Italy’s latest legislation on accounting fraud highlights the country’s difficulty in pursuing real economic and political reform

Italy has a longstanding corruption problem which the Italian Prime Minister, Matteo Renzi, has pledged to address. Andrea Lorenzo Capussela and Vito Intini write on a recent piece of legislation introduced in June which alters the rules on accounting fraud. They argue that the legislation has opened up a significant loophole and is indicative of the Italian political system’s inability to produce meaningful political and economic reforms

There is little evidence that the proposed reform of Italy’s labour market will actually generate growth or employment

The Italian government has outlined a number of policies aimed at reforming Italy’s labour market, with the proposals receiving final approval in the Italian Senate on 3 December. Andrea Lorenzo Capussela and Vito Intini assess whether the reforms, which have proved controversial, will actually have the desired effect in generating economic growth and employment. They write that while increasing the flexibility of the Italian labour market may be desirable, the rigidity of the labour market is not the biggest obstacle to growth in the country. They argue instead that the quality of Italy’s political institutions and governance standards should be the key focus of reform efforts

External pressure is needed to help Italy tackle its persistent corruption problem

Corruption has been a persistent problem in Italy, with the country receiving one of the lowest scores of EU member states in Transparency International’s latest ‘Corruption Perceptions Index’. Andrea Lorenzo Capussela and Vito Intini provide a comprehensive look at the problem, noting that on several measures corruption has increased since the late 1990s. They argue that corruption in Italy represents a ‘resilient equilibrium’, whereby the political system provides little incentive for parties to tackle the problem. They suggest that external pressure from other countries in the EU may offer one route to breaking this cycle

Performance Assessment in Fingerprinting and Multi Component Quantitative NMR Analyses

An interlaboratory comparison (ILC) was organized with the aim to set up quality control indicators suitable for multicomponent quantitative analysis by nuclear magnetic resonance (NMR) spectroscopy. A total of 36 NMR data sets (corresponding to 1260 NMR spectra) were produced by 30 participants using 34 NMR spectrometers. The calibration line method was chosen for the quantification of a five-component model mixture. Results show that quantitative NMR is a robust quantification tool and that 26 out of 36 data sets resulted in statistically equivalent calibration lines for all considered NMR signals. The performance of each laboratory was assessed by means of a new performance index (named Qp-score) which is related to the difference between the experimental and the consensus values of the slope of the calibration lines. Laboratories endowed with a Qp-score falling within the suitable acceptability range are qualified to produce NMR spectra that can be considered statistically equivalent in terms of relative intensities of the signals. In addition, the specific response of nuclei to the experimental excitation/relaxation conditions was addressed by means of the parameter named NR. NR is related to the difference between the theoretical and the consensus slopes of the calibration lines and is specific for each signal produced by a well-defined set of acquisition parameters

Sutureless repair for open treatment of inguinal hernia. Three techniques in comparison

: Currently, groin hernia repair is mostly performed with application of mesh prostheses fixed with or without suture. However, views on safety and efficacy of different surgical approaches are still partly discordant. In this multicentre retrospective study, three sutureless procedures, i.e., mesh fixation with glue, application of self-gripping mesh, and Trabucco's technique, were compared in 1034 patients with primary unilateral non-complicated inguinal hernia subjected to open anterior surgery. Patient-related features, comorbidities, and drugs potentially affecting the intervention outcomes were also examined. The incidence of postoperative complications, acute and chronic pain, and time until discharge were assessed. A multivariate logistic regression was used to compare the odds ratio of the surgical techniques adjusting for other risk factors. The application of standard/heavy mesh, performed in the Trabucco's technique, was found to significantly increase the odds ratio of hematomas (p = 0.014) and, most notably, of acute postoperative pain (p < 0.001). Among the clinical parameters, antithrombotic therapy and large hernia size were independent risk factors for hematomas and longer hospital stay, whilst small hernias were an independent predictor of pain. Overall, our findings suggest that the Trabucco's technique should not be preferred in patients with a large hernia and on antithrombotic therapy

Gemelli decision tree Algorithm to Predict the need for home monitoring or hospitalization of confirmed and unconfirmed COVID-19 patients (GAP-Covid19): Preliminary results from a retrospective cohort study

OBJECTIVE: To develop a deep learning-based decision tree for the primary care setting, to stratify adult patients with confirmed and unconfirmed coronavirus disease 2019 (COVID-19), and to predict the need for hospitalization or home monitoring. PATIENTS AND METHODS: We performed a retrospective cohort study on data from patients admitted to a COVID hospital in Rome, Italy, between 5 March 2020 and 5 June 2020. A confirmed case was defined as a patient with a positive nasopharyngeal RT-PCR test result, while an unconfirmed case had negative results on repeated swabs. Patients’ medical history and clinical, laboratory and radiological findings were collected, and the dataset was used to train a predictive model for COVID-19 severity. RESULTS: Data of 198 patients were included in the study. Twenty-eight (14.14%) had mild disease, 62 (31.31%) had moderate disease, 64 (32.32%) had severe disease, and 44 (22.22%) had critical disease. The G2 value assessed the contribution of each collected value to decision tree building. On this basis, SpO2 (%) with a cut point at 92 was chosen for the optimal first split. Therefore, the decision tree was built using values maximizing G2 and LogWorth. After the tree was built, the correspondence between inputs and outcomes was validated. CONCLUSIONS: We developed a machine learning-based tool that is easy to understand and apply. It provides good discrimination in stratifying confirmed and unconfirmed COVID-19 patients with different prognoses in every context. Our tool might allow general practitioners visiting patients at home to decide whether the patient needs to be hospitalized