Electronic Patient-Reported Outcome Measures (ePROMs) Improve the Assessment of Underrated Physical and Psychological Symptom Burden among Oncological Inpatients.

For advanced cancer inpatients, the established standard for gathering information about symptom burden involves a daily assessment by nursing staff using validated assessments. In contrast, a systematic assessment of patient-reported outcome measures (PROMs) is required, but it is not yet systematically implemented. We hypothesized that current practice results in underrating the severity of patients' symptom burden. To explore this hypothesis, we have established systematic electronic PROMs (ePROMs) using validated instruments at a major German Comprehensive Cancer Center. In this retrospective, non-interventional study, lasting from September 2021 to February 2022, we analyzed collected data from 230 inpatients. Symptom burden obtained by nursing staff was compared to the data acquired by ePROMs. Differences were detected by performing descriptive analyses, Chi-Square tests, Fisher's exact, Phi-correlation, Wilcoxon tests, and Cohen's r. Our analyses pointed out that pain and anxiety especially were significantly underrated by nursing staff. Nursing staff ranked these symptoms as non-existent, whereas patients stated at least mild symptom burden (pain: meanNRS/epaAC = 0 (no); meanePROM = 1 (mild); p < 0.05; r = 0.46; anxiety: meanepaAC = 0 (no); meanePROM = 1 (mild); p < 0.05; r = 0.48). In conclusion, supplementing routine symptom assessment used daily by nursing staff with the systematic, e-health-enabled acquisition of PROMs may improve the quality of supportive and palliative care.

Reversible occlusion of the pulmonary vasculature by transarterial embolisation with degradable starch microspheres: preclinical assessment in a human isolated lung perfusion model.

BACKGROUND: Transpulmonary embolisation (TPE) using degradable starch microspheres (DSM) is a potential approach to treat pulmonary metastases. However, there is a paucity of detailed information on perfusion dynamics. The aim of this study was to establish a human ex vivo isolated lung perfusion (ILP) model to observe and evaluate the effects of DSM-TPE in a near-physiologic setting. METHODS: ILP was carried out on six surgically resected lung lobes. At baseline, computed tomography (CT), including CT perfusion imaging (CTPI), and histopathological sampling were performed (t30). DSM-TPE was initiated and increased stepwise (t45, t60, t75, and t90) to be followed by CT imaging, histopathological sampling, and pulmonary arterial pressure (PAP). After the last assessment (t90), alpha-amylase was injected into the pulmonary artery to allow for DSM hydrolysation and two additional assessments (t105; t120). Histopathological specimens were evaluated using a semiquantitative ordinal score. CTPI was used for time to peak (TTP) analysis. RESULTS: After DSM administration, PAP and TTP increased significantly: PAP slope 95% confidence interval (CI) 0.104-0.483, p = 0.004; TTP t30 versus t45, p = 0.046. After the addition of alpha-amylase, functional parameters reverted to values comparable to baseline. In histopathological samples, embolisation grades increased significantly until t90 (slope 95% CI 0.027-0.066, p < 0.001) and decreased after addition of alpha-amylase (slope 95% CI -0.060-0.012, p = 0.165), CONCLUSIONS: The ILP model demonstrated successfully both the physiologic effect of DSM-TPE on human lungs and its reversibility with alpha-amylase. Thus, it can be used as a near-physiologic preclinical tool to simulate and assess later clinical approaches.

18F-FDG PET/MRI for Therapy Response Assessment of Isolated Limb Perfusion in Patients with Soft-Tissue Sarcomas.

