Left Ventricular Diastolic Dysfunction across Levels of Kidney Function: A Cross-Sectional Study Based on Routine Clinical Practice Data.

Left ventricular diastolic dysfunction (LVDD) commonly coexists with kidney dysfunction. In this study, we investigated the presence of abnormalities in echocardiography parameters indicative of LVDD across stages of kidney function. Methods: We selected patients who visited a university hospital and had a serum creatinine and echocardiography reported in their medical records. Participants were categorized based on their kidney function: normal (estimated glomerular filtration rate [eGFR] ≥ 90 mL/min/1.73 m2), mildly decreased (eGFR: 60-90), moderately decreased (eGFR: 30-60), and severely decreased (eGFR < 30). The relationship between kidney function and echocardiography parameters was examined using logistic and linear regressions. Results: Among 4022 patients (age: 66.5 years [SD: 12.1], 41% women), 26%, 50%, 20%, and 4% had a normal, mildly, moderately, and severely decreased kidney function, respectively. Compared to patients with normal kidney function, patients with mildly decreased kidney function had higher odds for an abnormal E/e' ratio (OR: 1.51 [95% CI: 1.13, 2.02]). Patients with moderately decreased kidney function presented a higher risk of abnormal E/e' (OR: 2.90 [95% CI: 2.08, 4.04]), LAVI (OR: 1.62 [95% CI: 1.13, 2.33]), TR velocity (OR: 2.31 [95% CI: 1.49, 3.57]), and LVMI (OR: 1.70 [95% CI: 1.31, 2.20]), while patients with severely decreased kidney function had higher odds for abnormal E/e' (OR: 2.95 [95% CI: 1.68, 5.17]) and LVMI > 95 g/m2 in women or >115 g/m2 in men (OR: 2.07 [95% CI: 1.27, 3.38]). The linear regression showed a significant inverse association between eGFR and echocardiography parameters, meaning that with worse kidney function, the parameters for LVDD worsened as well. Conclusions: Abnormal echocardiography parameters of LVDD were present even in patients with mildly decreased kidney function. As the kidney function worsened, there was a gradual increase in the risk of abnormal parameters of LVDD.

Improving acute kidney injury alerts in tertiary care by linking primary care data: An observational cohort using routine care data.

Objective: Acute kidney injury (AKI) is easily missed and underdiagnosed in routine clinical care. Timely AKI management is important to decrease morbidity and mortality risks. We recently implemented an AKI e-alert at the University Medical Center Utrecht, comparing plasma creatinine concentrations with historical creatinine baselines, thereby identifying patients with AKI. This alert is limited to data from tertiary care, and primary care data can increase diagnostic accuracy for AKI. We assessed the added value of linking primary care data to tertiary care data, in terms of timely diagnosis or excluding AKI. Methods: With plasma creatinine tests for 84,984 emergency department (ED) visits, we applied the Kidney Disease Improving Global Outcome guidelines in both tertiary care-only data and linked data and compared AKI cases. Results: Using linked data, the presence of AKI could be evaluated in an additional 7886 ED visits. Sex- and age-stratified analyses identified the largest added value for women (an increase of 4095 possible diagnoses) and patients ≥60 years (an increase of 5190 possible diagnoses). We observed 398 additional visits where AKI was diagnosed, as well as 185 cases where AKI could be excluded. We observed no overall decrease in time between baseline and AKI diagnosis (28.4 days vs. 28.0 days). For cases where AKI was diagnosed in both data sets, we observed a decrease of 2.8 days after linkage, indicating a timelier diagnosis of AKI. Conclusions: Combining primary and tertiary care data improves AKI diagnostic accuracy in routine clinical care and enables timelier AKI diagnosis.

Use of antibiotics in the early COVID-19 pandemic in Poland, the Netherlands and Spain, from erraticism to (more) logic.

