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Background: Large Cell Neuroendocrine Carcinoma (LCNEC) is a rare subtype of lung cancer with poor clinical outcomes. Data on recurrence-free survival (RFS) in early and locally advanced pure LCNEC after complete resection (R0) are lacking. This study aims to evaluate clinical outcomes in this subgroup of patients and to identify potential prognostic markers. Methods: Retrospective multicenter study including patients with pure LCNEC stage I-III and R0 resection. Clinicopathological characteristics, RFS, and disease-specific survival (DSS) were evaluated. Univariate and multivariate analyses were performed. Results: 39 patients (M:F = 26:13), with a median age of 64 years (44–83), were included. Lobectomy (69.2%), bilobectomy (5.1%), pneumonectomy (18%), and wedge resection (7.7%) were performed mostly associated with lymphadenectomy. Adjuvant therapy included platinum-based chemotherapy and/or radiotherapy in 58.9% of cases. After a median follow-up of 44 (4–169) months, the median RFS was 39 months with 1-, 2- and 5-year RFS rates of 60.0%, 54.6%, and 44.9%, respectively. Median DSS was 72 months with a 1-, 2- and 5-year rate of 86.8, 75.9, and 57.4%, respectively. At multivariate analysis, age (cut-off 65 years old) and pN status were independent prognostic factors for both RFS (HR = 4.19, 95%CI = 1.46–12.07, p = 0.008 and HR = 13.56, 95%CI 2.45–74.89, p = 0.003, respectively) and DSS (HR = 9.30, 95%CI 2.23–38.83, p = 0.002 and HR = 11.88, 95%CI 2.28–61.84, p = 0.003, respectively). Conclusion: After R0 resection of LCNEC, half of the patients recurred mostly within the first two years of follow-up. Age and lymph node metastasis could help to stratify patients for adjuvant therapy.
Although bariatric surgery is known to change the metabolome, it is unclear if this is specific for the intervention or a consequence of the induced bodyweight loss. As the weight loss after Roux-en-Y Gastric Bypass (RYGB) can hardly be mimicked with an evenly effective diet in humans, translational research efforts might be helpful. A group of 188 plasma metabolites of 46 patients from the randomized controlled Würzburg Adipositas Study (WAS) and from RYGB-treated rats (n = 6) as well as body-weight-matched controls (n = 7) were measured using liquid chromatography tandem mass spectrometry. WAS participants were randomized into intensive lifestyle modification (LS, n = 24) or RYGB (OP, n = 22). In patients in the WAS cohort, only bariatric surgery achieved a sustained weight loss (BMI −34.3% (OP) vs. −1.2% (LS), p ≤ 0.01). An explicit shift in the metabolomic profile was found in 57 metabolites in the human cohort and in 62 metabolites in the rodent model. Significantly higher levels of sphingolipids and lecithins were detected in both surgical groups but not in the conservatively treated human and animal groups. RYGB leads to a characteristic metabolomic profile, which differs distinctly from that following non-surgical intervention. Analysis of the human and rat data revealed that RYGB induces specific changes in the metabolome independent of weight loss.
To evaluate an iterative learning approach for enhanced performance of robust artificial‐neural‐networks for k‐space interpolation (RAKI), when only a limited amount of training data (auto‐calibration signals [ACS]) are available for accelerated standard 2D imaging.
Methods
In a first step, the RAKI model was tailored for the case of limited training data amount. In the iterative learning approach (termed iterative RAKI [iRAKI]), the tailored RAKI model is initially trained using original and augmented ACS obtained from a linear parallel imaging reconstruction. Subsequently, the RAKI convolution filters are refined iteratively using original and augmented ACS extracted from the previous RAKI reconstruction. Evaluation was carried out on 200 retrospectively undersampled in vivo datasets from the fastMRI neuro database with different contrast settings.