Our purpose was to assess the diagnostic potential of simultaneously acquired 18F-FDG PET and MRI data sets for therapy response assessment of isolated limb perfusion (ILP) in patients with soft-tissue sarcomas (STS). Methods: In total, 45 patients with histopathologically verified STS were prospectively enrolled for an integrated 18F-FDG PET/MRI examination before and after ILP. Therapy response was assessed based on different MRI- and PET-derived morphologic (RECIST and the MR-adapted Choi criteria) and metabolic (PERCIST) criteria. In addition, a regression model was used combining relative changes in quantitative variables to predict treatment response under ILP. Histopathologic results after subsequent tumor resection served as the reference standard, and patients were categorized as responders or nonresponders on the basis of the 6-stage regression scale by Salzer-Kuntschik. Results: Histopathologic analysis categorized 27 patients as responders (grades I-III) and 18 patients as nonresponders (grades IV-VI). Calculated sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy were 22%, 89%, 75%, 43%, and 49% for RECIST; 70%, 44%, 66%, 50%, and 60% for the Choi criteria; and 85%, 78%, 85%, 78%, and 82% for PERCIST. Receiver-operating-characteristic analysis revealed an area under the curve (AUC) of 0.56 for RECIST, 0.57 for the Choi criteria, and 0.82 for PERCIST. The combined regression model revealed higher values (AUC, 0.90) than for the stand-alone analysis, however, differences to metabolic parameters did not reach significance (P value: 0.067). Conclusion: Our study demonstrates the superiority of 18F-FDG PET over MRI data sets for response assessment of STS under neoadjuvant ILP. In a clinical setting, MRI delivers valuable information for presurgical assessment. Therefore, combining 18F-FDG PET and MRI data may enable more reliable treatment planning and therapy monitoring of STS.

Trends in resource utilization and prescription of anticonvulsants for patients with active epilepsy in Germany from 2003 to 2013 - A ten-year overview.

This study evaluated trends in resource use and prescription patterns in patients with active epilepsy over a 10-year period at the same outpatient clinic of a German epilepsy center. We analyzed a cross-sectional patient sample of consecutive adults with active epilepsy over a 3-month period in 2013 and compared them with equally acquired data from the years 2003 and 2008. Using validated patient questionnaires, data on socioeconomic status, course of epilepsy, as well as direct and indirect costs were recorded. A total of 198 patients (mean age: 39.6±15.0years, 49.5% male) were enrolled and compared with our previous assessments in 2003 (n=101) and 2008 (n=151). In the 2013 cohort, 75.8% of the patients had focal epilepsy, and the majority were taking antiepileptic drugs (AEDs) (39.9% monotherapy, 59.1% polytherapy). We calculated epilepsy-specific costs of €3674 per three months per patient. Direct medical costs were mainly due to anticonvulsants (20.9% of total direct costs) and to hospitalization (20.8% of total direct costs). The proportion of enzyme-inducing anticonvulsants and 'old' AEDs decreased between 2003 and 2013. Indirect costs of €1795 in 2013 were mainly due to early retirement (55.0% of total indirect costs), unemployment (26.5%), and days off due to seizures (18.2%). In contrast to our previous findings from 2003 and 2008, our data show a stagnating cost increase with slightly reduced total costs and balanced direct and indirect costs in patients with active epilepsy. These findings are accompanied by an ongoing cost-neutral increase in the prescription of 'newer' and non-enzyme-inducing AEDs. However, the number and distribution of indirect cost components remained unchanged.

Evaluation of health-care utilization among adult patients with epilepsy in Germany.

This study evaluated the resource use of patients with epilepsy in the German district of Marburg-Biedenkopf. A cross-sectional cohort of consecutive adults with epilepsy, irrespective of seizure severity, duration of illness and epilepsy syndrome, was investigated in all health-care sectors. Costs of inpatient and outpatient treatment were derived from billing data of participating hospitals and office-based physicians. Data on socioeconomic status, course of epilepsy and further direct and indirect costs were recorded using patient questionnaires. We enrolled 366 patients from the district of Marburg-Biedenkopf and calculated annual epilepsy-specific costs of €7738 per patient. Direct costs contributed 31.1% (€2406) and indirect costs 68.9% (€5332) of the total costs. Direct medical costs were mainly due to hospitalization (33.2% of total direct costs) and anticonvulsants (26.7%). Costs of admissions were due to status epilepticus (24.4%), video-EEG monitoring (14.8%), newly diagnosed patients (14.4%) and seizure-related injuries (8.8%). Indirect costs were mainly due to early retirement (38.0%), unemployment (35.9%) and days off due to seizures (26.2%). The mean costs of epilepsy found in our study were lower than those found in studies conducted at European epilepsy centers due to the inclusion of patients in all health-care sectors.

Interactive production planning and ergonomic assessment with Digital Human Models--introducing the Editor for Manual Work Activities (ema).