INTRODUCTION: In the Spring of 2020, the world was hit with unparalleled impact by the coronavirus pandemic. Antibiotics were widely used, even without good rationale. The aim of our study was to compare the use of antibiotics in patients with confirmed COVID-19 from three hospitals across Europe (Poland, the Netherlands and Spain) between two subsequent periods in the early days of the pandemic. METHOD: We analysed data (antibiotics used and variation in the use of antibiotics, patients, admission and disease-related characteristics) from 300 patients admitted in three hospitals (University Hospital in Cracow, University Medical Center in Utrecht and Vall d'Hebron University Hospital in Barcelona) with confirmed infection of SARS-CoV-2 during Q1 2020 and Q4 2020. RESULTS: There was ample variation in terms of patient mix and outcomes across the 3 hospitals. The majority of patients (225 out of 300) in all 3 hospitals received at least 1 antibiotic during the hospitalisation period. A minority of patients (68 out of 300) had their bacterial test results positive during their hospitalisation period. Throughout the 2 study periods, third-generation cephalosporins (ceftriaxone in 170 out of 300 patients) emerged as the most commonly used class of antibiotics. There was an apparent shift towards more rational utilisation of antibiotics, in all three hospitals. CONCLUSIONS: Our study shows that during the early stage of COVID-19 pandemic in 2020, antibiotics were frequently used in three European teaching hospitals despite the relatively low incidence of microbiologically confirmed bacterial infections. While in the early days of the COVID-19 pandemic antibiotic prescribing was full of trial and error, we could also confirm a learning curve over time.

Relationship of neutrophil-to-lymphocyte ratio, in addition to C-reactive protein, with cardiovascular events in patients with type 2 diabetes.

AIM: To quantify the relationship of neutrophil-to-lymphocyte ratio (NLR) with cardiovascular events and all-cause mortality in patients with type 2 diabetes (T2D), independent of C-reactive protein (CRP). METHODS: Patients with T2D from the UCC-SMART-cohort were studied using multivariable-adjusted Cox regression. The relationship of NLR and CRP with vascular events (cerebrovascular events, myocardial infarction and vascular death) and all-cause mortality was quantified. RESULTS: During 10,833 person-years, 232 vascular events and 302 deaths occurred in 1,239 patients with T2D. Risk of vascular events and all-cause mortality increased per standard deviation (SD) in NLR (hazard ratio (HR) 1.27; 95 % confidence interval (CI):1.11-1.46) and 1.15; 95 % CI:1.02-1.30) after adjustment for CRP. CRP was not associated with vascular events after adjustment for NLR, (HR per SD 1.03; 95 % CI: 0.90-1.19), but was associated with all-cause mortality (HR per SD 1.18; 95 % CI: 1.04-1.33). Notably, NLR was related to vascular events in patients with CRP < 2 mg/L (HR per unit 1.45; 95 % CI: 1.19-1.77). CONCLUSION: In patients with T2D, NLR is related to higher risk of CVD and all-cause mortality, independently from CRP. NLR is related to CVD even when CRP is low, indicating that NLR is a marker of CVD-risk in addition to CRP. Both NLR and CRP are independently related to all-cause mortality in T2D patients.

A Wolf in Sheep's Clothing: Reuse of Routinely Obtained Laboratory Data in Research.

Electronic health records (EHRs) contain valuable data for reuse in science, quality evaluations, and clinical decision support. Because routinely obtained laboratory data are abundantly present, often numeric, generated by certified laboratories, and stored in a structured way, one may assume that they are immediately fit for (re)use in research. However, behind each test result lies an extensive context of choices and considerations, made by both humans and machines, that introduces hidden patterns in the data. If they are unaware, researchers reusing routine laboratory data may eventually draw incorrect conclusions. In this paper, after discussing health care system characteristics on both the macro and micro level, we introduce the reader to hidden aspects of generating structured routine laboratory data in 4 steps (ordering, preanalysis, analysis, and postanalysis) and explain how each of these steps may interfere with the reuse of routine laboratory data. As researchers reusing these data, we underline the importance of domain knowledge of the health care professional, laboratory specialist, data manager, and patient to turn routine laboratory data into meaningful data sets to help obtain relevant insights that create value for clinical care.

