Machine Learning in Antibody Diagnostics for Inflammatory Bowel Disease Subtype Classification.

Antibody testing in inflammatory bowel disease (IBD) can add to diagnostic accuracy of the main subtypes Crohn's disease (CD) and ulcerative colitis (UC). Whether modern modeling techniques such as supervised and unsupervised machine learning are of value for finer distinction of subtypes such as IBD-unclassified (IBD-U) is not known. We determined the antibody profile of 100 adult IBD patients from the Swiss IBD cohort study with known subtype (50 CD, 50 UC) as well as of 76 IBD-U patients. We included ASCA IgG and IgA, p-ANCA, MPO- and PR3-ANCA, and xANCA measurements for computing different antibody panels as well as machine learning models. The AUC of an optimized antibody panel was 85% (95%CI, 78-92%) to distinguish CD from UC patients. The antibody profile of IBD-U patients was closely related to UC. No specific antibody profile was predictive for IBD-U nor for re-classification. The panel diagnostic was in favor of UC reclassification prediction with a correct assignment rate of 69.2-73.1% depending on the cut-off applied. Supervised machine learning could not distinguish between CD, UC, and IBD-U. More so, unsupervised machine learning suggested only two distinct clusters as a likely number of IBD subtypes. Antibodies in IBD are supportive in confirming clinical determined subtypes CD and UC but have limited capacity to predict IBD-U and reclassification during follow-up. In terms of antibody profiles, IBD-U is not a distinct subtype of IBD.

Prognostic models in COVID-19 infection that predict severity: a systematic review.

Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

Extending outbreak investigation with machine learning and graph theory: Benefits of new tools with application to a nosocomial outbreak of a multidrug-resistant organism.

OBJECTIVE: From January 1, 2018, until July 31, 2020, our hospital network experienced an outbreak of vancomycin-resistant enterococci (VRE). The goal of our study was to improve existing processes by applying machine-learning and graph-theoretical methods to a nosocomial outbreak investigation. METHODS: We assembled medical records generated during the first 2 years of the outbreak period (January 2018 through December 2019). We identified risk factors for VRE colonization using standard statistical methods, and we extended these with a decision-tree machine-learning approach. We then elicited possible transmission pathways by detecting commonalities between VRE cases using a graph theoretical network analysis approach. RESULTS: We compared 560 VRE patients to 86,684 controls. Logistic models revealed predictors of VRE colonization as age (aOR, 1.4 (per 10 years), with 95% confidence interval [CI], 1.3-1.5; P < .001), ICU admission during stay (aOR, 1.5; 95% CI, 1.2-1.9; P < .001), Charlson comorbidity score (aOR, 1.1; 95% CI, 1.1-1.2; P < .001), the number of different prescribed antibiotics (aOR, 1.6; 95% CI, 1.5-1.7; P < .001), and the number of rooms the patient stayed in during their hospitalization(s) (aOR, 1.1; 95% CI, 1.1-1.2; P < .001). The decision-tree machine-learning method confirmed these findings. Graph network analysis established 3 main pathways by which the VRE cases were connected: healthcare personnel, medical devices, and patient rooms. CONCLUSIONS: We identified risk factors for being a VRE carrier, along with 3 important links with VRE (healthcare personnel, medical devices, patient rooms). Data science is likely to provide a better understanding of outbreaks, but interpretations require data maturity, and potential confounding factors must be considered.

Urine Flow Cytometry Parameter Cannot Safely Predict Contamination of Urine-A Cohort Study of a Swiss Emergency Department Using Machine Learning Techniques.

