Intra- and Extra-Hospitalization Monitoring of Vital Signs-Two Sides of the Same Coin: Perspectives from LIMS and Greenline-HT Study Operators.

BACKGROUND: In recent years, due to the epidemiological transition, the burden of very complex patients in hospital wards has increased. Telemedicine usage appears to be a potential high-impact factor in helping with patient management, allowing hospital personnel to assess conditions in out-of-hospital scenarios. METHODS: To investigate the management of chronic patients during both hospitalization for disease and discharge, randomized studies (LIMS and Greenline-HT) are ongoing in the Internal Medicine Unit at ASL Roma 6 Castelli Hospital. The study endpoints are clinical outcomes (from a patient's perspective). In this perspective paper, the main findings of these studies, from the operators' point of view, are reported. Operator opinions were collected from structured and unstructured surveys conducted among the staff involved, and their main themes are reported in a narrative manner. RESULTS: Telemonitoring appears to be linked to a reduction in side-events and side-effects, which represent some of most commons risk factors for re-hospitalization and for delayed discharge during hospitalization. The main perceived advantages are increased patient safety and the quick response in case of emergency. The main disadvantages are believed to be related to low patient compliance and an infrastructural lack of optimization. CONCLUSIONS: The evidence of wireless monitoring studies, combined with the analysis of activity data, suggests the need for a model of patient management that envisages an increase in the territory of structures capable of offering patients subacute care (the possibility of antibiotic treatments, blood transfusions, infusion support, and pain therapy) for the timely management of chronic patients in the terminal phase, for which treatment in acute wards must be guaranteed only for a limited time for the management of the acute phase of their diseases.

Polypharmacy Management in a Gender Perspective: At the Heart of the Problem: Analysis of Major Cardiac Diseases, SARS-CoV-2 Affection and Gender Distribution in a Cohort of Patients in Internal Medicine Ward.

BACKGROUND: COVID-19 patients with any pre-existing major cardio-vascular disease (CVD) are at the highest risk of viral infection and of developing severe disease. The pathophysiological mechanism is characterized by the viral link to angiotensin-converting enzyme 2 (ACE2) and the involvement of the endothelial system with the release of cytokines and the inflicting of direct damage to the myocardium, the induction of microthrombosis, and the initiation of alterations in oxygen diffusion. The aim of the study is to analyze the clinical course and outcomes in patients (gender-stratified) with pre-existing major CVD. METHODS: Out of the 1833 (973 M/860 F) patients admitted to the Internal Medicine COVID-19 Unit of "Castelli Hospital", Lazio, Italy, from 1 January 2021 to 31 December 2021, 600 patients (320 M/280 F) with a mean age of 77 (78.6 M/75.1 F) previously had CVD. Demographic characteristics, length of the stay (LOS) and oxygen therapy were evaluated. RESULTS: All of the CVD COVID-19 patients underwent non-invasive ventilation (NIV). CVD was linked with increased LOS (21 days F/22 M) compared to no CVD (19 days). In total, 32.7% of total patients had major CVD. CONCLUSIONS: Timely identification and evaluation of patients with pre-existing major CVD are fundamental for adequate treatment based on gender, severity, state of illness and for risk reduction.

Healthcare Workers after Two Years of COVID-19: The Consequences of the Pandemic on Psychological Health and Sleep among Nurses and Physicians.

COVID-19 has challenged the health workforce worldwide. In this cross-sectional study with a retrospective assessment, we explored the impact of the pandemic on mental health and sleep among a sample of Italian nurses and medical doctors. A total of 287 healthcare workers (212 nurses and 75 physicians) completed a web survey on socio-demographic, psychological, and sleep-related aspects referring to the period before the pandemic and to the present period of February to June 2022. Comparisons between nurses and physicians revealed that the former had greater distress in response to the pandemic. Consistently, the multivariate analysis of covariance showed that even if both groups were negatively impacted by the pandemic, nurses presented a greater worsening over time regarding several psychological and sleep symptoms. Furthermore, we observed that working on the frontline represented an additional risk factor for nurses. In line with previous evidence, we also found that personal experiences with COVID-19 are significant predictors of the current health status. Our results underscore the urgent need for preventive programs among healthcare operators to increase their coping skills and prevent the long-term consequences of chronic stress, especially for high-risk professionals. Specific attention should also be devoted to programs to improve sleep quality and reduce sleep-related traumatic symptoms.

3D CT-Inclusive Deep-Learning Model to Predict Mortality, ICU Admittance, and Intubation in COVID-19 Patients.

