Combination treatment optimization using a pan-cancer pathway model.

The design of efficient combination therapies is a difficult key challenge in the treatment of complex diseases such as cancers. The large heterogeneity of cancers and the large number of available drugs renders exhaustive in vivo or even in vitro investigation of possible treatments impractical. In recent years, sophisticated mechanistic, ordinary differential equation-based pathways models that can predict treatment responses at a molecular level have been developed. However, surprisingly little effort has been put into leveraging these models to find novel therapies. In this paper we use for the first time, to our knowledge, a large-scale state-of-the-art pan-cancer signaling pathway model to identify candidates for novel combination therapies to treat individual cancer cell lines from various tissues (e.g., minimizing proliferation while keeping dosage low to avoid adverse side effects) and populations of heterogeneous cancer cell lines (e.g., minimizing the maximum or average proliferation across the cell lines while keeping dosage low). We also show how our method can be used to optimize the drug combinations used in sequential treatment plans-that is, optimized sequences of potentially different drug combinations-providing additional benefits. In order to solve the treatment optimization problems, we combine the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm with a significantly more scalable sampling scheme for truncated Gaussian distributions, based on a Hamiltonian Monte-Carlo method. These optimization techniques are independent of the signaling pathway model, and can thus be adapted to find treatment candidates for other complex diseases than cancers as well, as long as a suitable predictive model is available.

A Multi-Modal Analysis of the Freezing of Gait Phenomenon in Parkinson's Disease.

BACKGROUND: Freezing of Gait (FOG) is one of the most disabling motor complications of Parkinson's disease, and consists of an episodic inability to move forward, despite the intention to walk. FOG increases the risk of falls and reduces the quality of life of patients and their caregivers. The phenomenon is difficult to appreciate during outpatients visits; hence, its automatic recognition is of great clinical importance. Many types of sensors and different locations on the body have been proposed. However, the advantages of a multi-sensor configuration with respect to a single-sensor one are not clear, whereas this latter would be advisable for use in a non-supervised environment. METHODS: In this study, we used a multi-modal dataset and machine learning algorithms to perform different classifications between FOG and non-FOG periods. Moreover, we explored the relevance of features in the time and frequency domains extracted from inertial sensors, electroencephalogram and skin conductance. We developed both a subject-independent and a subject-dependent algorithm, considering different sensor subsets. RESULTS: The subject-independent and subject-dependent algorithms yielded accuracies of 85% and 88% in the leave-one-subject-out and leave-one-task-out test, respectively. Results suggest that the inertial sensors positioned on the lower limb are generally the most significant in recognizing FOG. Moreover, the performance impairment experienced when using a single tibial accelerometer instead of the optimal multi-modal configuration is limited to 2-3%. CONCLUSIONS: The achieved results disclose the possibility of getting a good FOG recognition using a minimally invasive set-up made of a single inertial sensor. This is very significant in the perspective of implementing a long-term monitoring of patients in their homes, during activities of daily living.

Patterns of Emergency Department visits for acute and chronic diseases during the two pandemic waves in Italy.

BACKGROUND: Evidence is lacking about the impact of subsequent COVID-19 pandemic waves on Emergency Departments (ED). We analyzed the differences in patterns of ED visits in Italy during the two pandemic waves, focusing on changes in accesses for acute and chronic diseases. METHODS: We conducted a retrospective study using data from a metropolitan area in northern Italy that includes twelve ED. We analyzed weekly trends in non-COVID-19 ED visits during the first (FW) and second wave (SW) of the pandemic. Incidence rate ratios (IRRs) of triage codes, patient destination, and cause-specific ED visits in the FW and SW of the year 2020 vs. 2019 were estimated using Poisson regression models. MAIN FINDINGS: We found a significant decrease of ED visits by triage code, which was more marked for low priority codes and during the FW. We found an increased share of hospitalizations compared to home discharges both in the FW and in the SW. ED visits for acute and chronic conditions decreased during the FW, ranging, from -70% for injuries (IRR = 0.2862, p < 0.001) to -50% and - 60% for ischemic heart disease and heart failure. CONCLUSIONS: The two pandemic waves led to a selection of patients with higher and more urgent needs of acute hospital care. These findings should lead to investigate how to improve systems' capacity to manage changes in population needs.

Overexpression of the Cytokine BAFF and Autoimmunity Risk.

