Massimiliano Panella

Background: Gut microbiota plays a key role in the aging process, with age-related microbial shifts contributing to chronic inflammation, metabolic dysfunction, frailty, and cognitive decline. Despite growing interest, an integrated synthesis of how diet and lifestyle modifications influence gut microbiota remains limited. This overview of reviews summarizes the current evidence on how dietary and lifestyle interventions shape microbial composition and affect aging outcomes. Methods: Following the PRISMA guidelines, we searched PubMed and Scopus for English-language reviews (January 2023–October 2025) including human adults aged ≥ 18 years, evaluating dietary or lifestyle interventions, and reporting gut microbiota with healthy-aging outcomes. Quality of the reviews was appraised using the SANRA tool. Results: Mediterranean and plant-based diets, calorie restriction, and microbiota-targeted approaches such as probiotics, prebiotics, symbiotics, and fecal microbiota transplantation were associated with increases in short-chain fatty acid-producing bacteria, including Faecalibacterium, Bifidobacterium, Lactobacillus, and Akkermansia muciniphila, while reducing pro-inflammatory taxa. These changes were linked to improved metabolic and immune function, reduced inflammaging, lower frailty, and greater physical resilience. Cognitive benefits included decreased neuroinflammation and a lower risk of Alzheimer’s and Parkinson’s diseases. Conclusions: Maintaining microbial balance through targeted dietary strategies may support healthier, more resilient aging, offering practical insights for public health and clinical nutrition planning.

Despite warnings and strict guidelines, the use of antipsychotics in long-term care facilities (LTCFs) remains problematic worldwide. Several factors, incl

Background/Objectives: Chronic pain conditions are common among older residents in long-term care facilities (LTCFs), often leading to increased demand for analgesic drugs. Despite this, pain is frequently underdiagnosed and undertreated, especially in individuals with cognitive impairments such as dementia. Both underuse and overuse of analgesics remain a challenge in LTCFs, affecting patient outcomes and quality of life. This systematic review aimed to identify patient- and facility-level factors associated with variation in analgesic use in LTCFs. Methods: This review followed PRISMA guidelines. A comprehensive literature search was conducted in PubMed, CINAHL, Cochrane Library, and Scopus for studies published between 2013 and 2024. Eligible studies were focused on adults aged ≥ 60 years in LTCFs and examined patient and facility factors related to analgesic prescription. Risk of bias was assessed independently by two reviewers using STROBE, JBI, and MMAT tools. Disagreements were resolved by a third reviewer. Results: A total of 6266 studies were retrieved; 13 papers met the eligibility criteria after screening. Dementia was the most frequently reported factor associated with lower analgesic prescribing, largely due to difficulties in assessing pain and communication barriers. Other patient-related factors included pain severity and comorbidities. Facility-level factors such as staffing levels, staff qualifications, and facility size were also associated with variation in prescribing practices. Conclusions: Dementia highly impacts pain management due to assessment and communication challenges. Improved pain assessment tools and staff training are needed to recognize pain in cognitively impaired residents and ensure appropriate analgesic use in LTCFs.

Background and Objectives: Diabetes is a global public health challenge, with increasing prevalence worldwide. The implementation of artificial intelligence (AI) in the management of this condition offers potential benefits in improving healthcare outcomes. This study primarily investigates the barriers and facilitators perceived by healthcare professionals in the adoption of AI. Secondarily, by analyzing both quantitative and qualitative data collected, it aims to support the potential development of AI-based programs for diabetes management, with particular focus on a possible bottom-up approach. Materials and Methods: A scoping review was conducted following PRISMA-ScR guidelines for reporting and registered in the Open Science Framework (OSF) database. The study selection process was conducted in two phases—title/abstract screening and full-text review—independently by three researchers, with a fourth resolving conflicts. Data were extracted and assessed using Joanna Briggs Institute (JBI) tools. The included studies were synthesized narratively, combining both quantitative and qualitative analyses to ensure methodological rigor and contextual depth. Results: The adoption of AI tools in diabetes management is influenced by several barriers, including perceived unsatisfactory clinical performance, high costs, issues related to data security and decision-making transparency, as well as limited training among healthcare workers. Key facilitators include improved clinical efficiency, ease of use, time-saving, and organizational support, which contribute to broader acceptance of the technology. Conclusions: The active and continuous involvement of healthcare workers represents a valuable opportunity to develop more effective, reliable, and well-integrated AI solutions in clinical practice. Our findings emphasize the importance of a bottom-up approach and highlight how adequate training and organizational support can help overcome existing barriers, promoting sustainable and equitable innovation aligned with public health priorities.