BACKGROUND: Urine flow cytometry (UFC) analyses urine samples and determines parameter counts. We aimed to predict different types of urine culture growth, including mixed growth indicating urine culture contamination. METHODS: A retrospective cohort study (07/2017-09/2020) was performed on pairs of urine samples and urine cultures obtained from adult emergency department patients. The dataset was split into a training (75%) and validation set (25%). Statistical analysis was performed using a machine learning approach with extreme gradient boosting to predict urine culture growth types (i.e., negative, positive, and mixed) using UFC parameters obtained by UF-4000, sex, and age. RESULTS: In total, 3835 urine samples were included. Detection of squamous epithelial cells, bacteria, and leukocytes by UFC were associated with the different types of culture growth. We achieved a prediction accuracy of 80% in the three-class approach. Of the n = 126 mixed cultures in the validation set, 11.1% were correctly predicted; positive and negative cultures were correctly predicted in 74.0% and 96.3%. CONCLUSIONS: Significant bacterial growth can be safely ruled out using UFC parameters. However, positive urine culture growth (rule in) or even mixed culture growth (suggesting contamination) cannot be adequately predicted using UFC parameters alone. Squamous epithelial cells are associated with mixed culture growth.

The association between nurse staffing and inpatient mortality: A shift-level retrospective longitudinal study.

BACKGROUND: Worldwide, hospitals face pressure to reduce costs. Some respond by working with a reduced number of nurses or less qualified nursing staff. OBJECTIVE: This study aims at examining the relationship between mortality and patient exposure to shifts with low or high nurse staffing. METHODS: This longitudinal study used routine shift-, unit-, and patient-level data for three years (2015-2017) from one Swiss university hospital. Data from 55 units, 79,893 adult inpatients and 3646 nurses (2670 registered nurses, 438 licensed practical nurses, and 538 unlicensed and administrative personnel) were analyzed. After developing a staffing model to identify high- and low-staffed shifts, we fitted logistic regression models to explore associations between nurse staffing and mortality. RESULTS: Exposure to shifts with high levels of registered nurses had lower odds of mortality by 8.7% [odds ratio 0.91 95% CI 0.89-0.93]. Conversely, low staffing was associated with higher odds of mortality by 10% [odds ratio 1.10 95% CI 1.07-1.13]. The associations between mortality and staffing by other groups was less clear. For example, both high and low staffing of unlicensed and administrative personnel were associated with higher mortality, respectively 1.03 [95% CI 1.01-1.04] and 1.04 [95% CI 1.03-1.06]. DISCUSSION AND IMPLICATIONS: This patient-level longitudinal study suggests a relationship between registered nurses staffing levels and mortality. Higher levels of registered nurses positively impact patient outcome (i.e. lower odds of mortality) and lower levels negatively (i.e. higher odds of mortality). Contributions of the three other groups to patient safety is unclear from these results. Therefore, substitution of either group for registered nurses is not recommended.

Effects of Freezing and Thawing Procedures on Selected Clinical Chemistry Parameters in Plasma.

Introduction: Measurements from frozen sample collections are important key indicators in clinical studies. It is a prime concern of biobanks and laboratories to minimize preanalytical bias and variance through standardization. In this study, we aimed at assessing the effects of different freezing and thawing conditions on the reproducibility of medical routine parameters from frozen samples. Materials and Methods: In total, 12 pooled samples were generated from leftover lithium heparinized plasma samples from clinical routine testing. Aliquots of the pools were frozen using three freezing methods (in carton box at -80°C, flash freezing in liquid nitrogen, and controlled-rate freezing [CRF]) and stored at -80°C. After 3 days, samples were thawed using two methods (30 minutes at room temperature or water bath at 25°C for 3 minutes). Ten clinical chemistry laboratory parameters were measured before (baseline) and after freeze-thaw treatment: total calcium, potassium, sodium, alanine aminotransferase, lactate dehydrogenase (LDH), lipase, uric acid, albumin, c-reactive protein (CRP), and total protein. We evaluated the influence of the different preanalytical treatments on the test results and compared each condition with nonfrozen baseline measurements. Results: We found no significant differences between freezing methods for all tested parameters. Only LDH was significantly affected by thawing with fast-rate thawing being closer to baseline than slow-rate thawing. Potassium, LDH, lipase, uric acid, albumin, and CRP values were significantly changed after freezing and thawing compared with unfrozen samples. The least prominent changes compared with unfrozen baseline measurements were obtained when a CRF protocol of the local biobank and fast thawing was applied. However, the observed changes between baseline and frozen samples were smaller than the measurement uncertainty for 9 of the 10 parameters. Discussion: Changes introduced through freezing-thawing were small and not of clinical importance. A slight statistically based preference toward results from slow CRF and fast thawing of plasma being closest to unfrozen samples could be supported.