Chest CT is a useful initial exam in patients with coronavirus disease 2019 (COVID-19) for assessing lung damage. AI-powered predictive models could be useful to better allocate resources in the midst of the pandemic. Our aim was to build a deep-learning (DL) model for COVID-19 outcome prediction inclusive of 3D chest CT images acquired at hospital admission. This retrospective multicentric study included 1051 patients (mean age 69, SD = 15) who presented to the emergency department of three different institutions between 20th March 2020 and 20th January 2021 with COVID-19 confirmed by real-time reverse transcriptase polymerase chain reaction (RT-PCR). Chest CT at hospital admission were evaluated by a 3D residual neural network algorithm. Training, internal validation, and external validation groups included 608, 153, and 290 patients, respectively. Images, clinical, and laboratory data were fed into different customizations of a dense neural network to choose the best performing architecture for the prediction of mortality, intubation, and intensive care unit (ICU) admission. The AI model tested on CT and clinical features displayed accuracy, sensitivity, specificity, and ROC-AUC, respectively, of 91.7%, 90.5%, 92.4%, and 95% for the prediction of patient's mortality; 91.3%, 91.5%, 89.8%, and 95% for intubation; and 89.6%, 90.2%, 86.5%, and 94% for ICU admission (internal validation) in the testing cohort. The performance was lower in the validation cohort for mortality (71.7%, 55.6%, 74.8%, 72%), intubation (72.6%, 74.7%, 45.7%, 64%), and ICU admission (74.7%, 77%, 46%, 70%) prediction. The addition of the available laboratory data led to an increase in sensitivity for patient's mortality (66%) and specificity for intubation and ICU admission (50%, 52%, respectively), while the other metrics maintained similar performance results. We present a deep-learning model to predict mortality, ICU admittance, and intubation in COVID-19 patients. KEY POINTS: • 3D CT-based deep learning model predicted the internal validation set with high accuracy, sensibility and specificity (> 90%) mortality, ICU admittance, and intubation in COVID-19 patients. • The model slightly increased prediction results when laboratory data were added to the analysis, despite data imbalance. However, the model accuracy dropped when CT images were not considered in the analysis, implying an important role of CT in predicting outcomes.

Physicians' responsibility toward environmental degradation and climate change: A position paper of the European Federation of Internal Medicine.

The current data on climate change and environmental degradation are dramatic. The consequences of these changes are already having a significant impact on people's health. Physicians - as advocates of the patients, but also as citizens - have an ethical obligation to be involved in efforts to stop these changes. The European Federation of Internal Medicine (EFIM) strongly encourages the Internal Medicine societies and internists across Europe to play an active role in matters related to climate change and environmental degradation. At a national level, this includes advocating the adoption of measures that reduce greenhouse gas (GHG) emissions and environmental degradation and contributing to policy decisions related to these issues. At a hospital level and in clinical practice, supporting actions by the health sector to reduce its ecological footprint is vital. At the level of EFIM and its associated internal societies, promoting educational activities and developing a toolkit to prepare internists to better care for citizens who suffer from the consequences of climate change. In addition to advocating and implementing effective actions to reduce the ecological footprint of the health industry, recommending the introduction of these themes in scientific programs of Internal Medicine meetings and congresses and the pre- and postgraduate medical training. At a personal level, internists must be active agents in advocating sustainable practices for the environment, increasing the awareness of the community about the health risks of climate change and environmental degradation, and being role models in the adoption of environmentally friendly behaviour.

Deep learning and machine learning-based voice analysis for the detection of COVID-19: A proposal and comparison of architectures.

Alongside the currently used nasal swab testing, the COVID-19 pandemic situation would gain noticeable advantages from low-cost tests that are available at any-time, anywhere, at a large-scale, and with real time answers. A novel approach for COVID-19 assessment is adopted here, discriminating negative subjects versus positive or recovered subjects. The scope is to identify potential discriminating features, highlight mid and short-term effects of COVID on the voice and compare two custom algorithms. A pool of 310 subjects took part in the study; recordings were collected in a low-noise, controlled setting employing three different vocal tasks. Binary classifications followed, using two different custom algorithms. The first was based on the coupling of boosting and bagging, with an AdaBoost classifier using Random Forest learners. A feature selection process was employed for the training, identifying a subset of features acting as clinically relevant biomarkers. The other approach was centered on two custom CNN architectures applied to mel-Spectrograms, with a custom knowledge-based data augmentation. Performances, evaluated on an independent test set, were comparable: Adaboost and CNN differentiated COVID-19 positive from negative with accuracies of 100% and 95% respectively, and recovered from negative individuals with accuracies of 86.1% and 75% respectively. This study highlights the possibility to identify COVID-19 positive subjects, foreseeing a tool for on-site screening, while also considering recovered subjects and the effects of COVID-19 on the voice. The two proposed novel architectures allow for the identification of biomarkers and demonstrate the ongoing relevance of traditional ML versus deep learning in speech analysis.

Beyond Coronavirus: the metamorphosis as the essence of the phenomenon.

