Revisione critica dei risultati e nuovi algoritmi decisionali sulla chirurgia dell'OSAS

Obstructive sleep apnoea/hypopnoea syndrome (OSAHS) is the periodic reduction or cessation of airflow during sleep. The syndrome is associated whit loud snoring, disrupted sleep and observed apnoeas. Surgery aims to alleviate symptoms of daytime sleepiness, improve quality of life and reduce the signs of sleep apnoea recordered by polysomnography. Surgical intervention for snoring and OSAHS includes several procedures, each designed to increase the patency of the upper airway. Procedures addressing nasal obstruction include septoplasty, turbinectomy, and radiofrequency ablation (RF) of the turbinates. Surgical procedures to reduce soft palate redundancy include uvulopalatopharyngoplasty with or without tonsillectomy, uvulopalatal flap, laser-assisted uvulopalatoplasty, and RF of the soft palate. More significant, however, particularly in cases of severe OSA, is hypopharyngeal or retrolingual obstruction related to an enlarged tongue, or more commonly due to maxillomandibular deficiency. Surgeries in these cases are aimed at reducing the bulk of the tongue base or providing more space for the tongue in the oropharynx so as to limit posterior collapse during sleep. These procedures include tongue-base suspension, genioglossal advancement, hyoid suspension, lingualplasty, and maxillomandibular advancement. We reviewed 269 patients undergoing to osas surgery at the ENT Department of Forlì Hospital in the last decade. Surgery was considered a success if the postoperative apnea/hypopnea index (AHI) was less than 20/h. According to the results, we have developed surgical decisional algorithms with the aims to optimize the success of these procedures by identifying proper candidates for surgery and the most appropriate surgical techniques. Although not without risks and not as predictable as positive airway pressure therapy, surgery remains an important treatment option for patients with obstructive sleep apnea (OSA), particularly for those who have failed or cannot tolerate positive airway pressure therapy. Successful surgery depends on proper patient selection, proper procedure selection, and experience of the surgeon. The intended purpose of medical algorithms is to improve and standardize decisions made in the delivery of medical care, assist in standardizing selection and application of treatment regimens, to reduce potential introduction of errors. Nasal Continuous Positive Airway Pressure (nCPAP) is the recommended therapy for patients with moderate to severe OSAS. Unfortunately this treatment is not accepted by some patient, appears to be poorly tolerated in a not neglible number of subjects, and the compliance may be critical, especially in the long term if correctly evaluated with interview as well with CPAP smart cards analysis. Among the alternative options in Literature, surgery is a long time honoured solution. However until now no clear scientific evidence exists that surgery can be considered a really effective option in OSAHS management. We have design a randomized prospective study comparing MMA and a ventilatory device (Autotitrating Positive Airways Pressure – APAP) in order to understand the real effectiveness of surgery in the management of moderate to severe OSAS. Fifty consecutive previously full informed patients suffering from severe OSAHS were enrolled and randomised into a conservative (APAP) or surgical (MMA) arm. Demographic, biometric, PSG and ESS profiles of the two group were statistically not significantly different. One year after surgery or continuous APAP treatment both groups showed a remarkable improvement of mean AHI and ESS; the degree of improvement was not statistically different. Provided the relatively small sample of studied subjects and the relatively short time of follow up, MMA proved to be in our adult and severe OSAHS patients group a valuable alternative therapeutical tool with a success rate not inferior to APAP.

Development of Clinical Decision Support Systems based on Mathematical Models of Physiological Systems