Results
For limited training data (18 and 22 ACS lines for R = 4 and R = 5, respectively), iRAKI outperforms standard RAKI by reducing residual artifacts and yields better noise suppression when compared to standard parallel imaging, underlined by quantitative reconstruction quality metrics. Additionally, iRAKI shows better performance than both GRAPPA and standard RAKI in case of pre‐scan calibration with varying contrast between training‐ and undersampled data.
Conclusion
RAKI benefits from the iterative learning approach, which preserves the noise suppression feature, but requires less original training data for the accurate reconstruction of standard 2D images thereby improving net acceleration.
We assume that a specific health constraint, e.g., a certain aspect of bodily function or quality of life that is measured by a variable X, is absent (or irrelevant) in a healthy reference population (Ref0), and it is materially present and precisely measured in a diseased reference population (Ref1). We further assume that some amount of this constraint of interest is suspected to be present in a population under study (SP). In order to quantify this issue, we propose the introduction of an intuitive measure, the population comparison index (PCI), that relates the mean value of X in population SP to the mean values of X in populations Ref0 and Ref1. This measure is defined as PCI[X] = (mean[X|SP] − mean[X|Ref0])/(mean[X|Ref1] − mean[X|Ref0]) × 100[%], where mean[X|.] is the average value of X in the respective group of individuals. For interpretation, PCI[X] ≈ 0 indicates that the values of X in the population SP are similar to those in population Ref0, and hence, the impairment measured by X is not materially present in the individuals in population SP. On the other hand, PCI[X] ≈ 100 means that the individuals in SP exhibit values of X comparable to those occurring in Ref1, i.e., the constraint of interest is equally present in populations SP and Ref1. A value of 0 < PCI[X] < 100 indicates that a certain percentage of the constraint is present in SP, and it is more than in Ref0 but less than in Ref1. A value of PCI[X] > 100 means that population SP is even more affected by the constraint than population Ref1.
Background
The importance of chronic kidney disease (CKD) and anaemia has not been comprehensively studied in asymptomatic patients at risk for heart failure (HF) versus those with symptomatic HF. We analysed the prevalence, characteristics and prognostic impact of both conditions across American College of Cardiology/American Heart Association (ACC/AHA) precursor and HF stages A–D.
Methods and results
2496 participants from three non-pharmacological German Competence Network HF studies were categorized by ACC/AHA stage; stage C patients were subdivided into C1 and C2 (corresponding to NYHA classes I/II and III, respectively). Overall, patient distribution was 8.1%/35.3%/32.9% and 23.7% in ACC/AHA stages A/B/C1 and C2/D, respectively. These subgroups were stratified by the absence ( – ) or presence ( +) of CKD (estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73m2) and anaemia (haemoglobin in women/men < 12/ < 13 g/dL). The primary outcome was all-cause mortality at 5-year follow-up. Prevalence increased across stages A/B/C1 and C2/D (CKD: 22.3%/23.6%/31.6%/54.7%; anaemia: 3.0%/7.9%/21.7%/33.2%, respectively), with concordant decreases in median eGFR and haemoglobin (all p < 0.001). Across all stages, hazard ratios [95% confidence intervals] for all-cause mortality were 2.1 [1.8–2.6] for CKD + , 1.7 [1.4–2.0] for anaemia, and 3.6 [2.9–4.6] for CKD + /anaemia + (all p < 0.001). Population attributable fractions (PAFs) for 5-year mortality related to CKD and/or anaemia were similar across stages A/B, C1 and C2/D (up to 33.4%, 30.8% and 34.7%, respectively).
Conclusions
Prevalence and severity of CKD and anaemia increased across ACC/AHA stages. Both conditions were individually and additively associated with increased 5-year mortality risk, with similar PAFs in asymptomatic patients and those with symptomatic HF.
