REFERENCE 1. Kor DJ, Talmor D. Anesthesiology and the acute respiratory distress syndrome: an ounce of prevention is worth a pound of cure [editorial].
The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19–74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2–3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4–5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years.
Introduction Acellular dermal matrices (ADMs) are now commonly used for breast reconstruction surgery. There are various products available: ADMs derived from human (HADM), porcine (PADM), or bovine (BADM) sources. Detailed long-term follow-up studies are necessary to detect differences in complication rates between these products. Material and Methods From 2010 to 2015, forty-one patients underwent 52 ADM-breast reconstructions in our clinic, including oncologic breast reconstructions and breast augmentation revisions (n = 52). 15x HADMs (Epiflex®/DIZG), 21x PADMs (Strattice®/LifeCell), and 16x BADMs (Tutomesh®/RTI Surgical) were implanted. Retrospective data collection with median follow-up of 36 months (range: 12–54 months) was performed. Results Overall complication rate was 17% after ADM implantation (HADM: 7%; PADM: 14%; BADM: 31%). In a composite endpoint of complications and Red Breast Syndrome, a lower event probability was observed between BADMs, PADMs, and HADMs (44%, 19%, and 7%, resp.; p = 0.01 for the trend). Furthermore, capsular contracture occurred in 6%, more frequently as compared to the current literature. Conclusions When ADM-based reconstruction is indicated, the authors suggest primarily the use of HADMs and secondary the use of PADMs. It is shown that BADMs have the highest complication probability within our patient cohort; nevertheless, BADMs convey physical advantages in terms of flexibility and better aesthetic outcomes. The indication for the use of ADMs should be filled for each case individually.
Background: The aim of this study was to evaluate CT (computed tomography) imaging differences for the Delta and the Omicron variant in COVID-19 infection. Methods: The study population was derived from a retrospective study cohort investigating chest CT imaging patterns in vaccinated and nonvaccinated COVID-19 patients. CT imaging patterns of COVID-19 infection were evaluated by qualitative and semiquantitative scoring systems, as well as imaging pattern analysis. Results: A total of 60 patients (70.00% male, 62.53 ± 17.3 years, Delta: 43 patients, Omicron: 17 patients) were included. Qualitative scoring systems showed a significant correlation with virus variants; “typical appearance” and “very high” degrees of suspicion were detected more often in patients with Delta (RSNA: p = 0.003; CO-RADS: p = 0.002; COV-RADS: p = 0.001). Semiquantitative assessment of lung changes revealed a significant association with virus variants in univariate (Delta: 6.3 ± 3.5; Omicron: 3.12 ± 3.2; p = 0.002) and multivariate analysis. The vacuolar sign was significantly associated with the Delta variant (OR: 14.74, 95% CI: [2.32; 2094.7], p = 0.017). Conclusion: The Delta variant had significantly more extensive lung involvement and showed changes classified as “typical” more often than the Omicron variant, while the Omicron variant was more likely associated with CT findings such as “absence of pulmonary changes”. A significant correlation between the Delta variant and the vacuolar sign was observed.
To identify the most important parameters associated with cerebral white matter hyperintensities (WMH), in consideration of potential collinearity, we used a data-driven machine-learning approach. We analysed two independent cohorts (KORA and SHIP). WMH volumes were derived from cMRI-images (FLAIR). 90 (KORA) and 34 (SHIP) potential determinants of WMH including measures of diabetes, blood-pressure, medication-intake, sociodemographics, life-style factors, somatic/depressive-symptoms and sleep were collected. Elastic net regression was used to identify relevant predictor covariates associated with WMH volume. The ten most frequently selected variables in KORA were subsequently examined for robustness in SHIP. The final KORA sample consisted of 370 participants (58% male; age 55.7 ± 9.1 years), the SHIP sample comprised 854 participants (38% male; age 53.9 ± 9.3 years). The most often selected and highly replicable parameters associated with WMH volume were in descending order age, hypertension, components of the social environment (i.e. widowed, living alone) and prediabetes. A systematic machine-learning based analysis of two independent, population-based cohorts showed, that besides age and hypertension, prediabetes and components of the social environment might play important roles in the development of WMH. Our results enable personal risk assessment for the development of WMH and inform prevention strategies tailored to the individual patient.
