Urban freight distribution and innovative last-mile solutions from a traffic perspective

Urban population growth, the rise of e-commerce, and the increased need for economically and environmentally sustainable solutions represent urban freight distribution’s biggest challenges. Traffic and city logistics are often two sides of the same coin, as congestion affects city freight movements and vice versa. For this reason, it is important to develop comprehensive mobility and traffic management solutions that consider both systems. During the last decade, technology improvements in wireless communication, computational and sensing technologies, have paved the way to a series of mobility and transportation options (e.g., crowdshipping and driverless vehicles) that could transform the landscape of last-mile delivery. The main contribution of this dissertation consists of modeling urban freight impacts on traffic and investigating the potential implications of innovative last-mile solutions. The first part of this dissertation focuses on the feedback between freight movements and traffic, taking into consideration the impact of passenger vehicles on commercial vehicles, and vice versa. In order to achieve this goal, it is necessary to model trucks’ movements and loading/unloading operations with ad-hoc traffic simulations. Most of existing research has focused on analytical, static, or microscopic models, that either lack accuracy or scalability. Hence, this dissertation creates algorithms that couple existing macroscopic traffic flow models with the microscopic behavior of delivery vehicles. This issue is investigated both at single-link and network levels, by means of a suitable simulation framework. In both cases, applications of the modeling approach for freight traffic and freight demand management are shown. In the second part of this dissertation the potential impacts of last-mile delivery solutions are evaluated using the developed simulation framework. First, the impacts of alternative City Logistics solutions, such as off-peak deliveries and access restrictions are investigated. Then, the developed modeling framework is extended to investigate a crowdsourced service for parcel deliveries. The effects on traffic and emissions are investigated for the adoption of crowdshipping by carriers delivering parcels in the city center of Rome, Italy. The externalities associated with several strategic (chosen mode) and operational (detour length, parking behavior, and traffic conditions) aspects of this service are analyzed by means of simulation in realistic settings. Some results allow preliminary considerations about the effects of last-mile delivery solution that can been confirmed in other studies. Other findings, instead, are in line with studies from previous literature that adopted different approaches. The practice of off-peak deliveries, consisting in shifting part of the trips and operations to less congested hours of the day (typically evening and night) has proved to be an effective solution to freight-related congestion in urban settings. Restricting from deliveries specific links or sets of links, instead, could be beneficial only in some situations. Alternative crowdshipping implementation features, such as the transportation mode choice, but also operational aspects (such as availability of parking, optimization of existing trips, and implementation during off-peak hours) can also considerably influence the final traffic and emissions impacts of this service.Civil, Architectural, and Environmental Engineerin

Colorectal Cancer Stage at Diagnosis Before vs During the COVID-19 Pandemic in Italy

IMPORTANCE Delays in screening programs and the reluctance of patients to seek medical attention because of the outbreak of SARS-CoV-2 could be associated with the risk of more advanced colorectal cancers at diagnosis. OBJECTIVE To evaluate whether the SARS-CoV-2 pandemic was associated with more advanced oncologic stage and change in clinical presentation for patients with colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS This retrospective, multicenter cohort study included all 17 938 adult patients who underwent surgery for colorectal cancer from March 1, 2020, to December 31, 2021 (pandemic period), and from January 1, 2018, to February 29, 2020 (prepandemic period), in 81 participating centers in Italy, including tertiary centers and community hospitals. Follow-up was 30 days from surgery. EXPOSURES Any type of surgical procedure for colorectal cancer, including explorative surgery, palliative procedures, and atypical or segmental resections. MAIN OUTCOMES AND MEASURES The primary outcome was advanced stage of colorectal cancer at diagnosis. Secondary outcomes were distant metastasis, T4 stage, aggressive biology (defined as cancer with at least 1 of the following characteristics: signet ring cells, mucinous tumor, budding, lymphovascular invasion, perineural invasion, and lymphangitis), stenotic lesion, emergency surgery, and palliative surgery. The independent association between the pandemic period and the outcomes was assessed using multivariate random-effects logistic regression, with hospital as the cluster variable. RESULTS A total of 17 938 patients (10 007 men [55.8%]; mean [SD] age, 70.6 [12.2] years) underwent surgery for colorectal cancer: 7796 (43.5%) during the pandemic period and 10 142 (56.5%) during the prepandemic period. Logistic regression indicated that the pandemic period was significantly associated with an increased rate of advanced-stage colorectal cancer (odds ratio [OR], 1.07; 95%CI, 1.01-1.13; P = .03), aggressive biology (OR, 1.32; 95%CI, 1.15-1.53; P < .001), and stenotic lesions (OR, 1.15; 95%CI, 1.01-1.31; P = .03). CONCLUSIONS AND RELEVANCE This cohort study suggests a significant association between the SARS-CoV-2 pandemic and the risk of a more advanced oncologic stage at diagnosis among patients undergoing surgery for colorectal cancer and might indicate a potential reduction of survival for these patients