BACKGROUND: Genomewide association studies of autoimmune diseases have mapped hundreds of susceptibility regions in the genome. However, only for a few association signals has the causal gene been identified, and for even fewer have the causal variant and underlying mechanism been defined. Coincident associations of DNA variants affecting both the risk of autoimmune disease and quantitative immune variables provide an informative route to explore disease mechanisms and drug-targetable pathways. METHODS: Using case-control samples from Sardinia, Italy, we performed a genomewide association study in multiple sclerosis followed by TNFSF13B locus-specific association testing in systemic lupus erythematosus (SLE). Extensive phenotyping of quantitative immune variables, sequence-based fine mapping, cross-population and cross-phenotype analyses, and gene-expression studies were used to identify the causal variant and elucidate its mechanism of action. Signatures of positive selection were also investigated. RESULTS: A variant in TNFSF13B, encoding the cytokine and drug target B-cell activating factor (BAFF), was associated with multiple sclerosis as well as SLE. The disease-risk allele was also associated with up-regulated humoral immunity through increased levels of soluble BAFF, B lymphocytes, and immunoglobulins. The causal variant was identified: an insertion-deletion variant, GCTGT→A (in which A is the risk allele), yielded a shorter transcript that escaped microRNA inhibition and increased production of soluble BAFF, which in turn up-regulated humoral immunity. Population genetic signatures indicated that this autoimmunity variant has been evolutionarily advantageous, most likely by augmenting resistance to malaria. CONCLUSIONS: A TNFSF13B variant was associated with multiple sclerosis and SLE, and its effects were clarified at the population, cellular, and molecular levels. (Funded by the Italian Foundation for Multiple Sclerosis and others.).

Increased cortical lesion load and intrathecal inflammation is associated with oligoclonal bands in multiple sclerosis patients: a combined CSF and MRI study.

BACKGROUND: Although IgG oligoclonal bands (OCBs) in the cerebrospinal fluid (CSF) are a frequent phenomenon in multiple sclerosis (MS) patients, their relationship with grey matter lesions, intrathecal/meningeal inflammation and clinical evolution has not been clarified yet. The aim of our study was to assess the relationship between the OCBs, the inflammatory/neurodegenerative CSF profile at diagnosis, the cortical lesion load and the clinical evolution after 10 years. METHODS: This is a 10-year observational, cross-sectional study based on a combined MRI, cognitive and CSF profiling of the examined patients. Forty consecutive OCB-negative (OCB-) and 50 OCB-positive (OCB+) MS patients were included in this study. Both groups had mean disease duration of 10 years and were age and gender matched. Each patient underwent neurological and neuropsychological evaluation and 3-T MRI. Analysis of the presence and levels of 28 inflammatory mediators was performed in the CSF obtained from 10 OCB- MS, 11 OCB+ MS and 10 patients with other neurological conditions. RESULTS: Increased number of CLs was found in OCB+ compared to OCB- patients (p < 0.0001), whereas no difference was found in white matter lesion (WML) load (p = 0.36). The occurrence of OCB was also associated with increased levels of neurofilament light chains and of several inflammatory mediators linked to B lymphocyte activity and lymphoid-neogenesis (CXCL13, CXCL12, CXCL10, TNFSF13, TNFSF13B, IL6, IL10) and other pro-inflammatory molecules, such as IFN-γ, TNF, MMP2, GM-CSF, osteopontin and sCD163. Finally, the occurrence of OCB was found associated with poor prognosis, from both physical and cognitive points of view. CONCLUSIONS: OCB at MS onset are associated with more severe GM pathology and with a more severe physical disability and cognitive impairment after 10 years. Increased levels of cytokines linked to B cell activation, lymphoid-neogenesis, and pro-inflammatory immune response in the CSF of OCB+ patients support the hypothesis of crucial role played by compartmentalized, intrathecal B cell response in the pathogenesis of CLs and OCB production.

Dimethyl fumarate: a possible exit strategy from natalizumab treatment in patients with multiple sclerosis at risk for severe adverse events.