Axial light loss of monocytes as a readily available prognostic biomarker in patients with suspected infection at the emergency department.

OBJECTIVES: To evaluate the prognostic value of the coefficient of variance of axial light loss of monocytes (cv-ALL of monocytes) for adverse clinical outcomes in patients suspected of infection in the emergency department (ED). METHODS: We performed an observational, retrospective monocenter study including all medical patients ≥18 years admitted to the ED between September 2016 and June 2019 with suspected infection. Adverse clinical outcomes included 30-day mortality and ICU/MCU admission <3 days after presentation. We determined the additional value of monocyte cv-ALL and compared to frequently used clinical prediction scores (SIRS, qSOFA, MEWS). Next, we developed a clinical model with routinely available parameters at the ED, including cv-ALL of monocytes. RESULTS: A total of 3526 of patients were included. The OR for cv-ALL of monocytes alone was 2.21 (1.98-2.47) for 30-day mortality and 2.07 (1.86-2.29) for ICU/MCU admission <3 days after ED presentation. When cv-ALL of monocytes was combined with a clinical score, the prognostic accuracy increased significantly for all tested scores (SIRS, qSOFA, MEWS). The maximum AUC for a model with routinely available parameters at the ED was 0.81 to predict 30-day mortality and 0.81 for ICU/MCU admission. CONCLUSIONS: Cv-ALL of monocytes is a readily available biomarker that is useful as prognostic marker to predict 30-day mortality. Furthermore, it can be used to improve routine prediction of adverse clinical outcomes at the ED. CLINICAL TRIAL REGISTRATION: Registered in the Dutch Trial Register (NTR) und number 6916.

Preventing unnecessary imaging in patients suspect of coronary artery disease through machine learning of electronic health records.

Aims: With the ageing European population, the incidence of coronary artery disease (CAD) is expected to rise. This will likely result in an increased imaging use. Symptom recognition can be complicated, as symptoms caused by CAD can be atypical, particularly in women. Early CAD exclusion may help to optimize use of diagnostic resources and thus improve the sustainability of the healthcare system. To develop sex-stratified algorithms, trained on routinely available electronic health records (EHRs), raw electrocardiograms, and haematology data to exclude CAD in patients upfront. Methods and results: We trained XGBoost algorithms on data from patients from the Utrecht Patient-Oriented Database, who underwent coronary computed tomography angiography (CCTA), and/or stress cardiac magnetic resonance (CMR) imaging, or stress single-photon emission computerized tomography (SPECT) in the UMC Utrecht. Outcomes were extracted from radiology reports. We aimed to maximize negative predictive value (NPV) to minimize the false negative risk with acceptable specificity. Of 6808 CCTA patients (31% female), 1029 females (48%) and 1908 males (45%) had no diagnosis of CAD. Of 3053 CMR/SPECT patients (45% female), 650 females (47%) and 881 males (48%) had no diagnosis of CAD. On the train and test set, the CCTA models achieved NPVs and specificities of 0.95 and 0.19 (females) and 0.96 and 0.09 (males). The CMR/SPECT models achieved NPVs and specificities of 0.75 and 0.041 (females) and 0.92 and 0.026 (males). Conclusion: Coronary artery disease can be excluded from EHRs with high NPV. Our study demonstrates new possibilities to reduce unnecessary imaging in women and men suspected of CAD.

Data mining to retrieve smoking status from electronic health records in general practice.