COVID-19 ICU mortality prediction: a machine learning approach using SuperLearner algorithm

Background: Since the beginning of coronavirus disease 2019 (COVID-19), the development of predictive models has sparked relevant interest due to the initial lack of knowledge about diagnosis, treatment, and prognosis. The present study aimed at developing a model, through a machine learning approach, to predict intensive care unit (ICU) mortality in COVID-19 patients based on predefined clinical parameters. Results: Observational multicenter cohort study. All COVID-19 adult patients admitted to 25 ICUs belonging to the VENETO ICU network (February 28th 2020-april 4th 2021) were enrolled. Patients admitted to the ICUs before 4th March 2021 were used for model training (“training set”), while patients admitted after the 5th of March 2021 were used for external validation (“test set 1”). A further group of patients (“test set 2”), admitted to the ICU of IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan, was used for external validation. A SuperLearner machine learning algorithm was applied for model development, and both internal and external validation was performed. Clinical variables available for the model were (i) age, gender, sequential organ failure assessment score, Charlson Comorbidity Index score (not adjusted for age), Palliative Performance Score; (ii) need of invasive mechanical ventilation, non-invasive mechanical ventilation, O2 therapy, vasoactive agents, extracorporeal membrane oxygenation, continuous venous-venous hemofiltration, tracheostomy, re-intubation, prone position during ICU stay; and (iii) re-admission in ICU. One thousand two hundred ninety-three (80%) patients were included in the “training set”, while 124 (8%) and 199 (12%) patients were included in the “test set 1” and “test set 2,” respectively. Three different predictive models were developed. Each model included different sets of clinical variables. The three models showed similar predictive performances, with a training balanced accuracy that ranged between 0.72 and 0.90, while the cross-validation performance ranged from 0.75 to 0.85. Age was the leading predictor for all the considered model

Impact of asthma and comorbid allergic rhinitis on quality of life and control in patients of Italian general practitioners.

OBJECTIVE: Asthma is a disease with elevated prevalence within the general population. Although general practitioners (GPs) are among the first health-care professionals to whom patients refer for their symptoms, there are few evaluations of this disease based on data provided by the GPs. The aim of this observational study is to assess the impact of asthma and comorbid allergic rhinitis on individual/social burden, quality of life, and disease control in asthmatic patients of Italian GPs. METHODS: Throughout Italy, 107 GPs enrolled 995 patients diagnosed with asthma and using anti-asthmatic drug prescriptions, or with asthma-like symptoms during the previous 12 months. Data were collected through questionnaires filled out by GPs and patients. RESULTS: Of the 995 asthmatic patients, 60.6% had concomitant allergic rhinitis (R+A), 39.4% had asthma alone. The latter, compared to those with R+A, showed significantly lower prevalence of intermittent asthma (37.5% vs. 55.6%) and higher prevalence of mild, moderate, and severe persistent asthma (28.4% vs. 23.2%, 28.7% vs. 18.8%, and 5.4% vs 2.4%, respectively). Individual/social burden due to asthma was frequent and increased with disease severity: 87.5% of severe persistent asthma patients reported at least one medical consultation in the last 12 months, 37.5% emergency department visits, 26.7% hospitalization, and 62.5% limitations in daily activities. Control and quality of life were inversely associated with disease severity and were worse in patients with R+A than in those with asthma alone. CONCLUSIONS: This study showed the negative impact of high severity levels and comorbid allergic rhinitis on quality of life of asthmatic patients and on individual/social burden due to asthma in an Italian GPs setting

NEUROBIOLOGICAL CORRELATES OF ALPHA-TOCOPHEROL ANTIEPILEPTOGENIC EFFECTS AND microRNA EXPRESSION MODULATION IN A RAT MODEL OF KAINATE-INDUCED SEIZURES

