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BackgroundVertigo, a highly prevalent disease, imposes a rising burden on the health care system, exacerbated by the ageing of the population; and further, contributes to a wide span of indirect burden due to reduced capacity to work or need of assistance in activities of daily living. The aim of this review was to summarise the evidence on the economic burden of vertigo.MethodsAll original studies published between 2008 and 2018 about the economic evaluation of peripheral or central vestibular vertigo in developed countries were considered eligible, unrestricted to setting, health care provider, or study type.ResultsThe electronic search in three databases identified 154 studies from which 16 qualified for inclusion. All studies presented partial economic evaluation referring to a variety of vestibular vertigo including unspecified vertigo. Nine studies presented monetised cost results and seven studies reported health care utilization. Direct costs derived mainly from repeated and not well-targeted consultations at all levels of health care, excessive use of diagnostic imaging, and/or of emergency care. Considerable societal burden was caused by decreased productivity, mainly due to work absenteeism.ConclusionTo the best of our knowledge, this is the first systematic review of the existing evidence of the economic burden of vertigo. The lack of conclusive evidence revealed apparent targets of future research. First, studies of diagnostics and therapies for vestibular disease should include cost-effectiveness considerations. Population-based studies of health services utilization should include simple vestibular assessments to get more reliable estimates of the burden of disease and associated costs on the level of the general population. Further, clinical and population-based registries that include patients with vestibular disease, should consider collecting long-term data of societal burden. Primary data collection should increasingly include assessment of health care utilization e.g. by linking their diagnoses and outcomes to routine data from health insurances.

Vitamin D is critical for bone health and immune function, but the COVID-19 pandemic, characterized by lockdowns and reduced outdoor activity, raised concerns about potential declines in vitamin D levels due to dietary changes and limited sunlight exposure. In this study, we analyzed routinely-collected laboratory data ( N  = 292,187 patients) from a large laboratory chain in Bavaria, Germany, to assess changes in vitamin D levels before (March 2018 to February 2020) and during (March 2020 to February 2022) the pandemic. Different statistical approaches (i.e., descriptive statistics, propensity score matching, and a causal forest) were used to evaluate confounder-adjusted changes in vitamin D levels and deficiency rates. Mean vitamin D levels decreased significantly from 26.7 μ g/l pre-pandemic to 26.0 μ g/l during the pandemic ( p -value < 0.001), with a corresponding increase in deficiency rates from 31.2% to 35.2% ( p -value < 0.001). Across all statistical approaches, the decline in mean levels and the increase in deficiency rates were particularly pronounced among elderly women. These findings highlight the importance of public health strategies to monitor and improve vitamin D status, especially during periods of restricted outdoor activity. Decreased time spent outside during COVID-19 lockdowns may have impacted population vitamin D levels. Here, the authors investigate evidence for this effect using routinely collected vitamin D testing data from Bavaria, Germany.

Background Spontaneous episodic vertigo syndromes, namely vestibular migraine (VM) and Menière’s disease (MD), are difficult to differentiate, even for an experienced clinician. In the presence of complex diagnostic information, automated systems can support human decision making. Recent developments in machine learning might facilitate bedside diagnosis of VM and MD. Methods Data of this study originate from the prospective patient registry of the German Centre for Vertigo and Balance Disorders, a specialized tertiary treatment center at the University Hospital Munich. The classification task was to differentiate cases of VM, MD from other vestibular disease entities. Deep Neural Networks (DNN) and Boosted Decision Trees (BDT) were used for classification. Results A total of 1357 patients were included (mean age 52.9, SD 15.9, 54.7% female), 9.9% with MD and 15.6% with VM. DNN models yielded an accuracy of 98.4 ± 0.5%, a precision of 96.3 ± 3.9%, and a sensitivity of 85.4 ± 3.9% for VM, and an accuracy of 98.0 ± 1.0%, a precision of 90.4 ± 6.2% and a sensitivity of 89.9 ± 4.6% for MD. BDT yielded an accuracy of 84.5 ± 0.5%, precision of 51.8 ± 6.1%, sensitivity of 16.9 ± 1.7% for VM, and an accuracy of 93.3 ± 0.7%, precision 76.0 ± 6.7%, sensitivity 41.7 ± 2.9% for MD. Conclusion The correct diagnosis of spontaneous episodic vestibular syndromes is challenging in clinical practice. Modern machine learning methods might be the basis for developing systems that assist practitioners and clinicians in their daily treatment decisions.