Aims: Optimize and assess the performance of an existing data mining algorithm for smoking status from hospital electronic health records (EHRs) in general practice EHRs. Methods and results: We optimized an existing algorithm in a training set containing all clinical notes from 498 individuals (75 712 contact moments) from the Julius General Practitioners' Network (JGPN). Each moment was classified as either 'current smoker', 'former smoker', 'never smoker', or 'no information'. As a reference, we manually reviewed EHRs. Algorithm performance was assessed in an independent test set (n = 494, 78 129 moments) using precision, recall, and F1-score. Test set algorithm performance for 'current smoker' was precision 79.7%, recall 78.3%, and F1-score 0.79. For former smoker, it was precision 73.8%, recall 64.0%, and F1-score 0.69. For never smoker, it was precision 92.0%, recall 74.9%, and F1-score 0.83. On a patient level, performance for ever smoker (current and former smoker combined) was precision 87.9%, recall 94.7%, and F1-score 0.91. For never smoker, it was 98.0, 82.0, and 0.89%, respectively. We found a more narrative writing style in general practice than in hospital EHRs. Conclusion: Data mining can successfully retrieve smoking status information from general practice clinical notes with a good performance for classifying ever and never smokers. Differences between general practice and hospital EHRs call for optimization of data mining algorithms when applied beyond a primary development setting.

Platelet count and indices as postpartum hemorrhage risk factors: a retrospective cohort study.

BACKGROUND: Severe postpartum hemorrhage (SPPH) is the leading cause of maternal mortality and morbidity worldwide. Platelet anomalies frequently occur during pregnancy. However, their role in the etiology of SPPH is largely unknown. OBJECTIVE: To study the relation between platelet parameters and SPPH. METHODS: This retrospective single-center cohort included deliveries between 2009 and 2017. SPPH was defined as ≥1000 ml blood loss within 24 h after delivery. Platelet parameters were measured within 72 h before delivery. Multiple imputation was performed for missing data. Odds ratios were adjusted (aORs) for maternal age, multiple gestation, macrosomia, induction of labor, preeclampsia, and hemolysis, elevated liver enzymes, and low platelets syndrome. RESULTS: A total of 23 205 deliveries were included. Of the 2402 (10.4%) women with thrombocytopenia (<150 × 109 /L), 10.3% developed SPPH, compared with 7.6% of women with a normal platelet count (aOR: 1.34, 95% CI: 1.14-1.59). Women with a platelet count of <50 × 109 /L were most at risk (aOR of 2.24 [1.01-4.94]) compared with the reference group with normal platelet counts; the aOR was 1.22 (0.77-1.93) for the 50-99 × 109 /L platelet count group and 1.31 (1.10-1.56) for the 100-149 × 109 /L platelet count group. Plateletcrit was associated with SPPH (aOR 1.15 [1.08-1.21] per 0.05% decrease), and, although rarely present, a platelet distribution width (PDW) ≥23% (n = 22) also increased the odds of SPPH (aOR 6.05 [2.29-16.20]). CONCLUSION: Different degrees of thrombocytopenia were independently associated with the occurrence of SPPH. Despite their relation to SPPH, plateletcrit and a PDW of ≥23% have limited additional value in addition to platelet count.

Switching TNFα inhibitors: Patterns and determinants.