Long-term sequelae in hospitalized Coronavirus Disease 2019 (COVID-19) patients may result in limited quality of life. The current study aimed to determine health-related quality of life (HRQoL) after COVID-19 hospitalization in non-intensive care unit (ICU) and ICU patients. This is a single-center study at the University Hospital of Wuerzburg, Germany. Patients eligible were hospitalized with COVID-19 between March 2020 and December 2020. Patients were interviewed 3 and 12 months after hospital discharge. Questionnaires included the European Quality of Life 5 Dimensions 5 Level (EQ-5D-5L), patient health questionnaire-9 (PHQ-9), the generalized anxiety disorder 7 scale (GAD-7), FACIT fatigue scale, perceived stress scale (PSS-10) and posttraumatic symptom scale 10 (PTSS-10). 85 patients were included in the study. The EQ5D-5L-Index significantly differed between non-ICU (0.78 ± 0.33 and 0.84 ± 0.23) and ICU (0.71 ± 0.27; 0.74 ± 0.2) patients after 3- and 12-months. Of non-ICU 87% and 80% of ICU survivors lived at home without support after 12 months. One-third of ICU and half of the non-ICU patients returned to work. A higher percentage of ICU patients was limited in their activities of daily living compared to non-ICU patients. Depression and fatigue were present in one fifth of the ICU patients. Stress levels remained high with only 24% of non-ICU and 3% of ICU patients (p = 0.0186) having low perceived stress. Posttraumatic symptoms were present in 5% of non-ICU and 10% of ICU patients. HRQoL is limited in COVID-19 ICU patients 3- and 12-months post COVID-19 hospitalization, with significantly less improvement at 12-months compared to non-ICU patients. Mental disorders were common highlighting the complexity of post-COVID-19 symptoms as well as the necessity to educate patients and primary care providers about monitoring mental well-being post COVID-19.
Usability of a mHealth solution using speech recognition for point-of-care diagnostic management
(2023)
The administrative burden for physicians in the hospital can affect the quality of patient care. The Service Center Medical Informatics (SMI) of the University Hospital Würzburg developed and implemented the smartphone-based mobile application (MA) ukw.mobile1 that uses speech recognition for the point-of-care ordering of radiological examinations. The aim of this study was to examine the usability of the MA workflow for the point-of-care ordering of radiological examinations. All physicians at the Department of Trauma and Plastic Surgery at the University Hospital Würzburg, Germany, were asked to participate in a survey including the short version of the User Experience Questionnaire (UEQ-S) and the Unified Theory of Acceptance and Use of Technology (UTAUT). For the analysis of the different domains of user experience (overall attractiveness, pragmatic quality and hedonic quality), we used a two-sided dependent sample t-test. For the determinants of the acceptance model, we employed regression analysis. Twenty-one of 30 physicians (mean age 34 ± 8 years, 62% male) completed the questionnaire. Compared to the conventional desktop application (DA) workflow, the new MA workflow showed superior overall attractiveness (mean difference 2.15 ± 1.33), pragmatic quality (mean difference 1.90 ± 1.16), and hedonic quality (mean difference 2.41 ± 1.62; all p < .001). The user acceptance measured by the UTAUT (mean 4.49 ± 0.41; min. 1, max. 5) was also high. Performance expectancy (beta = 0.57, p = .02) and effort expectancy (beta = 0.36, p = .04) were identified as predictors of acceptance, the full predictive model explained 65.4% of its variance. Point-of-care mHealth solutions using innovative technology such as speech-recognition seem to address the users’ needs and to offer higher usability in comparison to conventional technology. Implementation of user-centered mHealth innovations might therefore help to facilitate physicians’ daily work.
Background
Guideline-directed medical therapy (GDMT) is the cornerstone in the treatment of patients with heart failure and reduced ejection fraction (HFrEF) and novel substances such as sacubitril/valsartan (S/V) and sodium-glucose co-transporter-2 inhibitors (SGLT2i) have demonstrated marked clinical benefits. We investigated their implementation into real-world HF care in Germany before, during, and after the COVID-19 pandemic period.
Methods
The IQVIA LRx data set is based on ∼80% of 73 million people covered by the German statutory health insurance. Prescriptions of S/V were used as a proxy for HFrEF. Time trends were analysed between Q1/2016 and Q2/2023 for prescriptions for S/V alone and in combination therapy with SGLT2i.