Longitudinal Study of the Variation in Patient Turnover and Patient-to-Nurse Ratio: Descriptive Analysis of a Swiss University Hospital.

BACKGROUND: Variations in patient demand increase the challenge of balancing high-quality nursing skill mixes against budgetary constraints. Developing staffing guidelines that allow high-quality care at minimal cost requires first exploring the dynamic changes in nursing workload over the course of a day. OBJECTIVE: Accordingly, this longitudinal study analyzed nursing care supply and demand in 30-minute increments over a period of 3 years. We assessed 5 care factors: patient count (care demand), nurse count (care supply), the patient-to-nurse ratio for each nurse group, extreme supply-demand mismatches, and patient turnover (ie, number of admissions, discharges, and transfers). METHODS: Our retrospective analysis of data from the Inselspital University Hospital Bern, Switzerland included all inpatients and nurses working in their units from January 1, 2015 to December 31, 2017. Two data sources were used. The nurse staffing system (tacs) provided information about nurses and all the care they provided to patients, their working time, and admission, discharge, and transfer dates and times. The medical discharge data included patient demographics, further admission and discharge details, and diagnoses. Based on several identifiers, these two data sources were linked. RESULTS: Our final dataset included more than 58 million data points for 128,484 patients and 4633 nurses across 70 units. Compared with patient turnover, fluctuations in the number of nurses were less pronounced. The differences mainly coincided with shifts (night, morning, evening). While the percentage of shifts with extreme staffing fluctuations ranged from fewer than 3% (mornings) to 30% (evenings and nights), the percentage within "normal" ranges ranged from fewer than 50% to more than 80%. Patient turnover occurred throughout the measurement period but was lowest at night. CONCLUSIONS: Based on measurements of patient-to-nurse ratio and patient turnover at 30-minute intervals, our findings indicate that the patient count, which varies considerably throughout the day, is the key driver of changes in the patient-to-nurse ratio. This demand-side variability challenges the supply-side mandate to provide safe and reliable care. Detecting and describing patterns in variability such as these are key to appropriate staffing planning. This descriptive analysis was a first step towards identifying time-related variables to be considered for a predictive nurse staffing model.

Renal Function-Adjusted D-Dimer Levels in Critically Ill Patients With Suspected Thromboembolism.

OBJECTIVES: Diagnosing thromboembolic disease typically includes D-dimer testing and use of clinical scores in patients with low to intermediate pretest probability. However, renal dysfunction is often observed in patients with thromboembolic disease and was previously shown to be associated with increased D-dimer levels. We seek to validate previously suggested estimated glomerular filtration rate-adjusted D-dimer cutoff levels. Furthermore, we strive to explore whether the type of renal dysfunction affects estimated glomerular filtration rate-adjusted D-dimer test characteristics. DESIGN: Single-center retrospective data analysis from electronic healthcare records of all emergency department patients admitted for suspected thromboembolic disease. SETTING: Tertiary care academic hospital. SUBJECTS: Exclusion criteria were as follows: age less than 16 years old, patients with active bleeding, and/or incomplete records. INTERVENTIONS: Test characteristics of previously suggested that estimated glomerular filtration rate-adjusted D-dimer cutoff levels (> 333 µg/L [estimated glomerular filtration rate, > 60 mL/min/1.73 m], > 1,306 µg/L [30-60 mL/min/1.73 m], and > 1,663 µg/L [< 30 mL/min/1.73 m]) were validated and compared with the conventional D-dimer cutoff level of 500 µg/L. MAIN RESULTS: A total of 14,477 patients were included in the final analysis, with 467 patients (3.5%) diagnosed with thromboembolic disease. Renal dysfunction was observed in 1,364 (9.4%) of the total population. When adjusted D-dimer levels were applied, test characteristics remained stable: negative predictive value (> 99%), sensitivity (91.2% vs 93.4%), and specificity (42.7% vs 50.7%) when compared with the conventional D-dimer cutoff level to rule out thromboembolic disease (< 500 µg/L). Comparable characteristics were also observed when adjusted D-dimer cutoff levels were applied in patients with acute kidney injury (negative predictive value, 98.8%; sensitivity, 95.8%; specificity, 39.2%) and/or "acute on chronic" renal dysfunction (negative predictive value, 98.0%; sensitivity, 92.9%; specificity, 48.5%). CONCLUSIONS: D-Dimer cutoff levels adjusted for renal dysfunction appear feasible and safe assessing thromboembolic disease in critically ill patients. Furthermore, adjusted D-dimer cutoff levels seem reliable in patients with acute kidney injury and "acute on chronic" renal dysfunction. In patients with estimated glomerular filtration rate less than 60 mL/min/1.73 m, the false-positive rate can be reduced when estimated glomerular filtration rate-adjusted D-dimer cutoff levels are applied.

