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Background: Atrial fibrillation is associated with several comorbidities, particularly cognitive impairment and dementia, especially in older patients. Non‐vitamin K oral anticoagulants (NOACs) or vitamin K antagonists (VKAs) were used to prevent thromboembolic events. However, data on the real benefit of these drugs on cognitive function decline remains controversial. In this study we evaluated the effect of NOACs compared to VKAs on the absolute and relative decline in cognitive function over time. Methods: Nine hundred and eighty‐three older patients with nonvalvular AF were enrolled (76 ± 6 years; 291 on VKAs and 692 on NOACs). The cognitive function was assessed with Mini Mental State examination (MMSE) score. The between‐arms difference of cognitive evolution over time was investigated by Linear Mixed Models and group‐based trajectory model analyses. Results: In the whole multicenter observational study, after a long follow‐up of 7.2 ± 3.4 years, the patients of the NOACs versus VKAs group had lowest absolute reduction of the MMSE score between baseline and follow‐up (−0.3 ± 0.03 vs.−1.7 ± 0.1, p < 0.001). After stratification into five subgroups according to trajectories of MMSE score over time, the probability to belong to trajectories with lower decline in cognitive functions was higher in patients on NOACs than in those on VKAs (3.93–13.88 times). Conclusion: In older patients with atrial fibrillation, the use of NOACs was associated with a smaller decline of cognitive function over time compared to the VKAs, regardless that patients in the NOACs group were older and with a higher burden of comorbidities. [ABSTRACT FROM AUTHOR]

Background/Objectives: Chronic kidney disease (CKD) and end-stage kidney disease (ESKD) are significant public health issues, with cardiovascular morbidity and mortality being the leading causes of death in hemodialysis patients. Osteopontin (OPN), a multifunctional glycoprotein, has emerged as a potential biomarker for vascular disease in CKD due to its role in inflammation, tissue remodeling, and calcification. Methods: This cohort study included 1124 hemodialysis patients from the PROGREDIRE study, a registry involving 35 dialysis units in Southern Italy. Serum osteopontin levels were measured using enzyme-linked immunosorbent assay (ELISA). The primary endpoints were all-cause and cardiovascular mortality. Multivariate Cox regression analyses were performed to assess the association between osteopontin levels and mortality, adjusting for traditional risk factors, biomarkers of inflammation, nutritional status, and ESKD-related factors. Results: During a mean follow-up of 2.8 years, 478 patients died, 271 from cardiovascular causes. Independent correlates of osteopontin included alkaline phosphatase and parathyroid hormone. Elevated osteopontin levels were significantly associated with increased all-cause mortality (HR 1.19, 95% CI 1.09–1.31, p < 0.001) and cardiovascular mortality (HR 1.22, 95% CI 1.08–1.38, p = 0.001) after adjusting for confounders. Conclusions: Elevated osteopontin levels are associated with increased all-cause and cardiovascular mortality in hemodialysis patients. These findings implicate osteopontin in the high risk for death and cardiovascular disease in the hemodialysis population. Intervention studies are needed to definitively test this hypothesis. [ABSTRACT FROM AUTHOR]

Simple Summary: Daratumumab (DARA) plus bortezomib, thalidomide, and dexamethasone (D-VTd) represent the standard of induction care in Europe for autologous stem cell transplantation (auto-SCT)-eligible, newly diagnosed multiple myeloma (NDMM) patients. This study aimed to investigate the possible impact of D-VTd induction therapy on hematopoietic engraftment after auto-SCT. Our findings indicate that patients treated with D-VTd experienced longer neutrophil and platelet engraftment times than those treated with VTd. Additionally, D-VTd treatment was associated with a higher incidence of febrile neutropenia and grade 2 or higher diarrhea. However, no significant differences were observed in the median number of days to discharge. The conclusion we can draw from our real-life study is that a four-drug induction therapy containing DARA does not impact transplant safety outcomes. Background: This real-life study aimed to investigate the possible impact of D-VTd induction therapy on hematopoietic engraftment after autologous stem cell transplantation (auto-SCT). Methods: Sixty consecutive NDMM patients received four cycles of induction therapy with D-VTd. The conditioning regimen consisted of melphalan 200 mg/m2. These patients were compared with a historical control group of 80 patients who received four cycles of VTd as induction therapy. Results: The median days to reach neutrophil and platelet engraftment significantly differed between patients treated with D-VTd (11 and 13 days, respectively) and VTd (10 and 12 days). Univariate Cox analyses show that patients treated with D-VTd had a hazard ratio of neutrophil engraftment that was 42% significantly lower than those in the VTd arm (HR: 0.58, p = 0.002), and a multivariate model confirmed this result. Patients treated with D-VTd developed FN more frequently. Univariate and multivariate logistic regressions revealed an association between D-VTd and FN. Delayed engraftment did not correlate with more extended hospitalization. No patients died in the first six months after transplantation. Conclusions: Our real-life study showed that a four-drug induction therapy containing DARA does not impact transplant safety outcomes. [ABSTRACT FROM AUTHOR]