Seizure-triggered maladaptive neural plasticity and neuroinflammation occur during the latent period as a key underlying event in epilepsy chronicization. Previously, we showed that α-tocopherol (α-T) reduces hippocampal neuroglial activation and neurodegeneration in the rat model of kainic acid (KA)-induced status epilepticus (SE). These findings allowed us to postulate an antiepileptogenic potential for α-T in hippocampal excitotoxicity, in line with clinical evidence showing that α-T improves seizure control in drug-resistant patients. To explore neurobiological correlates of the α-T antiepileptogenic role, rats were injected with such vitamin during the latent period starting right after KA-induced SE, and the effects on circuitry excitability, neuroinflammation, neuronal death, and microRNA (miRNA) expression were investigated in the hippocampus. Results show that in α-T-treated epileptic rats, (1) the number of population spikes elicited by pyramidal neurons, as well as the latency to the onset of epileptiform-like network activity recover to control levels; (2) neuronal death is almost prevented; (3) down-regulation of claudin, a blood-brain barrier protein, is fully reversed; (4) neuroinflammation processes are quenched (as indicated by the decrease of TNF-α, IL-1β, GFAP, IBA-1, and increase of IL-6); (5) miR-146a, miR-124, and miR-126 expression is coherently modulated in hippocampus and serum by α-T. These findings support the potential of a timely intervention with α-T in clinical management of SE to reduce epileptogenesis, thus preventing chronic epilepsy development. In addition, we suggest that the analysis of miRNA levels in serum could provide clinicians with a tool to evaluate disease evolution and the efficacy of α-T therapy in SE

Effect of centre volume on pathological outcomes and postoperative complications after surgery for colorectal cancer: results of a multicentre national study

Background: The association between volume, complications and pathological outcomes is still under debate regarding colorectal cancer surgery. The aim of the study was to assess the association between centre volume and severe complications, mortality, less-than-radical oncologic surgery, and indications for neoadjuvant therapy.Methods: Retrospective analysis of 16,883 colorectal cancer cases from 80 centres (2018-2021). Outcomes: 30-day mortality; Clavien-Dindo grade >2 complications; removal of >= 12 lymph nodes; non-radical resection; neoadjuvant therapy. Quartiles of hospital volumes were classified as LOW, MEDIUM, HIGH, and VERY HIGH. Independent predictors, both overall and for rectal cancer, were evaluated using logistic regression including age, gender, AJCC stage and cancer site.Results: LOW-volume centres reported a higher rate of severe postoperative complications (OR 1.50, 95% c.i. 1.15-1.096, P = 0.003). The rate of >= 12 lymph nodes removed in LOW-volume (OR 0.68, 95% c.i. 0.56-0.85, P = 12 lymph nodes removed was lower in LOW-volume than in VERY HIGH-volume centres (OR 0.57, 95% c.i. 0.41-0.80, P = 0.001). A lower rate of neoadjuvant chemoradiation was associated with HIGH (OR 0.66, 95% c.i. 0.56-0.77, P < 0.001), MEDIUM (OR 0.75, 95% c.i. 0.60-0.92, P = 0.006), and LOW (OR 0.70, 95% c.i. 0.52-0.94, P = 0.019) volume centres (vs. VERY HIGH).Conclusion: Colorectal cancer surgery in low-volume centres is at higher risk of suboptimal management, poor postoperative outcomes, and less-than-adequate oncologic resections. Centralisation of rectal cancer cases should be taken into consideration to optimise the outcomes

Impact of asthma and comorbid allergic rhinitis on quality of life and control in patients of Italian general practitioners.

OBJECTIVE: Asthma is a disease with elevated prevalence within the general population. Although general practitioners (GPs) are among the first health-care professionals to whom patients refer for their symptoms, there are few evaluations of this disease based on data provided by the GPs. The aim of this observational study is to assess the impact of asthma and comorbid allergic rhinitis on individual/social burden, quality of life, and disease control in asthmatic patients of Italian GPs. METHODS: Throughout Italy, 107 GPs enrolled 995 patients diagnosed with asthma and using anti-asthmatic drug prescriptions, or with asthma-like symptoms during the previous 12 months. Data were collected through questionnaires filled out by GPs and patients. RESULTS: Of the 995 asthmatic patients, 60.6% had concomitant allergic rhinitis (R+A), 39.4% had asthma alone. The latter, compared to those with R+A, showed significantly lower prevalence of intermittent asthma (37.5% vs. 55.6%) and higher prevalence of mild, moderate, and severe persistent asthma (28.4% vs. 23.2%, 28.7% vs. 18.8%, and 5.4% vs 2.4%, respectively). Individual/social burden due to asthma was frequent and increased with disease severity: 87.5% of severe persistent asthma patients reported at least one medical consultation in the last 12 months, 37.5% emergency department visits, 26.7% hospitalization, and 62.5% limitations in daily activities. Control and quality of life were inversely associated with disease severity and were worse in patients with R+A than in those with asthma alone. CONCLUSIONS: This study showed the negative impact of high severity levels and comorbid allergic rhinitis on quality of life of asthmatic patients and on individual/social burden due to asthma in an Italian GPs setting