This paper is an insight on a front-line doctor's experience of Coronavirus in Italy, in an Internal Medicine ward transformed to a COVID-19 ward. Using content analysis were analyzed 52 destructurated interviews to "Covid clinicians" in the "Ospedale dei Castelli" hospital structure in Rome, Italy. Thematic analysis was performed to recognize common topics in the interviews. Finally, a correlation between the 5 Ovid's forces (love and thirst for knowledge-positive ones-anger, envy and fear-negative ones) and Narrative Medicine scenarios (Physician and Patients, Physician and Society, Physician and Self, Physician and Colleagues) is described. Coronavirus is a "tsunami" by confrontation with the poet Ovid's five driving forces. Covid-19 never gave health-workers a chance to draw breath for a moment themselves, as presentation and treatment hypotheses changed at dizzying speed, constantly forcing them to modify and adapt established procedures and behavior as the pandemic evolved. Every scenarios present a correlation with at least one positive and one negative force (Physician and Patients: love and anger, Physician and Self: Fear and Thirst for Knowledge, Physician and Colleagues: Thirst for Knowledge and Envy, Physician and Society: Love, Fear and Anger). Many healthcare workers who came face-to-face with the magnitude of this emergency are able in some way to contextualize the social implications of this experience, which paradoxically has some positive aspects, having let them discover newfound courage, resourcefulness, and hope. Negative forces result from too strong positive emotions and they are a signal of deteriorated relationships and an alarm bell of clinician's burn-out. Covid era has been defined by the lack of emergency preparedness, together with lack of international coordination and media reports generating terror. People can defeat Covid by combatting against terror of the heart, by finding passion and courage and by dealing honestly with the fear of disease and death.

Green Line Hospital-Territory Study: A Single-Blind Randomized Clinical Trial for Evaluation of Technological Challenges of Continuous Wireless Monitoring in Internal Medicine, Preliminary Results.

BACKGROUND: Wireless vital parameter continuous monitoring (WVPCM) after discharge is compared to regular monitoring to provide data on the clinical-economic impact of complex patients (CPs) discharged from Internal Medicine Units of Ospedale dei Castelli, Lazio. PRIMARY OUTCOME: Major complications (MC) reduction. SECONDARY OUTCOMES: Patients who reached discharge criteria within the 7th day from admission; difference in MC incidence at the conclusion of the standard telemonitoring/clinical monitoring phase, 5 and 30 days after discharge; and conditions predisposing to MC occurrence. METHODS: Open label randomized controlled trial with wearable wireless system that creates alerts on portable devices. Continuous glycemic monitoring is performed for patients with diabetes mellitus. RESULTS: There were 110 patients enrolled (mean age: 76.2 years). Comorbidity: Cumulative Illness Rating Scale CIRS-CI (comorbidities index): 3.93, CIRS SI (severity index): 1.93. About 19% scored a BRASS (Blaylock Risk Assessment Screening Score) ≥20 indicating need for discharge planning requiring step-down care. Globally, 48% of patients in the control group had major complications (27 out of 56 patients), in contrast to 22% in the intervention group (12 out of 54 patients). CONCLUSIONS: Since WVPCM detects early complications during the post-discharge CPs monitoring, it increases safety and reduces inappropriate access to the Emergency Room, preventing avoidable re-hospitalizations.

Burden of COVID-19 on Italian Internal Medicine Wards: Delphi, SWOT, and Performance Analysis after Two Pandemic Waves in the Local Health Authority "Roma 6" Hospital Structures.

Background: COVID-19 causes major changes in day-to-day hospital activity due to its epidemiological characteristics and the clinical challenges it poses, especially in internal medicine wards. Therefore, it is necessary to understand and manage all of the implicated factors in order to maintain a high standard of care, even in sub-par circumstances. Methods: This was a three-phase, mixed-design study. Initially, the Delphi method allowed us to analyze the causes of poor outcomes in a cohort of an aggregate of Italian COVID-19 wards via an Ishikawa diagram. Then, for each retrieved item, a score was assigned according to a pros/cons, opportunities/threats system. Scores were also assigned according to potential value/perceived risk. Finally, the performances of MCs (Medicine-COVID-19 wards) and MCFs (Medicine-COVID-19-free: Internal Medicine wards) units were represented via a Barber's nomogram. Results: MCFs hospitalized 790 patients (-23.90% compared to 2019 Internal Medicine admissions). The main risk factors for mortality were patients admitted from local facilities (+7%) and the presence of comorbidities (>3: 100%, ≥5: 24.7%). A total of 197 (25%) patients were treated with non-invasive ventilation (NIV). The most deaths (57.14%) occurred in patients admitted from local facilities. Conclusions: Medicine-COVID-19 wards show higher complexity and demand compared to non-COVID-19 ones and they are comparable to sub-intensive therapy wards. It is necessary to promote the use of NIV in such settings.