The assessment of risk and effect size of a specific endpoint associated to the presence/absence of a certain exposure is a hallmark in clinical and epidemiological research. In fact, before recommending any treatment, it is mandatory to investigate the magnitude of the benefits and harms between the exposure under investigation (e.g. a given treatment) and a specific disease or event. To do this, clinicians and statisticians use absolute (risk differences, number needed to treat, likelihood to be helped or harmed) and relative (risk ratio, incidence rate ratio, hazard ratio and odds ratio) measures of effect. Herein, using a series of clinical examples, we aim to present a step by step methodologic approach of measures of effect in the area of nephrology and urology. [ABSTRACT FROM AUTHOR]

Abstract Background Translational Medicine focuses on “bench to bedside”, converting experimental results into clinical use. The “bedside to bench” transition remains challenging, requiring clinicians to define true clinical need for laboratory study. In this study, we show how observational data (an eleven-year data survey program on adolescent smoking behaviours), can identify knowledge gaps and research questions leading directly to clinical implementation and improved health care. We studied gender-specific trends (2000–2010) in Italian students to evaluate the specific impact of various anti-smoking programs, including evaluation of perceptions of access to cigarettes and health risk. Methods The study used, ESPAD-Italia® (European School Survey Project on Alcohol and other Drugs), is a nationally representative sample of high-school students. The permutation test for joinpoint regression was used to calculate the annual percent change in smoking. Changes in smoking habits by age, perceived availability and risk over a 11-year period were tested using a gender-specific logistic model and a multinomial model. Results Gender-stratified analysis showed 1) decrease of lifetime prevalence, then stabilization (both genders); 2) decrease in last month and occasional use (both genders); 3) reduction of moderate use (females); 4) no significant change in moderate use (males) and in heavy use (both genders). Perceived availability positively associates with prevalence, while perceived risk negatively associates, but interact with different effects depending on smoking patterns. In addition, government implementation of public policies concerning access to tobacco products in this age group during this period presented a unique background to examine their specific impact on behaviours. Conclusion Large observational databases are a rich resource in support of translational research. From these observations, key clinically relevant issues can be identified and form the basis for further clinical studies. The ability to identify patterns of behaviour and gaps in available data translates into new experiments, but also impacts development of public policy and reveals patterns of clinical reality. The observed global decrease in use is countered by stabilization in number of heavy smokers. Increased cigarette cost has not reduced use. While perceived risk of smoking may prevent initial experimentation, how government policies impact the perception of risk is not easily quantifiable.

Prognosis aims at estimating the future course of a given disease in probabilistic terms. As in diagnosis, where clinicians are interested in knowing the accuracy of a new test to identify patients affected by a given disease, in prognosis they wish to accurately identify patients at risk of a future event conditional to one or more prognostic factors. Thus, accurate risk predictions play a primary role in all fields of clinical medicine and in geriatrics as well because they can help clinicians to tailor the intensity of a treatment and to schedule clinical surveillance according to the risk of the concerned patient. Statistical methods able to evaluate the prognostic accuracy of a risk score demand the assessment of discrimination (the Harrell's C-index), calibration (Hosmer–May test) and risk reclassification abilities (IDI, an index of risk reclassification) of the same risk prediction rule whereas, in spite of the popular belief that traditional statistical techniques providing relative measures of effect (such as the hazard ratio derived by Cox regression analysis or the odds ratio obtained by logistic regression analysis) could be per se enough to assess the prognostic value of a biomarker or of a risk score. In this paper we provide a brief theoretical background of each statistical test and a practical approach to the issue. For didactic purposes, in the paper we also provide a dataset (n = 40) to allow the reader to train in the application of the proposed statistical methods. [ABSTRACT FROM AUTHOR]

Background Italy was the second country in the world, after China, to be hit by SARS-CoV-2 pandemic. Italy's experience teaches that steps to limit people's movement by imposing 'red zones' need to be put in place early by carefully identifying the cities to be included within these areas of quarantine. The assessment of the relationship between the distance from an established outbreak of SARS-CoV-2 infection with transmission-linked cases and mortality observed in other sites could provide useful information to identify the optimal radius of red zones. Methods We investigated the relationship between SARS-CoV-2 cases and the distance of each Italian province from the first outbreak of SARS-CoV-2 epidemic in Italy (the city of Lodi placed in the Lombardia region). In 38 provinces of Lombardia and neighboring regions, we performed a breakpoint analysis to identify the radius of the red zone around Lodi minimizing epidemic spread and mortality in neighboring cities. Results In all Italian provinces, a non-linear relationship was found between SARS-CoV-2 cases and distance from Lodi. In an analysis including the provinces of Lombardia and neighboring regions, SARS-CoV-2 cases and mortality increased when the distance from Lodi reduced below 92 and 140 km, respectively, and such relationships were amplified by ozone (O3) pollution. Conclusions The breakpoint analysis identifies the radius around the outbreak of Lodi minimizing the public health consequences of SARS-CoV-2 in neighboring cities. Such an approach can be useful to identify the red zones in future epidemics due to highly infective pathogens similar to SARS-CoV-2. [ABSTRACT FROM AUTHOR]