The aim of this study was to assess switching patterns and determinants for switching in patients initiating TNFα inhibitor (TNFα-i) treatment. Patients were included who started TNFα-i treatment between July 1, 2012 and December 31, 2017, from three Dutch hospitals, and were diagnosed with rheumatic diseases (RD), inflammatory bowel disease (IBD), or psoriasis. Outcomes were switching, defined as initiating another biological; switching patterns including multiple switches until the end of follow-up; determinants for first switch, assessed using multivariate logistic regression. A total of 2228 patients were included (median age 43.3 years, 57% female), of which 52% (n = 1155) received TNFα-i for RD, 43% (n = 967) for IBD, and 5% (n = 106) for psoriasis. About 16.6% of RD patients, 14.5% of IBD patients, and 16.0% of psoriasis patients switched at least once, mainly to another TNFα-i. TNFα-i dose escalation (OR 13.78, 95% CI 1.40-135.0) and high-dose corticosteroids initiation (OR 3.62, 95% CI 1.10-12.15) were determinants for switching in RD patients. TNFα-i dose escalation (OR 8.22, 95% CI 3.76-17.93), immunomodulator initiation/dose escalation (OR 2.13, 95% CI 1.04-4.34), high-dose corticosteroids initiation (OR 6.91, 95% CI 2.81-17.01) and serum concentration measurement (OR 5.44, 95% CI 2.74-10.79) were determinants for switching in IBD patients. Switching biological treatment occurred in about one in six patients. RD patients with TNFα-i dose escalation and/or high-dose corticosteroids initiation were more likely to switch. IBD patients with TNFα-i or immunomodulator initiation/dose escalation, high-dose corticosteroids initiation or serum concentration measurement were more likely to switch. These findings might help clinicians anticipating switching in TNFα-i treatment.

Intra-Operative Hypotension is a Risk Factor for Post-operative Silent Brain Ischaemia in Patients With Pre-operative Hypertension Undergoing Carotid Endarterectomy.

OBJECTIVE: Intra-operative haemodynamic instability during carotid endarterectomy (CEA) has been associated with an increased risk of procedural stroke. Diffusion weighted imaging (DWI) lesions have been proposed as a surrogate marker for peri-operative silent cerebral ischaemia. This study aimed to investigate the relationship between peri-operative blood pressure (BP) and presence of post-operative DWI lesions in patients undergoing CEA. METHODS: A retrospective analysis was performed based on patients with symptomatic CEA included in the MRI substudy of the International Carotid Stenting Study. Relative intra-operative hypotension was defined as a decrease of intra-operative systolic BP ≥ 20% compared with pre-operative ('baseline') BP, absolute hypotension was defined as a drop in systolic BP < 80  mmHg. The primary endpoint was the presence of any new DWI lesions on post-operative MRI (DWI positive). The occurrence and duration of intra-operative hypotension was compared between DWI positive and DWI negative patients as was the magnitude of the difference between pre- and intra-operative BP. RESULTS: Fifty-five patients with symptomatic CEA were included, of whom eight were DWI positive. DWI positive patients had a significantly higher baseline systolic (186 ± 31 vs. 158 ± 27 mmHg, p = .011) and diastolic BP (95 ± 15 vs. 84 ± 13 mmHg, p = .046) compared with DWI negative patients. Other pre-operative characteristics did not differ. Relative intra-operative hypotension compared with baseline occurred in 53/55 patients (median duration 34 min; range 0-174). Duration of hypotension did not differ significantly between the groups (p = .088). Mean systolic intra-operative BP compared with baseline revealed a larger drop in BP (-37 ± 29 mmHg) in DWI positive compared with DWI negative patients (-14 ± 26 mmHg, p = .024). Absolute intra-operative systolic BP values did not differ between the groups. CONCLUSION: In this exploratory study, high pre-operative BP and a larger drop of intra-operative BP were associated with peri-procedural cerebral ischaemia as documented with DWI. These results call for confirmation in an adequately sized prospective study, as they suggest important consequences for peri-operative haemodynamic management in carotid revascularisation.

Persistent Inflammation, Immunosuppression and Catabolism Syndrome (PICS) after Polytrauma: A Rare Syndrome with Major Consequences.