Rapid Centrifugation in the Routine Hemostasis Laboratory.

BACKGROUND: The use of short and uniform centrifugation schemes contributes significantly to the successful automation of laboratory procedures. It is however unclear if this is applicable to the hemostasis laboratory. OBJECTIVES: This article assesses the accuracy of measurements obtained with a rapid, high-speed centrifugation scheme in a large set of hemostasis tests, covering the full spectrum of values obtained in clinical practice, and using meaningful statistical measures. METHODS: Two citrated plasma samples were obtained from consecutive patients of a tertiary hospital with suspected abnormal hemostasis tests and processed with two centrifugation schemes in parallel: 1,500 × g for 10 minutes and 3,137 × g for 7 minutes. The following tests were conducted: prothrombin time (n = 125), international normalized ratio (n = 146), activated partial thromboplastin time (n = 119), thrombin time (n = 105), fibrinogen (n = 125), factor (F)II (n = 69), FV (n = 64), FVII (n = 64), FX (n = 67), FVIII (n = 55), FIX (n = 37), FXI (n = 35), and FXIII (n = 20), D-dimer (n = 34), antithrombin (n = 31), anti-Xa activity (n = 30), von Willebrand antigen (n = 25), and von Willebrand activity (VWF:GPIbM; n = 27). RESULTS: A wide range of results were obtained in all tests. Spearman's rank correlation coefficient was at least 0.95 for all tests except FV, FIX, and FXI. The coverage probability π at a given deviation index κ of 15% was above 0.9 for all tests except FV, FVII, FX, FVIII, FIX, FXI, and VWF:GPIbM, suggesting a lack of agreement. CONCLUSION: Our results suggest that high-speed centrifugation is applicable to the majority of routine hemostasis parameters. The coverage probability was more sensitive than Spearman's rank correlation to detect disagreement among centrifugation schemes.

Diagnosis of Urinary Tract Infections by Urine Flow Cytometry: Adjusted Cut-Off Values in Different Clinical Presentations.

BACKGROUND: Bacterium and leucocyte counts in urine can be measured by urine flow cytometry (UFC). They are used to predict significant bacterial growth in urine culture and to diagnose infections of the urinary tract. However, little information is available on appropriate UFC cut-off values for bacterium and leucocyte counts in specific clinical presentations. OBJECTIVE: To develop, validate, and evaluate adapted cut-off values that result in a high negative predictive value for significant bacterial growth in urine culture in common clinical presentation subgroups. METHODS: This is a single center, retrospective, observational study with data from patients of the emergency department of Bern University Hospital, Switzerland, with suspected infections of the urinary tract. The patients presented with different symptoms, and urine culture and urine flow cytometry were performed. For different clinical presentations, the patients were grouped by (i) age (>65 years), (ii) sex, (iii) clinical symptoms (e.g., fever or dysuria), and (iv) comorbidities such as diabetes and immunosuppression. For each group, cut-off values were developed, validated, and analyzed using different strategies, i.e., linear discriminant analysis (LDA) and Youden's index, and were compared with known cut-offs and cut-offs optimized for sensitivity. RESULTS: 613 patients were included in the study. Significant bacterial growth in urine culture depended on clinical presentation and ranged from 32.3% in male patients to 61.5% in patients with urinary frequency. In all clinical presentations, the predictive accuracy of UFC leucocyte and UFC bacterium counts was good for significant bacterial growth in urine culture (AUC ≥ 0.88). The adapted LDA95 equations did not exhibit consistently high sensitivity. However, the in-house cut-offs (test positive if UFC leucocytes > 17/µL or UFC bacteria > 125/µL) were highly sensitive (>90%). In female, younger, and dysuric patients, even higher cut-offs for UFC leucocytes (169/µL, 169/µL, and 205/µL) exhibited high sensitivity. Specificity was insufficient (<0.9) for all tested cut-offs. CONCLUSIONS: For various clinical presentations, significant bacterial growth in urine culture can be excluded if flow cytometry measurements give a bacterial count of ≤125/µL or a leucocyte count of ≤17/µL. In female patients, dysuric patients, and patients younger than ≤65 years, the leucocyte cut-off can be increased to 170/µL.

