL samples for mucosal antibodies. CONCLUSION: Nasopharyngeal swabs collected for diagnostic purposes may have utility in assessing antibodies from the human nasal mucosa, but variability in sampling should be accounted for. BAL samples can be utilised to study antibodies from the lower respiratory tract, but the possibility of plasma exudation should be excluded

Multi-drug resistance, inappropriate initial antibiotic therapy and mortality in Gram-negative severe sepsis and septic shock: A retrospective cohort study

INTRODUCTION: The impact of in vitro resistance on initially appropriate antibiotic therapy (IAAT) remains unclear. We elucidated the relationship between non-IAAT and mortality, and between IAAT and multi-drug resistance (MDR) in sepsis due to Gram-negative bacteremia (GNS). METHODS: We conducted a single-center retrospective cohort study of adult intensive care unit patients with bacteremia and severe sepsis/septic shock caused by a gram-negative (GN) organism. We identified the following MDR pathogens: MDR P. aeruginosa, extended spectrum beta-lactamase and carbapenemase-producing organisms. IAAT was defined as exposure within 24 hours of infection onset to antibiotics active against identified pathogens based on in vitro susceptibility testing. We derived logistic regression models to examine a) predictors of hospital mortality and b) impact of MDR on non-IAAT. Proportions are presented for categorical variables, and median values with interquartile ranges (IQR) for continuous. RESULTS: Out of 1,064 patients with GNS, 351 (29.2%) did not survive hospitalization. Non-survivors were older (66.5 (55, 73.5) versus 63 (53, 72) years, P = 0.036), sicker (Acute Physiology and Chronic Health Evaluation II (19 (15, 25) versus 16 (12, 19), P <0.001), and more likely to be on pressors (odds ratio (OR) 2.79, 95% confidence interval (CI) 2.12 to 3.68), mechanically ventilated (OR 3.06, 95% CI 2.29 to 4.10) have MDR (10.0% versus 4.0%, P <0.001) and receive non-IAAT (43.4% versus 14.6%, P <0.001). In a logistic regression model, non-IAAT was an independent predictor of hospital mortality (adjusted OR 3.87, 95% CI 2.77 to 5.41). In a separate model, MDR was strongly associated with the receipt of non-IAAT (adjusted OR 13.05, 95% CI 7.00 to 24.31). CONCLUSIONS: MDR, an important determinant of non-IAAT, is associated with a three-fold increase in the risk of hospital mortality. Given the paucity of therapies to cover GN MDRs, prevention and development of new agents are critical

A pragmatic machine learning model to predict carbapenem resistance

Infection caused by carbapenem-resistant (CR) organisms is a rising problem in the United States. While the risk factors for antibiotic resistance are well known, there remains a large need for the early identification of antibiotic-resistant infections. Using machine learning (ML), we sought to develop a prediction model for carbapenem resistance. All patients \u3e18 years of age admitted to a tertiary-care academic medical center between 1 January 2012 and 10 October 2017 with ≥1 bacterial culture were eligible for inclusion. All demographic, medication, vital sign, procedure, laboratory, and culture/sensitivity data were extracted from the electronic health record. Organisms were considered CR if a single isolate was reported as intermediate or resistant. Patients with CR and non-CR organisms were temporally matched to maintain the positive/negative case ratio. Extreme gradient boosting was used for model development. In total, 68,472 patients met inclusion criteria, with 1,088 patients identified as having CR organisms. Sixty-seven features were used for predictive modeling. The most important features were number of prior antibiotic days, recent central venous catheter placement, and inpatient surgery. After model training, the area under the receiver operating characteristic curve was 0.846. The sensitivity of the model was 30%, with a positive predictive value (PPV) of 30% and a negative predictive value of 99%. Using readily available clinical data, we were able to create a ML model capable of predicting CR infections at the time of culture collection with a high PPV