Nowadays, more trauma patients develop chronic critical illness (CCI), a state characterized by prolonged intensive care. Some of these CCI patients have disproportional difficulties to recover and suffer from recurrent infections, a syndrome described as the persistent inflammation, immunosuppression and catabolism syndrome (PICS). A total of 78 trauma patients with an ICU stay of ≥14 days (CCI patients) between 2007 and 2017 were retrospectively included. Within this group, PICS patients were identified through two ways: (1) their clinical course (≥3 infectious complications) and (2) by laboratory markers suggested in the literature (C-reactive protein (CRP) and lymphocytes), both in combination with evidence of increased catabolism. The incidence of PICS was 4.7 per 1000 multitrauma patients. The sensitivity and specificity of the laboratory markers was 44% and 73%, respectively. PICS patients had a longer hospital stay (median 83 vs. 40, p < 0.001) and required significantly more surgical interventions (median 13 vs. 3, p = 0.003) than other CCI patients. Thirteen PICS patients developed sepsis (72%) and 12 (67%) were readmitted at least once due to an infection. In conclusion, patients who develop PICS experience recurrent infectious complications that lead to prolonged hospitalization, many surgical procedures and frequent readmissions. Therefore, PICS forms a substantial burden on the patient and the hospital, despite its low incidence.

A pan-inflammatory microRNA-cluster is associated with orbital non-Hodgkin lymphoma and idiopathic orbital inflammation.

Non-Hodgkin orbital lymphoma (NHOL) and idiopathic orbital inflammation (IOI) are common orbital conditions with largely unknown pathophysiology that can be difficult to diagnose. In this study we aim to identify serum miRNAs associated with NHOL and IOI. We performed OpenArray® miRNA profiling in 33 patients and controls. Differentially expressed miRNAs were technically validated across technology platforms and replicated in an additional cohort of 32 patients and controls. We identified and independently validated a serum miRNA profile of NHOL that was remarkably similar to IOI and characterized by an increased expression of a cluster of eight miRNAs. Pathway enrichment analysis indicated that the miRNA-cluster is associated with immune-mediated pathways, which we supported by demonstrating the elevated expression of this cluster in serum of patients with other inflammatory conditions. The cluster contained miR-148a, a key driver of B-cell tolerance, and miR-365 that correlated with serum IgG and IgM concentrations. In addition, miR-29a and miR-223 were associated with blood lymphocyte and neutrophil populations, respectively. NHOL and IOI are characterized by an abnormal serum miRNA-cluster associated with immune pathway activation and linked to B cell and neutrophil dysfunction.

Data mining information from electronic health records produced high yield and accuracy for current smoking status.

OBJECTIVES: Researchers are increasingly using routine clinical data for care evaluations and feedback to patients and clinicians. The quality of these evaluations depends on the quality and completeness of the input data. STUDY DESIGN AND SETTING: We assessed the performance of an electronic health record (EHR)-based data mining algorithm, using the example of the smoking status in a cardiovascular population. As a reference standard, we used the questionnaire from the Utrecht Cardiovascular Cohort (UCC). To assess diagnostic accuracy, we calculated sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). RESULTS: We analyzed 1,661 patients included in the UCC to January 18, 2019. Of those, 14% (n = 238) had missing information on smoking status in the UCC questionnaire. Data mining provided information on smoking status in 99% of the 1,661 participants. Diagnostic accuracy for current smoking was sensitivity 88%, specificity 92%, NPV 98%, and PPV 63%. From false positives, 85% reported they had quit smoking at the time of the UCC. CONCLUSION: Data mining showed great potential in retrieving information on smoking (a near complete yield). Its diagnostic performance is good for negative smoking statuses. The implications of misclassification with data mining are dependent on the application of the data.

Reticulated Platelets as Predictor of Myocardial Injury and 30 Day Mortality After Non-cardiac Surgery.