Findings
The number of patients treated with S/V increased from 5260 in Q1/2016 to 351,262 in Q2/2023. The share of patients with combination therapy grew from 0.6% (29 of 5260) to 14.2% (31,128 of 219,762) in Q2/2021, and then showed a steep surge up to 54.8% (192,429 of 351,262) in Q2/2023, coinciding with the release of the European Society of Cardiology (ESC) guidelines for HF in Q3/2021. Women and patients aged >80 years were treated less often with combined therapy than men and younger patients. With the start of the COVID-19 pandemic, the number of patients with new S/V prescriptions dropped by 17.5% within one quarter, i.e., from 26,855 in Q1/2020 to 22,145 in Q2/2020, and returned to pre-pandemic levels only in Q1/2021.
Interpretation
The COVID-19 pandemic was associated with a 12-month deceleration of S/V uptake in Germany. Following the release of the ESC HF guidelines, the combined prescription of S/V and SGLT2i was readily adopted. Further efforts are needed to fully implement GDMT and strengthen the resilience of healthcare systems during public health crises.
Background
International guidelines emphasise the role of radiotherapy (RT) for the management of advanced adrenocortical carcinoma (ACC). However, the evidence for this recommendation is very low.
Methods
We retrospectively analysed all patients who received RT for advanced ACC in five European centres since 2000. Primary endpoint: time to progression of the treated lesion (tTTP). Secondary endpoints: best objective response, progression-free survival (PFS), overall survival (OS), adverse events, and the establishment of predictive factors by Cox analyses.
Results
In total, 132 tumoural lesions of 80 patients were treated with conventional RT (cRT) of 50–60 Gy (n = 20) or 20–49 Gy (n = 69), stereotactic body RT of 35–50 Gy (SBRT) (n = 36), or brachytherapy of 12–25 Gy (BT) (n = 7). Best objective lesional response was complete (n = 6), partial (n = 52), stable disease (n = 60), progressive disease (n = 14). Median tTTP was 7.6 months (1.0–148.6). In comparison to cRT\(_{20-49Gy}\), tTTP was significantly longer for cRT\(_{50-60Gy}\) (multivariate adjusted HR 0.10; 95% CI 0.03–0.33; p < 0.001) and SBRT (HR 0.31; 95% CI 0.12–0.80; p = 0.016), but not for BT (HR 0.66; 95% CI 0.22–1.99; p = 0.46). Toxicity was generally mild and moderate with three grade 3 events. No convincing predictive factors could be established.
Conclusions
This largest published study on RT in advanced ACC provides clear evidence that RT is effective in ACC.
Introduction
Medium-cut-off (MCO) dialyzers may beneficially impact outcomes in patients on hemodialysis.
Methods
In a randomized, controlled trial in maintenance hemodialysis patients, the new Nipro ELISIO-17HX MCO dialyzer was compared to the Baxter Theranova 400 filter regarding middle molecule removal. Furthermore, the suitability of two assays for free lambda-light chain (λFLC) detection (Freelite vs. N-Latex) was verified.
Results
ELISIO-HX achieved slightly lower reduction ratios for β2-microglobulin (71.8 ± 6.0 vs. 75.3 ± 5.8%; p = 0.001), myoglobin (54.7 ± 8.6 vs. 64.9 ± 8.7%; p < 0.001), and kappa-FLC (62.1 ± 8.8 vs. 56.3 ± 7.7%; p = 0.021). λFLC reduction ratios were more conclusive with the Freelite assay and not different between ELISIO-HX and Theranova (28.4 ± 3.9 vs. 38.7 ± 13.4%; p = 0.069). The albumin loss of Theranova was considerably higher (2.14 ± 0.45 vs. 0.77 ± 0.25 g; p = 0.001) and the Global Removal ScoreLoss alb largely inferior (30.6 ± 7.4 vs. 82.4 ± 29.2%/g; p = 0.006) to ELISIO-HX.
Conclusions
The new ELISIO-HX expands the choice of dialyzers for MCO hemodialysis.