INTRODUCTION: Among disease-modifying treatments for multiple sclerosis, natalizumab (NTZ) is highly effective, well tolerated and generally safe. Major concerns regard the risk of developing progressive multifocal leukoencephalopathy (PML), and the occurrence of rebounds or disease activity after its discontinuation. The aim of this study was to explore the efficacy of dimethyl fumarate (DMF) in preventing disease reactivation after NTZ discontinuation. METHODS: Thirty-nine patients with relapsing remitting multiple sclerosis, at high risk of PML, were switched from NTZ to DMF and underwent neurological and 3T MRI monitoring for 2 years. Clinical and MRI data regarding the 2-year period preceding NTZ treatment, the 2 years of NTZ treatment and the 2 years of DMF were collected. RESULTS: During the DMF phase, among the 39 patients, one or more relapses occurred in five patients (12.8%), increased disability progression in 4 (10.3%) and MRI activity in 8 (20.5%). Post-NTZ rebound effect was observed only in one patient. Overall, only two dropouts (one rebound activity and one gastrointestinal side effect) were registered and almost 80% of the patients have still no evidence of disease activity at the end of DMF treatment. The multiple linear regression model revealed that the number of relapses and MRI parameters before DMF treatment were good predictors of disease activity during treatment with DMF. DISCUSSION: DMF appeared generally safe and no carryover PML among investigated cases was observed. Although DMF did not eliminate the possibility of disease reactivation, it seems anyway a promising drug for those patients who shall discontinue NTZ. The clinical and radiological activity preceding the DMF treatment might be used as a prognostic marker of therapy response.

The burden of multiple sclerosis variants in continental Italians and Sardinians.

BACKGROUND: Recent studies identified > 100 non-HLA (human leukocyte antigen) multiple sclerosis (MS) susceptibility variants in Northern European populations, but their role in Southern Europeans is largely unexplored. OBJECTIVE: We aimed to investigate the cumulative impact of those variants in two Mediterranean populations: Continental Italians and Sardinians. METHODS: We calculated four weighted Genetic Risk Scores (wGRS), using up to 102 non-HLA MS risk variants and 5 HLA MS susceptibility markers in 1691 patients and 2194 controls from continental Italy; and 2861 patients and 3034 controls from Sardinia. We then assessed the differences between populations using Nagelkerke's R(2) and the area under the Receiver Operating Characteristic (ROC) curves. RESULTS: As expected, the genetic burden (mean wGRS value) was significantly higher in MS patients than in controls, in both populations. Of note, the burden was significantly higher in Sardinians. Conversely, the proportion of variability explained and the predictive power were significantly higher in continental Italians. Notably, within the Sardinian patients, we also observed a significantly higher burden of non-HLA variants in individuals who do not carry HLA risk alleles. CONCLUSIONS: The observed differences in MS genetic burden between the two Mediterranean populations highlight the need for more genetic studies in South Europeans, to further expand the knowledge of MS genetics.

Exercise-induced modulation of Interferon-signature: a therapeutic route toward management of Systemic Lupus Erythematosus.

Systemic Lupus Erythematosus (SLE) is a multisystemic autoimmune disorder characterized by flares-ups/remissions with a complex clinical picture related to disease severity and organ/tissue injury, which, if left untreated, may result in permanent damage. Enhanced fatigue and pain perception, worsened quality of life (QoL) and outcome are constant, albeit symptoms may differ. An aberrant SLE immunoprofiling, note as "interferon (IFN)α-signature", is acknowledged to break immunotolerance. Recently, a deregulated "IFNγ-signature" is suggested to silently precede/trigger IFNα profile before clinical manifestations. IFNα- and IFNγ-over-signaling merge in cytokine/chemokine overexpression exacerbating autoimmunity. Remission achievement and QoL improvement are the main goals. The current therapy (i.e., corticosteroids, immunosuppressants) aims to downregulate immune over-response. Exercise could be a safe treatment due to its ever-emerging ability to shape and re-balance immune system without harmful side-effects; in addition, it improves cardiorespiratory capacity and musculoskeletal strength/power, usually impaired in SLE. Nevertheless, exercise is not yet included in SLE care plans. Furthermore, due to the fear to worsening pain/fatigue, SLE subjects experience kinesiophobia and sedentary lifestyle, worsening physical health. Training SLE patients to exercise is mandatory to fight inactive behavior and ameliorate health. This review aims to focus the attention on the role of exercise as a non-pharmacological therapy in SLE, considering its ability to mitigate IFN-signature and rebalance (auto)immune response. To this purpose, the significance of IFNα- and IFNγ-signaling in SLE etiopathogenesis will be addressed first and discussed thereafter as biotarget of exercise. Comments are addressed on the need to make aware all SLE care professional figures to promote exercise for health patients.