OBJECTIVE: A pre-operative marker for identification of patients at risk of peri-operative adverse events and 30 day mortality might be the percentage of young, reticulated platelets (pRP). This study aimed to determine the predictive value of pre-operative pRP on post-operative myocardial injury (PMI) and 30 day mortality, in patients aged ≥ 60 years undergoing moderate to high risk non-cardiac surgery. METHODS: The incidence of PMI (troponin I > 0.06 µg/L) and 30 day mortality was compared for patients with normal and high pRP (≥2.82%) obtained from The Utrecht Patient Orientated Database. The predictive pRP value was assessed using logistic regression. A prediction model for PMI or 30 day mortality with known risk factors was compared with a model including increased pRP using the area under the receiving operator characteristics curve (AUROC). RESULTS: In total, 26.5% (607/2289) patients showed pre-operative increased pRP. Increased pRP was associated with more PMI and 30 day mortality compared with normal pRP (36.1% vs. 28.3%, p < .001 and 8.6% vs. 3.6%, p < .001). The median pRP was higher in patients suffering PMI and 30 day mortality compared with not (2.21 [IQR: 1.57-3.11] vs. 2.07 [IQR: 1.52-1.78], p = .002, and 2.63 [IQR: 1.76-4.15] vs. 2.09 [IQR: 1.52-3.98], p < .001). pRP was independently related to PMI (OR: 1.28 [95% CI: 1.04-1.59], p = .02) and 30 day mortality (OR: 2.35 [95% CI: 1.56-3.55], p < .001). Adding increased pRP to the predictive model of PMI or 30 day mortality did not increase the AUROC 0.71 vs. 0.72, and 0.80 vs. 0.81. CONCLUSION: In patients undergoing major non-cardiac surgery, increased pre-operative pRP is related to 30 day mortality and PMI.

Association of low testosterone with changes in non-cardiovascular biomarkers in adult men.

Testosterone has effects on many organs and systems. The purpose of this study was to test the hypothesis that low testosterone is associated with changes in various non-cardiovascular biomarkers in men older than 40 who were tested for possible hypogonadism. We extracted data from 9939 outpatient men who were over 40 years old (median age 56) and who also had concurrent laboratory measurements of total testosterone and one or more biomarkers of interest: estradiol, uric acid, prostate-specific antigen (PSA), sex-hormone binding globulin (SHBG), luteinizing hormone, creatinine, bone alkaline phosphatase (BAP), creatine kinase, hemoglobin A1c, and 25-hydroxy-vitamin D, and body mass index (BMI). In a smaller exploratory study of 19 otherwise healthy men presenting for evaluation of possible hypogonadism, pre-albumin (a.k.a.transthyretin, a marker of anabolism) and testosterone were measured. Men with lower levels of testosterone had significantly (p < 0.001) lower mean levels of PSA, SHBG, luteinizing hormone, and estradiol. Overall, men with low levels of testosterone also had significantly (p < 0.001) higher mean levels of LDH and BAP, but these associations varied between men who were younger or older than 56 years. There was a moderate but statistically significant positive correlation (r = 0.63, p < 0.05) between testosterone levels and pre-albumin. These results confirm our hypothesis that testosterone deficiency is associated with a broad range of systemic changes demonstrable in hormonal and non-hormonal serum assays in men over 40 years old being tested for possible hypogonadism.

A Human(e) Factor in Clinical Decision Support Systems.

The overwhelming amount, production speed, multidimensionality, and potential value of data currently available-often simplified and referred to as big data -exceed the limits of understanding of the human brain. At the same time, developments in data analytics and computational power provide the opportunity to obtain new insights and transfer data-provided added value to clinical practice in real time. What is the role of the health care professional in collaboration with the data scientist in the changing landscape of modern care? We discuss how health care professionals should provide expert knowledge in each of the stages of clinical decision support design: data level, algorithm level, and decision support level. Including various ethical considerations, we advocate for health care professionals to responsibly initiate and guide interprofessional teams, including patients, and embrace novel analytic technologies to translate big data into patient benefit driven by human(e) values.

Treatment to Target Using Recombinant Interleukin-1 Receptor Antagonist as First-Line Monotherapy in New-Onset Systemic Juvenile Idiopathic Arthritis: Results From a Five-Year Follow-Up Study.