Purpose Vertigo and dizziness belong to the most frequent syndromes in the primary, secondary and tertiary setting and can be divided into vertigo with episodic or chronic persistent complaints. Episodic vertigo (EVS) is characterized by recurrent attacks of vertigo or dizziness with intermittent symptom-free periods, while chronic vertigo (CVS) presents with persistent vertigo. It is still not completely understood how EVS or CVS affect health-related quality of life (HRQoL) and functioning. Methods Data originates from the DizzyReg patient registry, an ongoing prospective clinical patient registry situated at tertiary clinic at the university hospital, Munich. HRQoL and functioning was measured by self-report. CVS and EVS was categorized after comprehensive neuro-otological work-up in line with the diagnostic guidelines. Association of CVS and EVS was assessed with multivariable linear regression models adjusting for potential risk factors and confounders. Results The study included 548 patients (57% female, mean age 51.35). Patients with EVS were significantly younger (48.5 vs. 59.6 years) and were more often female (60 vs. 49%). EVS patients reported significantly better functioning (42.1 vs. 47.8) and HRQoL (63.87 vs. 58.08) than CVS patients. The effect was stable after adjusting for potential confounders. Conclusion This is the first study to show worse HRQoL in patients with CVS compared to EVS. The results of the study underpin the experience from clinical practice that mobility and balance control are especially important for patients with CVS.

In 2016, the Bárány Society defined new diagnostic criteria for the neurovascular compression syndrome of the eighth nerve, called “vestibular paroxysmia” (VP), differentiating between definite (dVP) and probable (pVP) forms. The aim of this study was (1) to describe clinical symptoms and laboratory findings in a well-diagnosed large patient cohort according to those criteria, and (2) to evaluate the long-term course over years in dVP. We identified 146 patients (73 dVP, 73 pVP) from our tertiary dizziness center registry. Data of structured history-taking, clinical neurological, neuro-ophthalmological/-otological examinations as well as MRI imaging were extracted for analyses. Overall, attack frequency ranged between 5 and 30 attacks per day; spinning vertigo was the most frequent type. In two-thirds of patients, attacks occurred spontaneously; in one-quarter, they were triggered by head movements. The majority (approximately 70%) reported no accompanying symptoms; in those with symptoms, mild unilateral cochlear symptoms prevailed. One-third of patients initially showed hyperventilation-induced nystagmus without specific direction, and a deviation of the subjective visual vertical between 3° and 6°. Complete loss of peripheral vestibular function was never evident. dVP and pVP significantly differed concerning the vertigo type, e.g., spinning vertigo was more frequent in dVP. Fortunately, three-quarters of dVP patients remained attack-free during follow-up (mean 4.8 years, standardized questionnaire), more than half of them even without any medication. Patients with ongoing attacks showed significantly higher attack frequency at baseline, but reported persistent frequency reduction. Overall, the long-term prognosis of VP appears favorable, not necessarily requiring ongoing treatment.

During the SARS-CoV-2 pandemic mobile health applications indicating risks emerging from close contacts to infected persons have a large potential to interrupt transmission chains by automating contact tracing. Since its dispatch in Germany in June 2020 the Corona Warn App has been downloaded on 25.7 Mio smartphones by February 2021. To understand barriers to download and user fidelity in different sociodemographic groups we analysed data from five consecutive cross-sectional waves of the COVID-19 Snapshot Monitoring survey from June to August 2020. Questions on the Corona Warn App included information on download, use, functionality, usability, and consequences of the app. Of the 4,960 participants (mean age 45.9 years, standard deviation 16.0, 50.4% female), 36.5% had downloaded the Corona Warn App. Adjusted analysis found that those who had downloaded the app were less likely to be female (Adjusted Odds Ratio for men 1.16 95% Confidence Interval [1.02;1.33]), less likely to be younger (Adjusted Odds Ratio for age 18 to 39 0.47 [0.32;0.59] Adjusted Odds Ratio for age 40 to 64 0.57 [0.46;0.69]), less likely to have a lower household income (AOR 0.55 [0.43;0.69]), and more likely to live in one of the Western federal states including Berlin (AOR 2.31 [1.90;2.82]). Willingness to disclose a positive test result and trust in data protection compliance of the Corona Warn App was significantly higher in older adults. Willingness to disclose also increased with higher educational degrees and income. This study supports the hypothesis of a digital divide that separates users and non-users of the Corona Warn App along a well-known health gap of education, income, and region.