In the last years of research, I focused my studies on different physiological problems. Together with my supervisors, I developed/improved different mathematical models in order to create valid tools useful for a better understanding of important clinical issues. The aim of all this work is to develop tools for learning and understanding cardiac and cerebrovascular physiology as well as pathology, generating research questions and developing clinical decision support systems useful for intensive care unit patients. I. ICP-model Designed for Medical Education We developed a comprehensive cerebral blood flow and intracranial pressure model to simulate and study the complex interactions in cerebrovascular dynamics caused by multiple simultaneous alterations, including normal and abnormal functional states of auto-regulation of the brain. Individual published equations (derived from prior animal and human studies) were implemented into a comprehensive simulation program. Included in the normal physiological modelling was: intracranial pressure, cerebral blood flow, blood pressure, and carbon dioxide (CO2) partial pressure. We also added external and pathological perturbations, such as head up position and intracranial haemorrhage. The model performed clinically realistically given inputs of published traumatized patients, and cases encountered by clinicians. The pulsatile nature of the output graphics was easy for clinicians to interpret. The manoeuvres simulated include changes of basic physiological inputs (e.g. blood pressure, central venous pressure, CO2 tension, head up position, and respiratory effects on vascular pressures) as well as pathological inputs (e.g. acute intracranial bleeding, and obstruction of cerebrospinal outflow). Based on the results, we believe the model would be useful to teach complex relationships of brain haemodynamics and study clinical research questions such as the optimal head-up position, the effects of intracranial haemorrhage on cerebral haemodynamics, as well as the best CO2 concentration to reach the optimal compromise between intracranial pressure and perfusion. We believe this model would be useful for both beginners and advanced learners. It could be used by practicing clinicians to model individual patients (entering the effects of needed clinical manipulations, and then running the model to test for optimal combinations of therapeutic manoeuvres). II. A Heterogeneous Cerebrovascular Mathematical Model Cerebrovascular pathologies are extremely complex, due to the multitude of factors acting simultaneously on cerebral haemodynamics. In this work, the mathematical model of cerebral haemodynamics and intracranial pressure dynamics, described in the point I, is extended to account for heterogeneity in cerebral blood flow. The model includes the Circle of Willis, six regional districts independently regulated by autoregulation and CO2 reactivity, distal cortical anastomoses, venous circulation, the cerebrospinal fluid circulation, and the intracranial pressure-volume relationship. Results agree with data in the literature and highlight the existence of a monotonic relationship between transient hyperemic response and the autoregulation gain. During unilateral internal carotid artery stenosis, local blood flow regulation is progressively lost in the ipsilateral territory with the presence of a steal phenomenon, while the anterior communicating artery plays the major role to redistribute the available blood flow. Conversely, distal collateral circulation plays a major role during unilateral occlusion of the middle cerebral artery. In conclusion, the model is able to reproduce several different pathological conditions characterized by heterogeneity in cerebrovascular haemodynamics and can not only explain generalized results in terms of physiological mechanisms involved, but also, by individualizing parameters, may represent a valuable tool to help with difficult clinical decisions. III. Effect of Cushing Response on Systemic Arterial Pressure. During cerebral hypoxic conditions, the sympathetic system causes an increase in arterial pressure (Cushing response), creating a link between the cerebral and the systemic circulation. This work investigates the complex relationships among cerebrovascular dynamics, intracranial pressure, Cushing response, and short-term systemic regulation, during plateau waves, by means of an original mathematical model. The model incorporates the pulsating heart, the pulmonary circulation and the systemic circulation, with an accurate description of the cerebral circulation and the intracranial pressure dynamics (same model as in the first paragraph). Various regulatory mechanisms are included: cerebral autoregulation, local blood flow control by oxygen (O2) and/or CO2 changes, sympathetic and vagal regulation of cardiovascular parameters by several reflex mechanisms (chemoreceptors, lung-stretch receptors, baroreceptors). The Cushing response has been described assuming a dramatic increase in sympathetic activity to vessels during a fall in brain O2 delivery. With this assumption, the model is able to simulate the cardiovascular effects experimentally observed when intracranial pressure is artificially elevated and maintained at constant level (arterial pressure increase and bradicardia). According to the model, these effects arise from the interaction between the Cushing response and the baroreflex response (secondary to arterial pressure increase). Then, patients with severe head injury have been simulated by reducing intracranial compliance and cerebrospinal fluid reabsorption. With these changes, oscillations with plateau waves developed. In these conditions, model results indicate that the Cushing response may have both positive effects, reducing the duration of the plateau phase via an increase in cerebral perfusion pressure, and negative effects, increasing the intracranial pressure plateau level, with a risk of greater compression of the cerebral vessels. This model may be of value to assist clinicians in finding the balance between clinical benefits of the Cushing response and its shortcomings. IV. Comprehensive Cardiopulmonary Simulation Model for the Analysis of Hypercapnic Respiratory Failure We developed a new comprehensive cardiopulmonary model that takes into account the mutual interactions between the cardiovascular and the respiratory systems along with their short-term regulatory mechanisms. The model includes the heart, systemic and pulmonary circulations, lung mechanics, gas exchange and transport equations, and cardio-ventilatory control. Results show good agreement with published patient data in case of normoxic and hyperoxic hypercapnia simulations. In particular, simulations predict a moderate increase in mean systemic arterial pressure and heart rate, with almost no change in cardiac output, paralleled by a relevant increase in minute ventilation, tidal volume and respiratory rate. The model can represent a valid tool for clinical practice and medical research, providing an alternative way to experience-based clinical decisions. In conclusion, models are not only capable of summarizing current knowledge, but also identifying missing knowledge. In the former case they can serve as training aids for teaching the operation of complex systems, especially if the model can be used to demonstrate the outcome of experiments. In the latter case they generate experiments to be performed to gather the missing data.

La performance rituale delle Nava Durgā: musica e danza tra i Banmālā di Bhaktapur, Nepal

Il presente lavoro è il risultato di cinque anni di ricerca sulla performance rituale delle Nava Durgā del popolo newar a Bhaktapur (Nepal). Dal 1512, per circa nove mesi all'anno, gli uomini della casta inferiore Banmālā reincarnano le nove manifestazioni femminili della dea Durgā ed eseguono le danze in maschera. La performance della Nava Durgā è una pratica culturale molto complessa, composta da suoni, danze, processioni, momenti di venerazione (pūjā), rituali tantrici e momenti sacrificali. Gli aspetti musicali e teatrali della performance costituiscono il focus dell’indagine di questo studio. Dopo una descrizione analitica degli strumenti musicali utilizzati nella performance, alcuni elementi sonori vengono trascritti e analizzati mettendo in luce le caratteristiche tipiche della musica newar. I contenuti narrativi delle danze e il ciclo vitale delle Nava Durgā rispecchiano la vita hindu. La loro interpretazione viene realizzata in base alle osservazioni etnografiche; alcuni temi che costituiscono gli obiettivi dei devoti hindu (puruṣārtha) vengono esaminati attraverso l’approccio storico e quello etnografico, anche al fine di sottolineare il ruolo didascalico e formativo della performance. Un altro argomento discusso in questo lavoro consiste nell'identità dei danzatori Banmālā e quella del popolo newar in generale; questo aspetto è emerso in modo rilevante anche durante le fasi di mediatizzazione della performance delle Nava Durgā avvenute nel periodo del COVID-19. Da questo punto di vista, il presente lavoro costituisce un contributo alla diffusione della conoscenza della tradizione delle Nava Durgā; questo converge con l'obiettivo dei Banmālā di aumentare la visibilità della performance al fine di affermare la propria identità sia nel contesto nazionale che in quello internazionale.

Network analysis and machine learning assist drug repurposing and safety assessment in neurological diseases

In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.