Development and internal validation of a multivariable model for the prediction of the probability of 1-year readmission to the emergency department for acute alcohol intoxication.

To develop and internally validate a multivariable logistic regression model (LRM) for the prediction of the probability of 1-year readmission to the emergency department (ED) in patients with acute alcohol intoxication (AAI). We developed and internally validated the LRM on a previously analyzed retrospective cohort of 3304 patients with AAI admitted to the ED of the Sant'Orsola-Malpighi Hospital (Bologna, Italy). The benchmark LRM employed readmission to the same ED for AAI within 1 year as the binary outcome, age as a continuous predictor, and sex, alcohol use disorder, substance use disorder, at least one previous admission for trauma, mental or behavioral disease, and homelessness as the binary predictors. Optimism correction was performed using the bootstrap on 1000 samples without replacement. The benchmark LRM was gradually simplified to get the most parsimonious LRM with similar optimism-corrected overall fit, discrimination and calibration. The 1-year readmission rate was 15.7% (95% CI 14.4-16.9%). A reduced LRM based on sex, age, at least one previous admission for trauma, mental or behavioral disease, and homelessness, performed nearly as well as the benchmark LRM. The reduced LRM had the following optimism-corrected metrics: scaled Brier score 17.0%, C-statistic 0.799 (95% CI 0.778 to 0.821), calibration in the large 0.000 (95% CI - 0.099 to 0.099), calibration slope 0.985 (95% CI 0.893 to 1.088), and an acceptably accurate calibration plot. An LRM based on sex, age, at least one previous admission for trauma, mental or behavioral disease, and homelessness can be used to estimate the probability of 1-year readmission to ED for AAI. To begin proving its clinical utility, this LRM should be validated in external cohorts.

Mortality and its association with chronic alcohol-related diseases in patients admitted to the emergency department for acute alcoholic intoxication: retrospective cohort study.

We assessed long-term mortality and its association with chronic alcohol-related diseases in patients admitted to the emergency department (ED) because of acute alcoholic intoxication (AAI). A retrospective cohort study was performed at the ED of Sant'Orsola-Malpighi Hospital, Bologna, Italy. 3304 patients, corresponding to 6415 admissions for AAI, who accessed the ED from January 1, 2005, to December 31, 2017, were studied. The ED electronic registry system was used to assess living status on 08 May 2020 and to obtain the prespecified potential predictors, i.e., age at first admission, sex, alcohol use disorder (AUD), substance use disorder (SUD), more than 1 admission to ED for trauma, mental and behavioral disorders, neurological disorders, and cardiovascular disease. The median follow-up time was 9.3 years and the time on risk was 30,053 person years (PY) with a death rate corresponding to 4.42 (95% CI 3.74-5.26) per 1000 PY (n = 133 deaths). The death rate was higher in patients with AUD (17.30) than in those without AUD (1.98) and in those with SUD (13.58) than in those without SUD (3.80). Lastly, there was a clearly higher death rate among AUD+ SUD+ (20.89) compared to AUD-SUD-patients (1.74). At multivariable Cox regression, AUD, SUD, and liver cirrhosis were strong and independent predictors of time-to-death. Using standardized mortality ratios, a clear excess of mortality was evident for all the age bands from (40-45] to (60-65] years. Mortality is higher in AAI than in the general population and chronic alcohol-related diseases are strongly associated with it.

Are "cases", "waves", "tests" and "modeling" deceiving indicators to describe the COVID-19 pandemic?

This commentary elaborates on different methodological aspects complicating the interpretation of epidemiological data related to the current COVID-19 pandemic, thus preventing reliable within and across-country estimates. Firstly, an inaccuracy of epidemiological data maybe arguably be attributed to passive surveillance, a relatively long incubation period during which infected individuals can still shed high loads of virus into the surrounding environment and the very high proportion of cases not even developing signs and/or symptoms of COVID-19. The latter is also the major reason for the inappropriateness of the abused "wave" wording, which gives the idea that health system starts from scratch to respond between "peaks". Clinical data for case-management on the other hand often requires complex technology in order to merge and clean data from health care facilities. Decision-making is often further derailed by the overuse of epidemiological modeling: precise aspects related to transmissibility, clinical course of COVID-19 and effectiveness of the public health and social measures are heavily influenced by unbeknownst and unpredictable human behaviors and modelers try to overcome missing epidemiological information by relying on poorly precise or questionable assumptions. Therefore the COVID-9 pandemic may provide a valuable opportunity to rethink how we are dealing with the very basic principles of epidemiology as well as risk communication issues related to such an unprecedented emergency situation.