The links of hepcidin and erythropoietin in the interplay of inflammation and iron deficiency in a large observational study of rheumatoid arthritis.

Anaemia affects quality of life and radiographic outcome in rheumatoid arthritis (RA). In a cross-sectional study with 779 patients, we assessed the prognostic potential of the major haematopoietic regulators, hepcidin and erythropoietin, comparing their serum concentrations with respect to different anaemia types, inflammatory activity, anti-cytokine-specific treatment effects and iron deficiency (ID) indices. The results showed that clinical disease activity was more closely associated with haemoglobin levels than with anti-tumour necrosis factor-alpha or interleukin 6 receptor effects. In ID, hepcidin was suppressed, independently of inflammation. Erythropoietin levels were inappropriately low in relation to the degree of anaemia, but, in contrast to low haemoglobin, not directly associated with joint damage progression. Hepcidin and erythropoietin levels are intimately connected with inflammation and ID. Interventional studies on these important targets are already in progress.

Bootstrap-based testing approaches for the assessment of the diagnostic accuracy of biomarkers subject to a limit of detection.

Assessment of the diagnostic accuracy of biomarkers through receiver operating characteristic curve analysis frequently involves a limit of detection imposed by the laboratory analytical system precision. As a consequence, measurements below a certain level are undetectable and ignoring these is known to lead to negatively biased estimates of the area under the receiver operating characteristic curve. In this article, we introduce two receiver operating characteristic curve-based parametric approaches that tackle the issue of correct assessment of diagnostic markers in the presence of a limit of detection. Proposed approaches are simulation-based utilising bootstrap methodology. Non-parametric alternatives that are naively used in the literature do not solve the inherent problem of limit of detection values which are treated as censored observations. However, the latter seems to perform adequately well in our simulation study. Nonparametric bootstrap was consistently used throughout, while other bootstrap alternatives performed similarly in our pilot simulation study. The simulation study involves the comparison of parametric and non-parametric options described here versus alternative strategies that are routinely used in the literature. We apply all methods to a study-setting resembling a chemical quasi-standard situation, where compound tumour biomarkers were searched within a multi-variable set of measurements to discriminate between two groups, namely colorectal cancer and controls. We focus in the assessment of glutamine and methionine.

PR3-ANCA and panel diagnostics in pediatric inflammatory bowel disease to distinguish ulcerative colitis from Crohn's disease.

BACKGROUND: Accurate classification of patients with inflammatory bowel disease into the subtypes ulcerative colitis (UC) and Crohn's disease (CD) is still a challenge, but important for therapy and prognosis. OBJECTIVES: To evaluate the diagnostic utility of anti-neutrophil cytoplasmic antibodies specific for proteinase-3 (PR3-ANCA) for ulcerative colitis (UC) and the value of an antibody panel incorporating PR3-ANCA to differentiate between Crohn's disease (CD) and UC. STUDY DESIGN: In this cohort study, 122 pediatric and adolescent individuals were retrospectively included (61 IBD patients of two clinical centers, 61 non-IBD controls). All subjects had a comprehensive antibody profile done from stored sera taken close to time of diagnosis. By employing quasi-exhaustive logistic regression the best discriminative model for UC and CD,subjects was determined in a training cohort and confirmed in a validation cohort. RESULTS: PR3-ANCA was specifically associated with UC (odds ratio (OR), 17.6; 95% confidence interval (CI); 3.6, 87); P < .001). A four antibody-panel including PR3-ANCA had an AUC of 90.81% (95%CI; 81.93, 99.69) to distinguish between UC and CD in the training cohort. In a smaller external validation cohort, the AUC was 84.13% (95%CI; 64.21, 100) for accurate diagnosis of CD and UC. CONCLUSION: PR3-ANCA is highly specific for UC. The differentiating capability of a panel, which contains PR3-ANCA and weighs broadly available antibodies, is superior and utilization of the panel can support accurate classification in the work-up of pediatric and adolescent patients with IBD patients.