The origin of malnutrition in older age is multifactorial and risk factors may vary according to health and living situation. The present study aimed to identify setting-specific risk profiles of malnutrition in older adults and to investigate the association of the number of individual risk factors with malnutrition. Data of four cross-sectional studies were harmonized and uniformly analysed. Malnutrition was defined as BMI < 20 kg/m2 and/or weight loss of >3 kg in the previous 3-6 months. Associations between factors of six domains (demographics, health, mental function, physical function, dietary intake-related problems, dietary behaviour), the number of individual risk factors and malnutrition were analysed using logistic regression. Community (CD), geriatric day hospital (GDH), home care (HC), nursing home (NH). CD older adults (n 1073), GDH patients (n 180), HC receivers (n 335) and NH residents (n 197), all ≥65 years. Malnutrition prevalence was lower in CD (11 %) than in the other settings (16-19 %). In the CD sample, poor appetite, difficulties with eating, respiratory and gastrointestinal diseases were associated with malnutrition; in GDH patients, poor appetite and respiratory diseases; in HC receivers, younger age, poor appetite and nausea; and in NH residents, older age and mobility limitations. In all settings the likelihood of malnutrition increased with the number of potential individual risk factors. The study indicates a varying relevance of certain risk factors of malnutrition in different settings. However, the relationship of the number of individual risk factors with malnutrition in all settings implies comprehensive approaches to identify persons at risk of malnutrition early.

Objective Phenotypes are important for patient classification, disease prognostication, and treatment customization. We aimed to identify distinct clinical phenotypes of children and adolescents hospitalized with SARS-CoV-2 infection, and to evaluate their prognostic differences. Methods The German Society of Pediatric Infectious Diseases (DGPI) registry is a nationwide, prospective registry for children and adolescents hospitalized with a SARS-CoV-2 infection in Germany. We applied hierarchical clustering for phenotype identification with variables including sex, SARS-CoV-2-related symptoms on admission, pre-existing comorbidities, clinically relevant coinfection, and SARS-CoV-2 risk factors. Outcomes of this study were: discharge status and ICU admission. Discharge status was categorized as: full recovery, residual symptoms, and unfavorable prognosis (including consequential damage that has already been identified as potentially irreversible at the time of discharge and SARS-CoV-2-related death). After acquiring the phenotypes, we evaluated their correlation with discharge status by multinomial logistic regression model, and correlation with ICU admission by binary logistic regression model. We conducted an analogous subgroup analysis for those aged < 1 year (infants) and those aged ⩾ 1 year (non-infants). Results The DGPI registry enrolled 6983 patients, through which we identified six distinct phenotypes for children and adolescents with SARS-CoV-2 which can be characterized by their symptom pattern: phenotype A had a range of symptoms, while predominant symptoms of patients with other phenotypes were gastrointestinal (95.9%, B), asymptomatic (95.9%, C), lower respiratory tract (49.8%, D), lower respiratory tract and ear, nose and throat (86.2% and 41.7%, E), and neurological (99.2%, F). Regarding discharge status, patients with D and E phenotype had the highest odds of having residual symptoms (OR: 1.33 [1.11, 1.59] and 1.91 [1.65, 2.21], respectively) and patients with phenotype D were significantly more likely (OR: 4.00 [1.95, 8.19]) to have an unfavorable prognosis. Regarding ICU, patients with phenotype D had higher possibility of ICU admission than staying in normal ward (OR: 4.26 [3.06, 5.98]), compared to patients with phenotype A. The outcomes observed in the infants and non-infants closely resembled those of the entire registered population, except infants did not exhibit typical neurological/neuromuscular phenotypes. Conclusions Phenotypes enable pediatric patient stratification by risk and thus assist in personalized patient care. Our findings in SARS-CoV-2-infected population might also be transferable to other infectious diseases.

DNA methylation (DNAm) patterns in peripheral blood have been shown to be associated with aging related health outcomes. We perform an epigenome-wide screening to identify CpGs related to frailty, defined by a frailty index (FI), in a large population-based cohort of older adults from Germany, the ESTHER study. Sixty-five CpGs are identified as frailty related methylation loci. Using LASSO regression, 20 CpGs are selected to derive a DNAm based algorithm for predicting frailty, the epigenetic frailty risk score (eFRS). The eFRS exhibits strong associations with frailty at baseline and after up to five-years of follow-up independently of established frailty risk factors. These associations are confirmed in another independent population-based cohort study, the KORA-Age study, conducted in older adults. In conclusion, we identify 65 CpGs as frailty-related loci, of which 20 CpGs are used to calculate the eFRS with predictive performance for frailty over long-term follow-up. Frailty is associated with an increased risk for negative health outcomes in older populations, and being able to predict frailty could facilitate prevention measures. By performing an epigenome-wide screen, the authors derived a DNA methylation based measure for frailty which can predict both prevalence and longer-term incidence of frailty.