Human-level play in the game of Diplomacy by combining language models with strategic reasoning.

Despite much progress in training artificial intelligence (AI) systems to imitate human language, building agents that use language to communicate intentionally with humans in interactive environments remains a major challenge. We introduce Cicero, the first AI agent to achieve human-level performance in Diplomacy, a strategy game involving both cooperation and competition that emphasizes natural language negotiation and tactical coordination between seven players. Cicero integrates a language model with planning and reinforcement learning algorithms by inferring players' beliefs and intentions from its conversations and generating dialogue in pursuit of its plans. Across 40 games of an anonymous online Diplomacy league, Cicero achieved more than double the average score of the human players and ranked in the top 10% of participants who played more than one game.

Cross-sectional analysis of the humoral response after SARS-CoV-2 vaccination in Sardinian multiple sclerosis patients, a follow-up study.

Monitoring immune responses to SARS-CoV-2 vaccination and its clinical efficacy over time in Multiple Sclerosis (MS) patients treated with disease-modifying therapies (DMTs) help to establish the optimal strategies to ensure adequate COVID-19 protection without compromising disease control offered by DMTs. Following our previous observations on the humoral response one month after two doses of BNT162b2 vaccine (T1) in MS patients differently treated, here we present a cross-sectional and longitudinal follow-up analysis six months following vaccination (T2, n=662) and one month following the first booster (T3, n=185). Consistent with results at T1, humoral responses were decreased in MS patients treated with fingolimod and anti-CD20 therapies compared with untreated patients also at the time points considered here (T2 and T3). Interestingly, a strong upregulation one month after the booster was observed in patients under every DMTs analyzed, including those treated with fingolimod and anti-CD20 therapies. Although patients taking these latter therapies had a higher rate of COVID-19 infection five months after the first booster, only mild symptoms that did not require hospitalization were reported for all the DMTs analyzed here. Based on these findings we anticipate that additional vaccine booster shots will likely further improve immune responses and COVID-19 protection in MS patients treated with any DMT.

Violence Against Healthcare: A Public Health Issue beyond Conflict Settings.

A 3-year analysis released in August 2021 by the WHO indicated that more than 700 healthcare workers and patients have died (2,000 injured) as a result of attacks against health facilities since 2017. The COVID-19 pandemic has made the risks even worse for doctors, nurses, and support staff, unfortunately. According to the latest figures from the International Committee of the Red Cross, 848 COVID-19-related violent incidents were recorded in 2020, and this is likely an underrepresentation of a much more widespread phenomenon. In response to rises in COVID-19-related attacks against healthcare, some countries have taken action. In Algeria, for instance, the penal code was amended to increase protection for healthcare workers against attacks and to punish individuals who damage health facilities. In the United Kingdom, the police, crime, sentencing, and courts bill proposed increased the maximum penalty from 12 months to 2 years in prison for anyone who assaults an emergency worker. Measures taken by countries represent a good practical way to counteract this crisis within COVID-19. However, we stress the importance of primary prevention with the use of communication: social media and other communication channels are fundamentally important to combat violence against health professionals, both to inform the population with quality data and to disseminate campaigns to prevent these acts.

CovHos, a New Score to Predict the Need of Hospitalization for Coronavirus Disease 2019 (COVID-19) Patients at the Emergency Department.