OBJECTIVE: Systemic juvenile idiopathic arthritis (JIA) is a multifactorial autoinflammatory disease with a historically poor prognosis. With current treatment regimens, approximately half of patients still experience active disease after 1 year of therapy. This study was undertaken to evaluate a treat-to-target approach using recombinant interleukin-1 receptor antagonist (rIL-1Ra; anakinra) as first-line monotherapy to achieve early inactive disease and prevent damage. METHODS: In this single-center, prospective study, patients with new-onset systemic JIA with an unsatisfactory response to nonsteroidal antiinflammatory drugs received rIL-1Ra monotherapy according to a treat-to-target strategy. Patients with an incomplete response to 2 mg/kg rIL-1Ra subsequently received 4 mg/kg rIL-1Ra or additional prednisolone, or switched to alternative therapy. For patients in whom inactive disease was achieved, rIL-1Ra was tapered after 3 months and subsequently stopped. RESULTS: Forty-two patients, including 12 who had no arthritis at disease onset, were followed up for a median of 5.8 years. The median time to achieve inactive disease was 33 days. At 1 year, 76% had inactive disease, and 52% had inactive disease while not receiving medication. High neutrophil counts at baseline and a complete response after 1 month of rIL-1Ra were highly associated with inactive disease at 1 year. After 5 years of follow-up, 96% of the patients included had inactive disease, and 75% had inactive disease while not receiving medication. Articular or extraarticular damage was reported in <5%, and only 33% of the patients received glucocorticoids. Treatment with rIL-1Ra was equally effective in systemic JIA patients without arthritis at disease onset. CONCLUSION: Treatment to target, starting with first-line, short-course monotherapy with rIL-1Ra, is a highly efficacious strategy to induce and sustain inactive disease and to prevent disease- and glucocorticoid-related damage in systemic JIA.

A single preoperative blood test predicts postoperative sepsis and pneumonia after coronary bypass or open aneurysm surgery.

BACKGROUND: Major surgery comes with a high risk for postoperative inflammatory complications. Preoperative risk scores predict mortality risk but fail to identify patients at risk for complications following cardiovascular surgery. We therefore assessed the value of preoperative red cell distribution width (RDW) as a predictor for pneumonia and sepsis after cardiovascular surgery and studied the relation of RDW with hematopoietic tissue activity. METHODS: RDW is an easily accessible, yet seldomly used parameter from routine haematology measurements. RDW was extracted from the Utrecht Patient Orientated Database (UPOD) for preoperative measurements in patients undergoing open abdominal aortic anuerysm repair (AAA)(N = 136) or coronary artery bypass grafting (CABG)(N = 2193). The cohorts were stratified in tertiles to assess effects over the different groups. Generalized Linear Models were used to determine associations between RDW and postoperative inflammatory complications. Hematopoietic tissue activity was scored using fluor-18-(18F)-deoxyglucose positron emission tomography and associated with RDW using linear regression models. RESULTS: In total, 43(31.6%) and 73 patients (3.3%) suffered from inflammatory complications after AAA-repair or CABG, respectively; the majority being pneumonia in both cohorts. Postoperative inflammatory outcome incidence increased from 19.6% in the lowest to 48.9% in the highest RDW tertile with a corresponding risk ratio (RR) of 2.35 ([95%CI:1.08-5.14] P = 0.032) in AAA patients. In the CABG cohort, the incidence of postoperative inflammatory outcomes increased from 1.8% to 5.3% with an adjusted RR of 1.95 ([95%CI:1.02-3.75] P = 0.044) for the highest RDW tertile compared with the lowest RDW tertile. FDG-PET scans showed associations of RDW with tissue activity in the spleen (B = 0.517 [P = 0.001]) and the lumbar bone marrow (B = 0.480 [P = 0.004]). CONCLUSION: Elevated RDW associates with increased risk for postoperative inflammatory complications and hematopoietic tissue activity. RDW likely reflects chronic low-grade inflammation and should be considered to identify patients at risk for postoperative inflammatory complications following cardiovascular surgery.