The aging workforce is a risk factor for manufacturing industries that contain many jobs with high physical workloads. Thus, ergonomic risk factors have to be avoided in early phases of production planning. This paper introduces a new tool for simulating manual work activities with 3D human models, the so-called emaΦ. For the most part, the emaΦ software is based on a unique modular approach including a number of complex operations that were theoretically developed and empirically validated by means of motion capturing technologies. Using these modules for defining the digital work process enables the production planner to compile human simulations more accurately and much quicker compared to any of the existing modeling tools. Features of the emaΦ software implementation, such as ergonomic evaluation and MTM-time analyses, and the workflow for practical application are presented.

Identity-by-descent filtering of exome sequence data for disease-gene identification in autosomal recessive disorders.

MOTIVATION: Next-generation sequencing and exome-capture technologies are currently revolutionizing the way geneticists screen for disease-causing mutations in rare Mendelian disorders. However, the identification of causal mutations is challenging due to the sheer number of variants that are identified in individual exomes. Although databases such as dbSNP or HapMap can be used to reduce the plethora of candidate genes by filtering out common variants, the remaining set of genes still remains on the order of dozens. RESULTS: Our algorithm uses a non-homogeneous hidden Markov model that employs local recombination rates to identify chromosomal regions that are identical by descent (IBD = 2) in children of consanguineous or non-consanguineous parents solely based on genotype data of siblings derived from high-throughput sequencing platforms. Using simulated and real exome sequence data, we show that our algorithm is able to reduce the search space for the causative disease gene to a fifth or a tenth of the entire exome. AVAILABILITY: An R script and an accompanying tutorial are available at http://compbio.charite.de/index.php/ibd2.html.

Clinical diagnostics in human genetics with semantic similarity searches in ontologies.

The differential diagnostic process attempts to identify candidate diseases that best explain a set of clinical features. This process can be complicated by the fact that the features can have varying degrees of specificity, as well as by the presence of features unrelated to the disease itself. Depending on the experience of the physician and the availability of laboratory tests, clinical abnormalities may be described in greater or lesser detail. We have adapted semantic similarity metrics to measure phenotypic similarity between queries and hereditary diseases annotated with the use of the Human Phenotype Ontology (HPO) and have developed a statistical model to assign p values to the resulting similarity scores, which can be used to rank the candidate diseases. We show that our approach outperforms simpler term-matching approaches that do not take the semantic interrelationships between terms into account. The advantage of our approach was greater for queries containing phenotypic noise or imprecise clinical descriptions. The semantic network defined by the HPO can be used to refine the differential diagnosis by suggesting clinical features that, if present, best differentiate among the candidate diagnoses. Thus, semantic similarity searches in ontologies represent a useful way of harnessing the semantic structure of human phenotypic abnormalities to help with the differential diagnosis. We have implemented our methods in a freely available web application for the field of human Mendelian disorders.

Uncertainty assessment of contaminant plume length estimates in heterogeneous aquifers.

The Virtual Aquifer approach is used in this study to assess the uncertainty involved in the estimation of contaminant plume lengths in heterogeneous aquifers. Contaminant plumes in heterogeneous two-dimensional conductivity fields and subject to first order and Michaelis-Menten (MM) degradation kinetics are investigated by the center line method. First order degradation rates and plume lengths are estimated from point information obtained along the plume center line. Results from a Monte-Carlo investigation show that the estimated rate constant is highly uncertain and biased towards overly high values. Uncertainty and bias amplify with increasing heterogeneity up to maximum values of one order of magnitude. Calculated plume lengths reflect this uncertainty and bias. On average, plume lengths are estimated to about 50% of the true plume length. When plumes subject to MM degradation kinetics are investigated by using a first order rate law, an additional error is introduced and uncertainty as well as bias increase, causing plume length estimates to be less than 40% of the true length. For plumes with MM degradation kinetics, therefore, a regression approach is used which allows the determination of the MM parameters from center line data. Rate parameters are overestimated by a factor of two on average, while plume length estimates are about 80% of the true length. Plume lengths calculated using the MM parameters are thus closer to the correct length, as compared to the first order approximation. This approach is therefore recommended if field data collected along the center line of a plume give evidence of MM kinetics.