Cow's Milk Consumption and Health: A Health Professional's Guide.

The most recent scientific evidence supports the consumption of cow's milk and dairy products as part of a balanced diet. However, these days, the public and practicing physicans are exposed to a stream of inconsistent (and often misleading) information regarding the relationship between cow's milk intake and health in the lay press and in the media. The purpose of this article, in this context, is to facilitate doctor-patient communication on this topic, providing physicians with a series of structured answers to frequently asked patient questions. The answers range from milk and milk-derived products' nutritional function across the life span, to their relationship with diseases such as osteoporosis and cancer, to lactose intolerance and milk allergy, and have been prepared by a panel of experts from the Italian medical and nutritional scientific community. When consumed according to appropriate national guidelines, milk and its derivatives contribute essential micro- and macronutrients to the diet, especially in infancy and childhood where bone mass growth is in a critical phase. Furthermore, preliminary evidence suggests potentially protective effects of milk against overweight, obesity, diabetes, and cardiovascular disease, while no clear data suggest a significant association between milk intake and cancer. Overall, current scientific literature suggests that an appropriate consumption of milk and its derivatives, according to available nutritional guidelines, may be beneficial across all age groups, with the exception of specific medical conditions such as lactose intolerance or milk protein allergy. Key teaching points: Milk and its derivatives contribute essential micro and macronutrients to the diet, when consumed according to appropriate national guidelines, especially in infancy and childhood where bone mass growth is in a critical phase. Preliminary evidence suggests potentially protective effects of milk against overweight, obesity, diabetes and cardiovascular disease No clear data are available about the association between milk intake and cancer. Current scientific literature suggests that an appropriate consumption of milk and its derivatives may be beneficial at all ages, with the exception of specific medical conditions such as lactose intolerance or milk protein allergy.

[Contact lens-related Fusarium keratitis: a case report].

We aim to highlight the key factors for a good outcome of fungal keratitis. We describe a case of contact lens-related Fusarium keratitis in a young girl. After identification of Fusarium spp under direct microscopic examination and in culture, a prolonged treatment with topic natamycin 5% was started and administered for five months with restitutio ad integrum of the eye. Prompt microbiological diagnosis and a specific and prolonged treatment are essential for correct management of Fusarium keratitis.

Acute Complex Care Model: An organizational approach for the medical care of hospitalized acute complex patients.

BACKGROUND: Chronic diseases are the major cause of death (59%) and disability worldwide, representing 46% of global disease burden. According to the Future Hospital Commission of the Royal College of Physicians, Medical Division (MD) will be responsible for all hospital medical services, from emergency to specialist wards. The Hospital Acute Care Hub will bring together the clinical areas of the MD that focus on the management of acute medical patients. The Chronic Care Model (CCM) places the patient at the center of the care system enhancing the community's social and health support, pathways and structures to keep chronic, frail, poly-pathological people at home or out of the hospital. The management of such patients in the hospital still needs to be solved. Hereby, we propose an innovative model for the management of the hospital's acute complex patients, which is the hospital counterpart of the CCM. ACUTE COMPLEX CARE MODEL (ACCM): The target population are acutely ill complex and poly-pathological patients (AICPPs), admitted to hospital and requiring high technology resources. The mission is to improve the management of medical admissions through pre-defined intra-hospital tracks and a global, multidisciplinary, patient-centered approach. The ACCM leader is an internal medicine specialist (IMS) who summarizes health problems, establishes priorities, and restores health balance in AICPPs. CONCLUSIONS: The epidemiological transition leading to a progressive increase in "chronically unstable" and complex patients needing frequent hospital treatment, inevitably enhances the role of hospital IMS in the coordination and delivery of care. ACCM represents a practical response to this epochal change of roles.

The Impact of Event Scale: validation of an Italian version.

OBJECTIVE: To validate an Italian version of the Impact of Event Scale (IES) in patients addressing the emotional impact of a recent road accident. METHODS: Seventy-nine subjects were examined within 1-34 weeks after an accident by means of (1). an Italian version of the IES, (2). a free description of the accident, and (3). a questionnaire assessing subjects' behaviour and feelings. RESULTS: IES data were analysed by means of the principal component analysis (PCA) method, followed by a quartimax rotation, obtaining a two-factor solution interpreted as intrusion (Factor 1) and avoidance (Factor 2). Furthermore, the scores to the two subscales were considered in order to assess their predictive value on some variables linked to the traumatic event. Intrusion significantly discriminated the emotional intensity and fear level of subjects as a consequence of the accident. CONCLUSIONS: The IES is a two-dimensional test capable of evaluating posttraumatic stress. The intrusion and avoidance factors explained 40% of the total variance. The two-factor solution has a psychological counterpart and is similar to the findings of earlier studies conducted on a larger number of subjects in other countries.