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

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

Multi-infusion with integrated multiple pressure sensing allows earlier detection of line occlusions

Abstract Background Occlusions of intravenous (IV) tubing can prevent vital and time-critical medication or solutions from being delivered into the bloodstream of patients receiving IV therapy. At low flow rates (≤ 1 ml/h) the alarm delay (time to an alert to the user) can be up to 2 h using conventional pressure threshold algorithms. In order to reduce alarm delays we developed and evaluated the performance of two new real-time occlusion detection algorithms and one co-occlusion detector that determines the correlation in trends in pressure changes for multiple pumps. Methods Bench-tested experimental runs were recorded in triplicate at rates of 1, 2, 4, 8, 16, and 32 ml/h. Each run consisted of 10 min of non-occluded infusion followed by a period of occluded infusion of 10 min or until a conventional occlusion alarm at 400 mmHg occurred. The first algorithm based on binary logistic regression attempts to detect occlusions based on the pump’s administration rate Q(t) and pressure sensor readings P(t). The second algorithm continuously monitored whether the actual variation in the pressure exceeded a threshold of 2 standard deviations (SD) above the baseline pressure. When a pump detected an occlusion using the SD algorithm, a third algorithm correlated the pressures of multiple pumps to detect the presence of a shared occlusion. The algorithms were evaluated using 6 bench-tested baseline single-pump occlusion scenarios, 9 single-pump validation scenarios and 7 multi-pump co-occlusion scenarios (i.e. with flow rates of 1 + 1, 1 + 2, 1 + 4, 1 + 8, 1 + 16, and 1 + 32 ml/h respectively). Alarm delay was the primary performance measure. Results In the baseline single-pump occlusion scenarios, the overall mean ± SD alarm delay of the regression and SD algorithms were 1.8 ± 0.8 min and 0.4 ± 0.2 min, respectively. Compared to the delay of the conventional alarm this corresponds to a mean time reduction of 76% (P = 0.003) and 95% (P = 0.001), respectively. In the validation scenarios the overall mean ± SD alarm delay of the regression and SD algorithms were respectively 1.8 ± 1.6 min and 0.3 ± 0.2 min, corresponding to a mean time reduction of 77% and 95%. In the multi-pump scenarios a correlation > 0.8 between multiple pump pressures after initial occlusion detection by the SD algorithm had a mean ± SD alarm delay of 0.4 ± 0.2 min. In 2 out of the 9 validation scenarios an occlusion was not detected by the regression algorithm before a conventional occlusion alarm occurred. Otherwise no occlusions were missed. Conclusions In single pumps, both the regression and SD algorithm considerably reduced alarm delay compared to conventional pressure limit-based detection. The SD algorithm appeared to be more robust than the regression algorithm. For multiple pumps the correlation algorithm reliably detected co-occlusions. The latter may be used to localize the segment of tubing in which the occlusion occurs. Trial registration Not applicable

Fluid balance and phase angle as assessed by bioelectrical impedance analysis in critically ill patients:a multicenter prospective cohort study

Background: Bioelectrical impedance analysis (BIA) is a validated method to assess body composition in persons with fluid homeostasis and reliable body weight. This is not the case during critical illness. The raw BIA markers resistance, reactance, phase angle, and vector length are body weight independent. Phase angle reflects cellular health and has prognostic significance. We aimed to assess the course of phase angle and vector length during intensive care unit (ICU) admission, and determine the relation between their changes (Δ) and changes in body hydration. Methods: A prospective, dual-center observational study of adult ICU patients was conducted. Univariate and multivariable regression analyses were performed, including reactance as a marker of cellular mass and integrity and total body water according to the Biasioli equation (TBWBiasioli) and fluid balance as body weight independent markers of hydration. Results: One hundred and fifty-six ICU patients (mean ± SD age 62.5 ± 14.5 years, 67% male) were included. Between days 1 and 3, there was a significant decrease in reactance/m (−2.6 ± 6.0 Ω), phase angle (−0.4 ± 1.1°), and vector length (−12.2 ± 44.3 Ω/m). Markers of hydration significantly increased. Δphase angle and Δvector length were both positively related to Δreactance/m (r2 = 0.55, p < 0.01; r2 = 0.38, p < 0.01). Adding ΔTBWBiasioli as explaining factor strongly improved the association between Δphase angle and Δreactance/m (r2 = 0.73, p < 0.01), and Δvector length and Δreactance/m (r2 = 0.77, p < 0.01). Conclusions: Our results show that during critical illness, changes in phase angle and vector length partially reflect changes in hydration

"There is a life before and after cancer":experiences of resuming life and unmet care needs in stage I and II melanoma survivors

