EP-1811: Accuracy of dose calculations on CBCT scans of lung cancer patients using a vendor-specific approach

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Time courses of urinary creatinine excretion, measured creatinine clearance and estimated glomerular filtration rate over 30 days of ICU admission

Purpose: Baseline urinary creatinine excretion (UCE) is associated with ICU outcome, but its time course is not known. Materials and methods: We determined changes in UCE, plasma creatinine, measured creatinine clearance (mCC) and estimated glomerular filtration (eGFR) in patients with an ICU-stay 30d without acute kidney injury stage 3. The Cockcroft-Gault, MDRD (modification of diet in renal disease) and CKD-EPI (chronic kidney disease epidemiology collaboration) equations were used. Results: In 248 patients with 5143 UCEs hospital mortality was 24%. Over 30d, UCE absolutely decreased in male survivors and non-survivors and female survivors and nonsurvivors by 0.19, 0.16, 0.10 and 0.05 mmol/d/d (all P < 0.001). Relative decreases in UCE were similar in all four groups: 1.3, 1.4, 1.2 and 0.9%/d respectively. Over 30d, mCC remained unchanged, but eGFR rose by 31% (CKD-EPI) and 73% (MDRD) and creatinine clearance estimated by Cockcroft-Gault by 59% (all P < 0.001). Conclusions: Over 1 month of ICU stay, UCE declined by 1%/d which may correspond to an equivalent decline in muscle mass. These rates of UCE decrease were similar in survivors, non-survivors, males and females underscoring the intransigent nature of this process. In contrast to measured creatinine clearance, estimates of eGFR progressively rose during ICU stay. (c) 2020 Published by Elsevier Inc

Machine learning in infection management using routine electronic health records:tools, techniques, and reporting of future technologies

Background: Machine learning (ML) is increasingly being used in many areas of health care. Its use in infection management is catching up as identified in a recent review in this journal. We present here a complementary review to this work. Objectives: To support clinicians and researchers in navigating through the methodological aspects of ML approaches in the field of infection management. Sources: A Medline search was performed with the keywords artificial intelligence, machine learning, infection∗, and infectious disease∗ for the years 2014–2019. Studies using routinely available electronic hospital record data from an inpatient setting with a focus on bacterial and fungal infections were included. Content: Fifty-two studies were included and divided into six groups based on their focus. These studies covered detection/prediction of sepsis (n = 19), hospital-acquired infections (n = 11), surgical site infections and other postoperative infections (n = 11), microbiological test results (n = 4), infections in general (n = 2), musculoskeletal infections (n = 2), and other topics (urinary tract infections, deep fungal infections, antimicrobial prescriptions; n = 1 each). In total, 35 different ML techniques were used. Logistic regression was applied in 18 studies followed by random forest, support vector machines, and artificial neural networks in 18, 12, and seven studies, respectively. Overall, the studies were very heterogeneous in their approach and their reporting. Detailed information on data handling and software code was often missing. Validation on new datasets and/or in other institutions was rarely done. Clinical studies on the impact of ML in infection management were lacking. Implications: Promising approaches for ML use in infectious diseases were identified. But building trust in these new technologies will require improved reporting. Explainability and interpretability of the models used were rarely addressed and should be further explored. Independent model validation and clinical studies evaluating the added value of ML approaches are needed

Predicting keratinocyte carcinoma in patients with actinic keratosis: development and internal validation of a multivariable risk-prediction model

Background: Patients with actinic keratosis (AK) are at increased risk for developing keratinocyte carcinoma (KC) but predictive factors and their risk rates are unknown. Objectives: To develop and internally validate a prediction model to calculate the absolute risk of a first KC in patients with AK. Methods: The risk-prediction model was based on the prospective population-based Rotterdam Study cohort. We hereto analysed the data of participants with at least one AK lesion at cohort baseline using a multivariable Cox proportional hazards model and included 13 a priori defined candidate predictor variables considering phenotypic, genetic and lifestyle risk factors. KCs were identified by linkage of the data with the Dutch Pathology Registry. Results: Of the 1169 AK participants at baseline, 176 (15·1%) developed a KC after a median follow-up of 1·8 years. The final model with significant predictors was obtained after backward stepwise selection and comprised the presence of four to nine AKs [hazard ratio (HR) 1·68, 95% confidence interval (CI) 1·17–2·42], 10 or more AKs (HR 2·44, 95% CI 1·65–3·61), AK localization on the upper extremities (HR 0·75, 95% CI 0·52–1·08) or elsewhere except the head (HR 1·40, 95% CI 0·98–2·01) and coffee consumption (HR 0·92, 95% CI 0·84–1·01). Evaluat