Introduction/Aim: Type 1 diabetes (T1D) challenges glycemic control, with sleep disturbances affecting insulin sensitivity and glucose variability. This study aimed to observe sleep quality in T1D patients and glycemic outcomes, particularly at bedtime hours. Methods: This retrospective observational study, conducted at an Italian clinical center, included T1D patients using Medtronic devices. Sleep quality was assessed using the Italian version of the Pittsburgh Sleep Quality Index (PSQI), and glycemic outcomes were analyzed with CGM data. Descriptive statistics and non-parametric tests were applied for statistical comparisons. Results: Of 45 patients, four were excluded, leaving 41 for analysis. The mean PSQI score was 6.0 ± 4.1, with 36.6% showing poor sleep quality. No significant differences in age, sex, BMI, or diabetes duration were found. Poor sleepers had a higher time above range level 2 (TAR2) (6.3 ± 6.2%) compared to good sleepers (4.1 ± 5.0%). During bedtime hours, poor sleepers showed a significantly higher TAR2 (6.7 ± 7.2% vs. 3.3 ± 6.2%, p = 0.013). Conclusions: Poor sleep quality is associated with increased nocturnal hyperglycemia in T1D patients. Enhancing sleep quality may contribute to improved glycemic control, particularly during nighttime. Future research should explore targeted sleep interventions in diabetes care, and specific lifestyle-based healthcare programs are recommended to optimize glycemic outcomes.

Background: Seasonal influenza currently remains a major public health concern for the community and, in particular, the health care worker (HCW). According to the World Health Organization, HCWs are among the high-risk categories for which vaccination is recommended, due to the derived absenteeism, productivity loss, and high probability of transmitting the disease to vulnerable individuals or patients. Therefore, an HCW vaccination policy should be adopted by every health care provider. There is growing evidence that a time effect of the vaccination event is probable, which may influence vaccine effectiveness. We designed and conducted an observational study to investigate the time to anti-influenza vaccination event of different categories of HCWs belonging to different occupational settings in a tertiary hospital during three seasons in order to retrieve some insight about HCW prioritization when designing vaccination campaigns. Materials and Methods: We retrospectively analyzed the results of two HCW anti-influenza vaccination campaigns (2022 and 2023) to assess any difference regarding job typology and unit typology (critical care, surgical, medical, service). We first fitted a classic Cox proportional hazard model and then an AI random forest model to assess variable importance. We used R, RStudio, and the survex package. Results: Overall, other HCWs reported a lower vaccination rate compared to nurses (HR 0.77; 95%CI 0.62–0.97), and service unit personnel appeared to more likely be vaccinated (HR 1.42; 95%CI 1.01–1.99) compared to those belonging to the critical care units. As expected, older workers tended to be vaccinated more frequently (HR 1.70 for the (46, 65] category compared to the younger one; 95%CI 1.39–2.09). The variable importance analysis showed consistent superiority of the ward typology and age category variables with respect to time. During the entire timeline, the ward typology appeared to be more important than the HCW typology. Conclusions: Our results suggest a prioritization policy based firstly on the unit typology followed by the job typology for HCW anti-influenza campaigns.

Background: The world’s population is not only growing but also ageing, and healthcare systems should adapt to the needs of an ageing population. Until now, there has been no clear definition of a preventive pathway with the aim of improving lifestyles and promoting healthy and active ageing. The present systematic review aims to provide evidence to support the development of effective ways of delivering preventive pathways for healthy ageing. Methods: Several databases were searched, i.e., MEDLINE, COCHRANE, CINAHL, and PsycINFO, by using specific inclusion criteria, such as elderly population (i.e., subjects aged 65 years and older), preventive interventions for healthy ageing, studies with or without control groups, and effectiveness and methodological structure of the prevention pathway. The risk of bias was assessed by using the Joanna Briggs Institute and mixed methods appraisal tools. Results: A total of 9998 studies were identified after the removal of duplicates, and after screening title, abstracts, and full text, 14 studies were finally included. All the prevention pathways described are based on physical activity (PA) programmes, dietary interventions, and cognitive and mental health. The professional figures involved in the pathways were experts in prevention and health promotion, like family and community nurses, kinesiologists, and experts in stress management. The majority of the preventive pathways were implemented in primary care and community settings. Conclusions: Our systematic review provides evidence for developing an effective preventive healthy ageing pathway through tailored PA, diet, and cognitive health interventions. This co-designed approach should involve a multidisciplinary expert team and be implemented in primary care and community settings to improve psycho-physical health and longevity.