The effect of a previous created distal arteriovenous-fistula on radial bone DXA measurements in prevalent renal transplant recipients.

BACKGROUND: Accelerated bone loss occurs rapidly following renal transplantation due to intensive immunosuppression and persistent hyperparathyroidism. In renal transplant recipients (RTRs) due to the hyperparathyroidism the non-dominant forearm is often utilized as a peripheral measurement site for dual-energy x-ray absorptiometry (DXA) measurements. The forearm is also the site of previous created distal arteriovenous fistulas (AVF). Although AVF remain patent long after successful transplantation, there are no data available concerning their impact on radial bone DXA measurements. METHODS: In this cross-sectional study we performed DXA in 40 RTRs with preexisting distal AVF (RTRs-AVF) to assess areal bone mineral density (aBMD) differences between both forearms (three areas) and compared our findings to patients with chronic kidney disease (CKD, n = 40), pre-emptive RTRs (RTRs-pre, n = 15) and healthy volunteers (n = 20). In addition, we assessed relevant demographic, biochemical and clinical aspects. RESULTS: We found a marked radial asymmetry between the forearms in RTRs with preexisting AVF. The radial aBMD at the distal AVF forearm was lower compared to the contralateral forearm, resulting in significant differences for all three areas analyzed: the Rad-1/3: median (interquartile range) in g/cm2, Rad-1/3: 0.760 (0.641-0.804) vs. 0.742 (0.642, 0.794), p = 0.016; ultradistal radius, Rad-UD: 0.433 (0.392-0.507) vs. 0.420 (0.356, 0.475), p = 0.004; and total radius, Rad-total: 0.603 (0.518, 0.655) vs. 0.599 (0.504, 0.642), p = 0.001). No such asymmetries were observed in any other groups. Lower aBMD in AVF forearm subregions resulted in misclassification of osteoporosis. CONCLUSIONS: In renal transplant recipients, a previously created distal fistula may exert a negative impact on the radial bone leading to significant site-to-site aBMD differences, which can result in diagnostic misclassifications.

The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter.

OBJECTIVE: Patients presenting with suspected urinary tract infection are common in every day emergency practice. Urine flow cytometry has replaced microscopic urine evaluation in many emergency departments, but interpretation of the results remains challenging. The aim of this study was to develop and validate tools that predict urine culture growth out of urine flow cytometry parameter. METHODS: This retrospective study included all adult patients that presented in a large emergency department between January and July 2017 with a suspected urinary tract infection and had a urine flow cytometry as well as a urine culture obtained. The objective was to identify urine flow cytometry parameters that reliably predict urine culture growth and mixed flora growth. The data set was split into a training (70%) and a validation set (30%) and different decision-making approaches were developed and validated. RESULTS: Relevant urine culture growth (respectively mixed flora growth) was found in 40.2% (7.2% respectively) of the 613 patients included. The number of leukocytes and bacteria in flow cytometry were highly associated with urine culture growth, but mixed flora growth could not be sufficiently predicted from the urine flow cytometry parameters. A decision tree, predictive value figures, a nomogram, and a cut-off table to predict urine culture growth from bacteria and leukocyte count were developed, validated and compared. CONCLUSIONS: Urine flow cytometry parameters are insufficient to predict mixed flora growth. However, the prediction of urine culture growth based on bacteria and leukocyte count is highly accurate and the developed tools should be used as part of the decision-making process of ordering a urine culture or starting an antibiotic therapy if a urogenital infection is suspected.