INTRODUCTION AND AIM: As first receivers of suspected coronavirus disease 2019 (COVID-19) patients, clinicians of the Emergency Department (ED) have to rapidly perform the first clinical assessment evaluating the intensity of care needed. So far, clear management guidelines still lack. We identified variables associated with hospitalization in order to give a quick tool to assist clinicians in stratifying cases based on the severity at their arrival at the ED and in predicting the need for hospital care.  Methods: This is a monocentric observational prospective study enrolling COVID-19 patients. A score for hospitalization prediction (CovHos Score) was created using variables associated with hospitalization at multivariate analysis and then validated on an internal subsequent cohort. RESULTS: A total of 667 patients were included; 465 (69.7%) were hospitalized and 108 (16.2%) died at 30-days follow-up. In a multivariate analysis, male sex, age>65, alveolar-to-arterial oxygen gradient percentage increase compared to that expected for age, neutrophils/lymphocytes ratio and C-reactive protein levels were significantly associated with a higher rate of hospital admission. A CovHos score cut-off of 12 points predicted hospitalization with 85% sensitivity and 82.4 % specificity (area under a receiver operating characteristic curve [AUROC] = 0.909, 95% CI 0.884 - 0.935). Similar results were obtained in the validation court. A cut-off of 22 has 79% sensitivity and 77% specificity in predicting mortality (AUROC = 0.824; 95% CI 0.782-0.866); sensitivity and specificity were respectively 71.4% and 71.3% in the validation group. CONCLUSIONS: Although medical judgment still remains crucial, the CovHos score is an effective tool to assist emergency clinicians in predicting the need for hospitalization or to optimize allocation in a shortage of hospital resources.

Role of ROX index in the first assessment of COVID-19 patients in the emergency department.

During the first outbreak of Coronavirus disease 2019 (COVID-19) Emergency Departments (EDs) were overcrowded. Hence, the need for a rapid and simple tool to support clinical decisions, such as the ROX index (Respiratory rate - OXygenation), defined as the ratio of peripheral oxygen saturation and fraction of inspired oxygen, to respiratory rate. The aim of the study was to evaluate the accuracy of the ROX index in predicting hospitalization and mortality in patients with a diagnosis of COVID-19 in the ED. The secondary outcomes were to assess the number of readmissions and the variations in the ROX index between the first and the second admission. This was an observational prospective monocentric study, carried out in the ED of Sant'Orsola-Malpighi Hospital in Bologna, Italy. Five hundred and fifty-four consecutive patients with COVID-19 were enrolled and the ROX index was calculated. Patients were followed until hospital discharge or death. A ROX index value < 25.7 was associated with hospitalization (area under the curve [AUC] = 0.737, 95% CI 0.696-0.779, p < 0.001). The ROX index < 22.3 was statistically related to higher 30-day mortality (AUC = 0.764, 95% CI 0.708-0.820, p < 0.001). Eight patients were discharged and returned to the ED within the subsequent 7 days, their mean ROX index was 30.3 (6.2; range 21.9-39.4) at the first assessment and 24.6 (5.5; 14.5-29.5) at the second assessment, (p = 0.012). The ROX index, together with laboratory, imaging and clinical findings, correlated with the need for hospital admission, mechanical ventilation and mortality risk in COVID-19 patients.

Non-COVID-19 patients in times of pandemic: Emergency department visits, hospitalizations and cause-specific mortality in Northern Italy.

The COVID-19 pandemic forced healthcare services organization to adjust to mutating healthcare needs. Not exhaustive data are available on the consequences of this on non-COVID-19 patients. The aim of this study was to assess the impact of the pandemic on non-COVID-19 patients living in a one-million inhabitants' area in Northern Italy (Bologna Metropolitan Area-BMA), analyzing time trends of Emergency Department (ED) visits, hospitalizations and mortality. We conducted a retrospective observational study using data extracted from BMA healthcare informative systems. Weekly trends of ED visits, hospitalizations, in- and out-of-hospital, all-cause and cause-specific mortality between December 1st, 2019 to May 31st, 2020, were compared with those of the same period of the previous year. Non-COVID-19 ED visits and hospitalizations showed a stable trend until the first Italian case of COVID-19 has been recorded, on February 19th, 2020, when they dropped simultaneously. The reduction of ED visits was observed in all age groups and across all severity and diagnosis groups. In the lockdown period a significant increase was found in overall out-of-hospital mortality (43.2%) and cause-specific out-of-hospital mortality related to neoplasms (76.7%), endocrine, nutritional and metabolic (79.5%) as well as cardiovascular (32.7%) diseases. The pandemic caused a sudden drop of ED visits and hospitalizations of non-COVID-19 patients during the lockdown period, and a concurrent increase in out-of-hospital mortality mainly driven by deaths for neoplasms, cardiovascular and endocrine diseases. As recurrencies of the COVID-19 pandemic are underway, the scenario described in this study might be useful to understand both the population reaction and the healthcare system response at the early phases of the pandemic in terms of reduced demand of care and systems capability in intercepting it.