Use of infrared thermography in the detection of superficial phlebitis in adult intensive care unit patients:A prospective single-center observational study

Common methods to detect phlebitis may not be sufficient for patients in the intensive care unit (ICU). The goal of this study was to investigate the feasibility of infrared (IR) thermography to objectively detect phlebitis in adult ICU patients. We included a total of 128 adult ICU-patients in a pilot and subsequent validation study. Median [interquartile range] age was 62 [54-71] years and 88 (69%) patients were male. Severity of phlebitis was scored using the visual infusion phlebitis (VIP)-score, ranging from 0 (no phlebitis) to 5 (thrombophlebitis). The temperature difference (ΔT) between the insertion site and a proximal reference point was measured with IR thermography. In 78 (34%) catheters early phlebitis and onset of moderate phlebitis was observed (VIP-score of 1-3). In both the pilot and the validation study groups ΔT was significantly higher when the VIP-score was ≥1 compared to a VIP-score of 0 (p<0.01 and p<0.001, respectively). Multivariate analysis identified ΔT (p<0.001) and peripheral venous catheter (PVC) dwell time (p = 0.001) as significantly associated with phlebitis. IR thermography may be a promising technique to identify phlebitis in the ICU. An increased ΔT as determined with thermography may be a risk factor for phlebitis

Association between lifetime smoking and cutaneous squamous cell carcinoma:A 2-sample Mendelian randomization study

Background/Purpose: Cutaneous squamous cell carcinoma (cSCC) is one of the most common malignancies worldwide. While several environmental risk factors for cSCC are well established, there is conflicting evidence on cigarette smoking (and its potential causal effect) and cSCC risk. Furthermore, it is unclear if these potential associations represent causal, modifiable risk factors for cSCC development. This study aims to assess the nature of the associations between cigarette smoking traits (smoking initiation, amount smoked, and lifetime smoking exposure) and cSCC risk using two-sample Mendelian randomization analyses. Methods: Genetic instruments, based on common genetic variants associated with cigarette smoking traits (P &lt; 5 × 10−8), were derived from published genome-wide association studies (GWASs). For cSCC, we used GWAS summary statistics from the Kaiser Permanente GERA cohort (7701 cSCC cases and 60,167 controls; all non-Hispanic Whites). Results: We found modest evidence that genetically determined lifetime smoking was associated with cSCC (inverse-variance weighted method: OR[95% CI] = 1.47[1.09-1.98]; P =.012), suggesting it may be a causal risk factor for cSCC. We did not detect any evidence of association between genetically determined smoking initiation or amount smoked and cSCC risk. Conclusion: Study findings highlight the importance of smoking prevention and may support risk-stratified cSCC screening strategies based on carcinogen exposure and other genetic and clinical information.</p

Duplication of the great saphenous vein: A definition problem and implications for therapy

BACKGROUND: In the literature there is a range from 1% to 20% of duplication (up to 20%) of the great saphenous vein (GSV) reported, because there is a lack of an accurate definition of the GSV and objective parameters for an anatomical identification. OBJECTIVE: To investigate the frequency of true duplications of the GSV. MATERIALS AND METHODS: A systematic review of the literature, a retrospective analysis of duplex examinations, and a prospective study of duplex examinations to investigate the frequency of true duplications of the GSV. RESULTS: In the literature review, a great variety of definitions is used for duplication of the GSV. Before the consensus of the Union International de Phlébologie (UIP) in 2006, Only in a small number of studies, the definition of the GSV in the saphenous compartment between the fascial blades is mentioned. CONCLUSION: Phlebographic studies have been the criterion standard for the identification of venous anatomy. Now, duplex is regarded as the criterion standard for accurate detection of the veins. True duplication of the GSV is less common than the previous literature has suggested, namely 1.6% to 2%. It is recommended that the duplicated GSV should be treated to avoid an important risk of recurrence of venous insufficiency