Given the high incidence and effective treatment options for liver diseases, they are of great socioeconomic importance. One of the most common methods for analyzing CT and MRI images for diagnosis and follow-up treatment is liver segmentation. Recent advances in deep learning have demonstrated encouraging results for automatic liver segmentation. Despite this, their success depends primarily on the availability of an annotated database, which is often not available because of privacy concerns. Federated Learning has been recently proposed as a solution to alleviate these challenges by training a shared global model on distributed clients without access to their local databases. Nevertheless, Federated Learning does not perform well when it is trained on a high degree of heterogeneity of image data due to multi-modal imaging, such as CT and MRI, and multiple scanner types. To this end, we propose FedNorm and its extension FedNorm+, two Federated Learning algorithms that use a modality-based normalization technique. Specifically, FedNorm normalizes the features on a client-level, while FedNorm+ employs the modality information of single slices in the feature normalization. Our methods were validated using 428 patients from six publicly available databases and compared to state-of-the-art Federated Learning algorithms and baseline models in heterogeneous settings (multi-institutional, multi-modal data). The experimental results demonstrate that our methods show an overall acceptable performance, achieve Dice per patient scores up to 0.961, consistently outperform locally trained models, and are on par or slightly better than centralized models.
Aim: To evaluate the distribution of intramyocellular lipids (IMCLs) and extramyocellular lipids (EMCLs) as well as total fat content in abdominal skeletal muscle by magnetic resonance imaging (MRI) using a dedicated segmentation algorithm in subjects with type 2 diabetes (T2D), prediabetes and normoglycaemic controls. Materials and Methods: Subjects from a population-based cohort were classified with T2D, prediabetes or as normoglycaemic controls. Total myosteatosis, IMCLs and
Background Little is known about the associations between cardiovascular risk factors (CRF) and disc degeneration (DD). Purpose To evaluate the potential association between CRFs and intervertebral DD in a population-based sample. Methods A total of 400 participants from the community-based KORA-study were assessed in terms of CRFs, specifically obesity, hypertension, diabetes, elevated LDL-c, low HDL-c, elevated triglycerides, smoking status, and alcohol consumption. The patients additionally underwent whole-body magnetic resonance imaging (MRI) using T2-weighted single-shot fast-spin-echo and T1 dual-echo gradient-echo Dixon pulse sequences. Thoracic and lumbar DD were assessed using the Pfirrmann score and for the presence of disc bulging/protrusion. Cross-sectional associations between CRFs and MR-based Pfirrmann score were then analyzed. Results A total of 385 individuals (58.2% men; mean age 56.3 ± 9.2 years) were included. Prevalence of DD was 76.4%. Older age (β = 0.18; 95% CI 0.12–0.25; P < 0.001) and higher body mass index (BMI) (β = 0.19; 95% CI 0.06–0.30; P = 0.003) were significantly associated with DD of the thoracolumbar spine. Diabetes was significantly associated with DD at T7/8 ( P = 0.029) and L3/4 ( P = 0.017). Hypertension correlated significantly with DD in univariate analysis, but the association did not persist using multivariate analysis (β = 0.53; 95% CI –0.74 to 1.81; P = 0.41). None of the other CRFs ( P ≥ 0.11) were associated with advanced DD. Disc bulging was independently associated with hypertension (β = 0.47; 95% CI 0.27–0.81; P = 0.01). Conclusion A significant independent association exists between age, BMI, and intervertebral DD. In contrast, there is no significant association between cardiovascular risk factors and DD. Providing strong evidence that the pathologic process undergirding DD is mechanical, rather than microvascular, in nature.
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