Judging health care priority in emergency situations: Patient facial appearance matters.

RATIONALE: Extensive research has shown that implicit trait inferences from facial appearance can bias everyday life in a pervasive way, influencing our decisions in different social contexts such as mate choice, political vote and criminal sentence. In situations characterized by time pressure and scant information, decisions based on inferences from facial appearance may have particularly critical and serious consequences, such as in emergency healthcare. No studies today have investigated this aspect in an actual emergency. OBJECTIVE: The aim of the present study was to go beyond this gap and to determine whether implicit inferences from patients' facial appearance could be predictive of disparities in clinical evaluations and priority of treatment. METHODS: In total, 183 cases of patients were evaluated by independent judges at zero acquaintance on the basis of different implicit facial appearance-based inferences, including trustworthiness and distress. Color-based priority code (White, Green, or Yellow) attributed by the triage nurse at the end of the registration process were recorded. RESULTS: Our results showed that more trustworthy- and distressed- looking patients' faces have been associated with a higher priority code. CONCLUSIONS: The present study shows that specific facial appearance-based inferences influence the attribution of priority code in healthcare that require quick decisions based on scarce clinical information such as in emergency. These results suggest the importance to bring to the attention of the healthcare professionals' the possibility of being victims of implicit inferences, and prompt to design educational interventions capable to increase their awareness of this bias in clinical evaluation.

Changing therapeutic strategies and persistence to disease-modifying treatments in a population of multiple sclerosis patients from Veneto region, Italy.

BACKGROUND: The availability of new disease-modifying treatments (DMTs) in the last years has changed the therapeutic strategies used in Multiple Sclerosis (MS). We aimed to describe trend in DMTs utilization and persistence to treatment in a large sample of patients attending 10 MS centres from four provinces of Veneto, Italy. METHODS: Demographic, clinical and DMTs information of patients regularly followed from January 2011 to August 2018 were recorded and analysed. Persistence at 12, 24 months and at last follow-up was assessed by Kaplan Meier survival analysis. Multivariable Cox- proportional hazard model was used to identify predictors of persistence. RESULTS: Of 3025 MS patients 65.7% were in treatment al last follow-up. Dimethylfumarate (DMF) was the most prescribed single drug among first-line and fingolimod among second-line DMTs. In the cohort of 1391 cases starting any DMT since 2011 12.9% stopped within 6 months, 24% within 12 and 40.3% within 24 months. Disease duration > 5 years at therapy start was predictive of greater risk of discontinuation, while age and sex were not. DMF use was predictive of higher persistence at 12 and 24 months, but not at last follow-up when azathioprine and glatiramer acetate showed the highest persistence compared to other DMTs. Side effects represented the main reason of discontinuation. CONCLUSION: The use of the new oral DMTs greatly increased since their approval but persistence in the long-term is not better than with old drugs. The treatment choice is still a challenge both for patients and their doctors.

The HEART score with high-sensitive troponin T at presentation: ruling out patients with chest pain in the emergency room.

The HEART score is a simple scoring system, ranging from 0 to 10, specifically developed for risk stratification of patients with undifferentiated chest pain. It has been validated for the conventional troponin, but not for high-sensitive troponin. We assess a modified version of the HEART score using a single high-sensitivity troponin T dosage at presentation, regardless of symptom duration, and with different ECG criteria to evaluate if the patients with a low HEART score could be safely discharged early. The secondary aim was to confirm a statistically significant difference in each HEART score group (low 0-3, intermediate 4-6, high 7-10) in the occurrence of major adverse cardiac events at 30 and 180 days. We retrospectively analyzed the HEART score of 1597 consecutive patients admitted to the Emergency Department of our Hospital for chest pain between January 1 and June 30, 2014. Of these, 190 did not meet the inclusion criteria and 29 were lost to follow-up. None of the 512 (37.2 %) patients with a low HEART score had an event within 180 days. The difference between the cumulative incidences of events in the three HEART score groups was statistically significant (P < 0.0001). We demonstrate that it might be possible to safely discharge Emergency Department chest pain patients with a low modified HEART score after an initial determination of high-sensitive troponin T, without a prolonged observation period or an additional cardiac testing.