Although the largest increase in melanoma incidence is observed for localised melanoma, little research has been done on its impact. Despite favourable prognoses and relatively short treatment trajectories, diagnosis and treatment may significantly impact life post-treatment. Therefore, the aim of this study was to gain an in-depth understanding of stage I and II melanoma survivors' experiences resuming life after treatment and their associated survivorship care (SSC) needs. A qualitative focus group study was conducted with 18 stage I or II melanoma survivors, divided over three focus groups with 6 survivors each. Transcripts were analysed through thorough thematic content analysis, using multiple phases of coding. In resuming life, survivors experienced profound initial impacts of disease and treatment, fed by a perceived lack of knowledge and underestimation of melanoma. They faced unexpected physical and emotional effects post-surgery, experiencing mixed feelings from relief to fear and uncertainty. Survivors felt misunderstood, had to adjust their lives, and managed personal and external expectations while experiencing a positive shift in life perspective, leading to a notable difference in life before and after cancer. In terms of SSC needs, survivors stressed the need for tailored information, accessible resources, patient-centered follow-up, and supportive care addressing the total impact of disease and treatment. These findings highlight the importance of improving melanoma awareness and providing holistic SSC not only to advanced, but also to localised melanoma survivors. A tailored survivorship care plan could facilitate access to information and supportive care, helping patients resume their lives.</p

Bedside lung ultrasound in the critically ill patient with pulmonary pathology:different diagnoses with comparable chest X-ray opacification

The differential diagnosis and treatment of opacifications on the chest X-ray in critically ill patients may be challenging. This holds in particular the patient that suffers from respiratory failure with hemodynamic instability. Opacification in the chest X-ray could be the result of hematothorax, pleural effusion, atelectasis, or consolidation. Physical examination of such patients may not always indicate what the cause of the opacification is and thus may not always help indicate the correct therapeutic approach. In such cases, bedside ultrasound may be very helpful. We present two cases with similar chest X-ray opacifications but different diagnoses established with the help of a bedside lung ultrasound. There is documented accuracy of ultrasound in differentiating pleural effusions from consolidation. Ultrasound is safe and may be an alternative for computed tomography scan in a hemodynamically or respiratory unstable intensive care patient

The epidemiology of acne vulgaris in a multiethnic adolescent population from Rotterdam, the Netherlands:A cross-sectional study

Background: Although acne is a prevalent multifactorial inflammatory skin condition, few studies were performed in multiethnic populations. Objectives: To study the prevalence and determinants of acne in a multiethnic study at the start of puberty. Methods: This cross-sectional study is embedded in Generation R, a population-based prospective study from Rotterdam, the Netherlands. Three-dimensional facial photos at the center visit in 2016-2019 (of ∼13-year-olds) were used to grade acne severity using the Global Evaluation of the Acne Severity (GEA). Analyses were stratified by biological sex and explored through chi-square tests and multivariable ordinal logistic regression. Results: A total of 4561 children (51% girls) with a median age of 13.5 (IQR 13.3-13.6) were included. The visible acne prevalence (GEA 2-5) for girls vs boys was 62% vs 45% and moderate-to-severe acne (GEA 3-5) 14% vs 9%. Higher puberty stages (adjusted odds ratios: 1.38 [1.20-1.59] and 2.16 [1.86-2.51] for girls and boys, respectively) and darker skin colors V and VI (adjusted odds ratios: 1.90 [1.17-3.08] and 2.43 [1.67-3.56]) were associated with more severe acne in both sexes, and being overweight in boys (adjusted odds ratio: 1.58 [1.15-2.17]). Limitations: Cross-sectional design. Conclusions: Acne prevalence was high at the age of 13 years and was associated with advanced puberty, darker skin color, and weight status.</p

The epidemiology of acne vulgaris in a multiethnic adolescent population from Rotterdam, the Netherlands:A cross-sectional study

Background: Although acne is a prevalent multifactorial inflammatory skin condition, few studies were performed in multiethnic populations. Objectives: To study the prevalence and determinants of acne in a multiethnic study at the start of puberty. Methods: This cross-sectional study is embedded in Generation R, a population-based prospective study from Rotterdam, the Netherlands. Three-dimensional facial photos at the center visit in 2016-2019 (of ∼13-year-olds) were used to grade acne severity using the Global Evaluation of the Acne Severity (GEA). Analyses were stratified by biological sex and explored through chi-square tests and multivariable ordinal logistic regression. Results: A total of 4561 children (51% girls) with a median age of 13.5 (IQR 13.3-13.6) were included. The visible acne prevalence (GEA 2-5) for girls vs boys was 62% vs 45% and moderate-to-severe acne (GEA 3-5) 14% vs 9%. Higher puberty stages (adjusted odds ratios: 1.38 [1.20-1.59] and 2.16 [1.86-2.51] for girls and boys, respectively) and darker skin colors V and VI (adjusted odds ratios: 1.90 [1.17-3.08] and 2.43 [1.67-3.56]) were associated with more severe acne in both sexes, and being overweight in boys (adjusted odds ratio: 1.58 [1.15-2.17]). Limitations: Cross-sectional design. Conclusions: Acne prevalence was high at the age of 13 years and was associated with advanced puberty, darker skin color, and weight status.</p