Influence of centrifugation conditions on the results of 77 routine clinical chemistry analytes using standard vacuum blood collection tubes and the new BD-Barricor tubes.

INTRODUCTION: Although centrifugation is performed in almost every blood sample, recommendations on duration and g-force are heterogeneous and mostly based on expert opinions. In order to unify this step in a fully automated laboratory, we aimed to evaluate different centrifugation settings and their influence on the results of routine clinical chemistry analytes. MATERIALS AND METHODS: We collected blood from 41 healthy volunteers into BD Vacutainer PST II-heparin-gel- (LiHepGel), BD Vacutainer SST II-serum-, and BD Vacutainer Barricor heparin-tubes with a mechanical separator (LiHepBar). Tubes were centrifuged at 2000xg for 10 minutes and 3000xg for 7 and 5 minutes, respectively. Subsequently 60 and 21 clinical chemistry analytes were measured in plasma and serum samples, respectively, using a Roche COBAS instrument. RESULTS: High sensitive Troponin T, pregnancy-associated plasma protein A, ß human chorionic gonadotropin and rheumatoid factor had to be excluded from statistical evaluation as many of the respective results were below the measuring range. Except of free haemoglobin (fHb) measurements, no analyte result was altered by the use of shorter centrifugation times at higher g-forces. Comparing LiHepBar to LiHepGel tubes at different centrifugation setting, we found higher lactate-dehydrogenase (LD) (P = 0.003 to < 0.001) and lower bicarbonate values (P = 0.049 to 0.008) in the latter. CONCLUSIONS: Serum and heparin samples may be centrifuged at higher speed (3000xg) for a shorter amount of time (5 minutes) without alteration of the analytes tested in this study. When using LiHepBar tubes for blood collection, a separate LD reference value might be needed.

Utility of quick sepsis-related organ failure assessment (qSOFA) to predict outcome in patients with pneumonia.

BACKGROUND: Despite on-going advances in medical treatment, the burden of disease of pneumonia remains high. We aimed to determine the association of the qSOFA score with in-hospital mortality, length of hospitalisation, and admission to the intensive care unit (ICU) in patients with pneumonia. Further, in a subgroup analysis, the outcomes were compared for qSOFA in comparison to other risk scores, including the CURB-65 and SIRS scores. METHODS: In a retrospective analysis, admission data from the ED of the Bern University Hospital, Switzerland, were screened to identify patients admitted for pneumonia. In addition to clinical characteristics, qSOFA and CURB-65 scores and SIRS criteria were assessed and evaluated with respect to the defined study outcomes. RESULTS: 527 patients (median age 66 IQR 50-76) were included in this study. The overall in-hospital mortality was 13.3% (n = 70); 22.0% (n = 116) were transferred to the ICU. The median length of hospitalisation was 7 days (IQR 4-12). In comparison to qSOFA-negative patients, qSOFA-positive patients had increased odds ratios for in-hospital mortality (OR 2.6, 95%:1.4, 4.7, p<0.001) and ICU admission (3.5, 95% CI: 2.0. 5.8, p<0.001) and an increased length of stay (p<0.001). For ICU admission, the specificity of qSOPA-positivity (≥2) was 82.1% and sensitivity 43.0%. For in-hospital mortality, the specificity of qSOPA-positivity (≤2) was 88.9% and sensitivity 24.4%. In the subgroup analysis (n = 366). The area under the receiver operating curve for ICU admission was higher for qSOFA than for the CURB-65 score (p = 0.013). The evaluated scores did not differ significantly in their prognostication of in-hospital mortality (p>0.05). CONCLUSIONS: The qSOFA score is associated with in-hospital mortality, ICU admission and length of hospitalisation in ED patients with pneumonia. Subgroup analysis revealed that qSOFA is superior to CURB-65 in respect to prognostication of ICU admission.

