Background: Italy's severe COVID-19 outbreak was addressed by a lockdown that gradually increased in space, time and intensity. The effectiveness of the lockdown has not been precisely assessed with respect to the intensity of mobility restriction and the time until the outbreak receded. Methods: We used processed mobile phone tracking data to measure mobility restriction, and related those data to the number of new SARS-CoV-2 positive cases detected on a daily base in the three most affected Italian regions, Lombardy, Veneto and Emilia-Romagna, from February 1 through April 6, 2020, when two subsequent lockdowns with increasing intensity were implemented by the Italian government. Findings: During the study period, mobility restriction was inversely related to the daily number of newly diagnosed SARS-CoV-2 positive cases only after the second, more effective lockdown, with a peak in the curve of diagnosed cases of infection occurring 14 to 18 days from lockdown in the three regions and 9 to 25 days in the included provinces. An effective reduction in transmission must have occurred nearly immediately after the tighter lockdown, given the lag time of around 10 days from asymptomatic infection to diagnosis. The period from lockdown to peak was shorter in the areas with the highest prevalence of the infection. This effect was seen within slightly more than one week in the most severely affected areas. Interpretation: It appears that the less rigid lockdown led to an insufficient decrease in mobility to reverse an outbreak such as COVID-19. With a tighter lockdown, mobility decreased enough to bring down transmission promptly below the level needed to sustain the epidemic. Funding: No funding sources have been used for this work.

The objective of this paper is to explain how to apply, interpret, and present the results of a new instrument to assess the risk of bias (RoB) in non-randomized studies (NRS) dealing with effects of environmental exposures on health outcomes. This instrument is modeled on the Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) instrument. The RoB instrument for NRS of exposures assesses RoB along a standardized comparison to a randomized target experiment, instead of the study-design directed RoB approach. We provide specific guidance for the integral steps of developing a research question and target experiment, distinguishing issues of indirectness from RoB, making individual-study judgments, and performing and interpreting sensitivity analyses for RoB judgments across a body of evidence. Also, we present an approach for integrating the RoB assessments within the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework to assess the certainty of the evidence in the systematic review. Finally, we guide the reader through an overall assessment to support the rating of all domains that determine the certainty of a body of evidence using the GRADE approach.

Background and aims There is poor knowledge on characteristics, comorbidities and laboratory measures associated with risk for adverse outcomes and in-hospital mortality in European Countries. We aimed at identifying baseline characteristics predisposing COVID-19 patients to in-hospital death. Methods and results Retrospective observational study on 3894 patients with SARS-CoV-2 infection hospitalized from February 19th to May 23rd, 2020 and recruited in 30 clinical centres distributed throughout Italy. Machine learning (random forest)-based and Cox survival analysis. 61.7% of participants were men (median age 67 years), followed up for a median of 13 days. In-hospital mortality exhibited a geographical gradient, Northern Italian regions featuring more than twofold higher death rates as compared to Central/Southern areas (15.6% vs 6.4%, respectively). Machine learning analysis revealed that the most important features in death classification were impaired renal function, elevated C reactive protein and advanced age. These findings were confirmed by multivariable Cox survival analysis (hazard ratio (HR): 8.2; 95% confidence interval (CI) 4.6–14.7 for age ≥85 vs 18–44 y); HR = 4.7; 2.9–7.7 for estimated glomerular filtration rate levels <15 vs ≥ 90 mL/min/1.73 m 2 ; HR = 2.3; 1.5–3.6 for C-reactive protein levels ≥10 vs ≤ 3 mg/L). No relation was found with obesity, tobacco use, cardiovascular disease and related-comorbidities. The associations between these variables and mortality were substantially homogenous across all sub-groups analyses. Conclusions Impaired renal function, elevated C-reactive protein and advanced age were major predictors of in-hospital death in a large cohort of unselected patients with COVID-19, admitted to 30 different clinical centres all over Italy.

In 2007, supplementation with the trace element selenium in a trial was unexpectedly found to be associated with an excess risk of type 2 diabetes. Given the concerns raised by these findings and the large number of recent studies on this topic, we reviewed the available literature with respect to this possible association. In this paper, we assessed the results of both experimental and nonexperimental epidemiologic studies linking selenium with type 2 diabetes incidence. Through a systematic literature search, we retrieved 50 potentially eligible nonexperimental studies and 5 randomized controlled trials published through June 11, 2018. To elucidate the possible dose-response relation, we selected for further analysis those studies that included multiple exposure levels and serum or plasma levels. We computed a pooled summary risk ratio (RR) of diabetes according to selenium exposure in these studies. We also computed a RR for diabetes incidence following supplementation with 200 µg/day of selenium compared with placebo in trials. In the nonexperimental studies, we found a direct relation between selenium exposure and risk of diabetes, with a clear and roughly linear trend in subjects with higher plasma or serum selenium levels, with RR at 140 µg/L of selenium exposure compared with a referent category of < 45 µg/L equal to 3.6 [95% confidence interval (CI) 1.4-9.4]. A dose-response meta-analysis focusing on studies with direct assessment of dietary selenium intake showed a similar trend. In experimental studies, selenium supplementation increased the risk of diabetes by 11% (RR 1.11, 95% CI 1.01-1.22) compared with the placebo-allocated participants, with a higher RR in women than in men. Overall, results from both nonexperimental and experimental studies indicate that selenium may increase the risk of type 2 diabetes across a wide range of exposure levels. The relative increase in risk is small but of possible public health importance because of the high incidence of diabetes and the ubiquity of selenium exposure.

Background Epidemiologic studies, including trials, suggest an association between potassium intake and blood pressure ( BP ). However, the strength and shape of this relationship is uncertain. Methods and Results We performed a meta‐analysis to explore the dose‐response relationship between potassium supplementation and BP in randomized‐controlled trials with a duration ≥4 weeks using the recently developed 1‐stage cubic spline regression model. This model allows use of trials with at least 2 exposure categories. We identified 32 eligible trials. Most were conducted in adults with hypertension using a crossover design and potassium supplementation doses that ranged from 30 to 140 mmol/d. We observed a U‐shaped relationship between 24‐hour active and control arm differences in potassium excretion and BP levels, with weakening of the BP reduction effect above differences of 30 mmol/d and a BP increase above differences ≈80 mmol/d. Achieved potassium excretion analysis also identified a U‐shaped relationship. The BP ‐lowering effects of potassium supplementation were stronger in participants with hypertension and at higher levels of sodium intake. The BP increase with high potassium excretion was noted in participants with antihypertensive drug‐treated hypertension but not in their untreated counterparts. Conclusions We identified a nonlinear relationship between potassium intake and both systolic and diastolic BP , although estimates for BP effects of high potassium intakes should be interpreted with caution because of limited availability of trials. Our findings indicate an adequate intake of potassium is desirable to achieve a lower BP level but suggest excessive potassium supplementation should be avoided, particularly in specific subgroups.