Introduction/Aim: Type 1 Diabetes (T1D) challenges glycemic control, with sleep dis-turbances affecting insulin sensitivity and glucose variability. This study aims to assess sleep quality in T1D patients and its impact on glycemic outcomes, particularly at bed-time. Methods: This retrospective observational study, conducted at an Italian clinical center, included T1D patients using Medtronic devices. Sleep quality was assessed us-ing the Italian version of the Pittsburgh Sleep Quality Index (PSQI), and glycemic out-comes were analyzed with CGM data. Statistical comparisons were made using de-scriptive statistics and non-parametric tests. Results: Of 45 patients, 4 were excluded, leaving 41 for analysis. The mean PSQI score was 6.0 ± 4.1, with 36.6% showing poor sleep quality. No significant differences in age, sex, BMI, or diabetes duration were found. Poor sleepers had higher Time in Elevated Glycemic Range 2 (TAR2) (6.3 ± 6.2%) compared to good sleepers (4.1 ± 5.0%). During bedtime hours, poor sleepers showed significantly higher TAR2 (6.7 ± 7.2% vs. 3.3 ± 6.2%, p = 0.013). Conclusions: Improving sleep quality may boost glycemic control and prevent nocturnal hyperglycemia. Future research should focus on sleep interventions in diabetes care.

Background: The impact of a patient safety incident (PSI) on nurses and doctors in hospital settings has been studied in depth. However, the impact of a PSI on general practitioners and how those health care professionals can be supported are less clear. Objectives: The objective of this study is to investigate the prevalence of GPs (in training) being personally involved in a PSI, as well as the impact, the support needed, and open disclosure in the aftermath of these PSIs. Methods: A cross-sectional study, conducted between January 3, 2022, and March 5, 2022, led to a sample of 78 GPs or GPs in training in Flanders (Belgium). Participants filled in more than 80% of a questionnaire that measured the involvement in a PSI during the prior year and their entire career, and the impact in terms of emotional symptoms, attitudes, the support needed, and open disclosure were included. Results: In total, 78 responses of GPs (in training) filled in the questionnaire, of which 87.2% were involved in a PSI over the course of their entire career and 55.1% during the prior year. Often, such a PSI resulted in permanent patient harm or patient death. The PSI that stuck with the GPs the most had many negative consequences for the GP in question, such as hypervigilance (88.2%) and feelings of guilt (82.4%), stress (79.4%), and shame (75.0%). More than half of the respondents involved want substantive clarity (64.4%), and in case of 51.7% of the respondents, an open discussion with the patient and/or family took place afterwards. Conclusions: This study shows that GPs, even in training, can be negatively impacted after a PSI. Only half of the respondents were involved in an open disclosure process, but the ones involved had a positive feeling after disclosure. More support is needed for health care professionals in the aftermath of a PSI in primary care, and this support could enhance their involvement in the open disclosure process.

Patient safety in psychiatric inpatient facilities remains under-researched despite its crucial importance. This study aims to address this gap by using expert opinion to estimate the frequency of diverse patient safety incidents (PSIs) in psychiatric settings and to compare it with the existing literature. Utilizing a seven-step approach, a questionnaire based on the World Health Organization’s International Classification for Patient Safety was developed and deployed. A total of 33 expert opinions were collected. Results showed a higher estimated incidence of PSIs in psychiatric settings compared to general healthcare, highlighting categories such as patient behavior, medication, and infrastructure as significant contributors. Experts emphasized the prevalence of incidents related to behavioral issues and inadequate infrastructure, areas often overlooked in the existing literature. Unlike general settings, psychiatric facilities appear more vulnerable to specific PSIs, such as those related to medication and building safety, underscoring the need for targeted safety measures. Our study suggests the existence of significant discrepancies between expert opinion and available research, with several underexplored domains in psychiatric patient safety.