Association of the Intestinal Microbiome with the Development of Neovascular Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is the most frequent cause of blindness in the elderly. There is evidence that nutrition, inflammation and genetic risk factors play an important role in the development of AMD. Recent studies suggest that the composition of the intestinal microbiome is associated with metabolic diseases through modulation of inflammation and host metabolism. To investigate whether compositional and functional alterations of the intestinal microbiome are associated with AMD, we sequenced the gut metagenomes of patients with AMD and controls. The genera Anaerotruncus and Oscillibacter as well as Ruminococcus torques and Eubacterium ventriosum were relatively enriched in patients with AMD, whereas Bacteroides eggerthii was enriched in controls. Patient's intestinal microbiomes were enriched in genes of the L-alanine fermentation, glutamate degradation and arginine biosynthesis pathways and decreased in genes of the fatty acid elongation pathway. These findings suggest that modifications in the intestinal microbiome are associated with AMD, inferring that this common sight threatening disease may be targeted by microbiome-altering interventions.

Targeted and global pharmacometabolomics in everolimus-based immunosuppression: association of co-medication and lysophosphatidylcholines with dose requirement.

INTRODUCTION: The immunosuppressive therapy with everolimus (ERL) after heart transplantation is characterized by a narrow therapeutic window and a substantial variability in dose requirement. Factors explaining this variability are largely unknown. OBJECTIVES: Our aim was to evaluate factors affecting ERL metabolism and to identify novel metabolites associated with the individual ERL dose requirement to elucidate mechanisms underlying ERL dose response variability. METHOD: We used liquid chromatography coupled with mass spectrometry for quantification of ERL metabolites in 41 heart transplant patients and evaluated the effect of clinical and genetic factors on ERL pharmacokinetics. Non-targeted plasma metabolic profiling by ultra-performance liquid chromatography and high resolution quadrupole-time-of-flight mass spectrometry was used to identify novel metabolites associated with ERL dose requirement. RESULTS: The determination of ERL metabolites revealed differences in metabolite patterns that were independent from clinical or genetic factors. Whereas higher ERL dose requirement was associated with co-administration of sodium-mycophenolic acid and the CYP3A5 expressor genotype, lower dose was required for patients receiving vitamin K antagonists. Global metabolic profiling revealed several novel metabolites associated with ERL dose requirement. One of them was identified as lysophosphatidylcholine (lysoPC) (16:0/0:0). Subsequent targeted analysis revealed that high levels of several lysoPCs were significantly associated with higher ERL dose requirement. CONCLUSION: For the first time, this study describes distinct ERL metabolite patterns in heart transplant patients and detected potentially new drug-drug interactions. The global metabolic profiling facilitated the discovery of novel metabolites associated with ERL dose requirement that might represent new clinically valuable biomarkers to guide ERL therapy.

High sensitive cardiac troponin T: Testing the test.

BACKGROUND: High sensitive cardiac troponin T (hs-TnT) found its way into everyday clinical routine to diagnose acute myocardial infarction (AMI). However, its levels vary considerably based on the underlying pathophysiology of the patients. Hence we sought to test the applicability of the currently only available hs-TnT assay (Roche Diagnostics, Switzerland) to diagnose acute myocardial infarction. METHODS AND PATIENTS: Retrospectively, we analyzed the hs-TnT results of 1573 patients admitted to a level A university hospital emergency department. Overall 323 patients had an acute cardiac event defined as Non-ST Elevated Myocardial Infarction (NSTEMI) and 286 patients had a ST-Elevated Myocardial Infarction (STEMI). 964 patients served as controls, consisting of patients with other cardiac and non-cardiac morbidity. RESULTS: The sensitivity of hs-TnT for detecting an acute cardiac event was more than 92% overall. The specificity varied around 35% depending on the respective patient cohort. ROC curve analysis of the initial hs-TnT results showed that the AUC in total cardiac events (STEMI and NSTEMI) was 0.81. Detailed analysis resulted in an AUC of 0.79 in NSTEMI and 0.84 in STEMI patients detected via the initial hs-TnT. We further tested the ESC algorithm for detecting NSTEMI and obtained a sensitivity of about 83%, while 43% of all non-NSTEMIs are classified as NSTEMIs. CONCLUSION: We show that the specificity of hs-TnT for AMI is very low and conclude that the current assay including its delta values represents myocardial damage of any origin. This damage alone does not substantiate an AMI diagnosis even when international algorithms are applied.