Objective: To assess individual variation in anxiety, stress disorder, depression, insomnia, burnout, and resilience in health care workers (HCWs), 12 and 18 months after the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Methods: Prospective longitudinal study. Results: A total of 207 HCWs (74% female, 46% physicians, 44% nurses) answered; 50% scored over the cut-off for anxiety (GAD-7), 66% for PCL-C, 41% for depression (PHQ-9), 25% for ISI, and 15% started sleep inducers; 52% showed emotional exhaustion (EE), 68% detachment (DE), 39% professional efficacy (EF) at MBI; 27% completed the follow-up questionnaire 6 months later, showing a significant reduction in nearly all scores (GAD-7 median 11[5-15] vs 7[4-12] (P < 0.001); PCL-C 43[30-58] vs 37[24-50] (P < 0.05); PHQ-9 10[4-16] vs 6[3-12] (P < 0.001); ISI 10[4-15] vs 7[5-12](NS); MBI EE 25[16-35] vs 23 [15-31] (NS), DE 13[8-17] vs 12[8-17], EF 29[25-34] vs 30[25-34]. Living in a flat (OR 2.27 [1.10-4.81], high-intensity-of-care working (2.83 [1.15-7.16] increased risk of anxiety (GAD-7); age between 31-40 y (OR 2.8 [1.11-7.68], being a nurse (OR 3.56 [1.59-8.36] and high-intensity-of-care working (OR 8.43 [2.92-26.8] increased risk of pathological stress (PCL-C). Conclusions: Nearly half of HCWs showed psychological distress, especially nurses, women, and the youngest. A mandatory job change, increasing intensity of care, working in a COVID-19 department, and being infected were negative factors; having a partner and living in a detached house were protective. Six months later, all the psychological domains showed individual improvement.

At the very beginning of the European spread of SARS-CoV-2, Piedmont was one of the most affected regions in Italy, with a strong impact on healthcare organizations. In this study, we evaluated the characteristics and outcomes of the COVID-19 patients in an entire region during the first three pandemic waves, identifying similarities and differences in the SARS-CoV-2 epidemic’s timeline. We collected the health-administrative data of all the Piedmont COVID-19 patients infected during the first three pandemic waves (1 March 2020–15 April 2020; 15 October 2020–15 December 2020; 1 March 2021–15 April 2021, respectively). We compared differences among the waves in subjects positive for SARS-CoV-2 and in patients admitted to ICU. Overall, 18.621 subjects tested positive during the first wave (405 patients/day), 144.350 (2366.4 patients/day) in the second, and 81.823 (1778.8 patients/day) in the third. In the second and third waves, we observed a reduction in median age, comorbidity burden, mortality in outpatients, inpatients, and patients admitted to ICU, in intubation, invasive ventilation and tracheostomy, and a parallel increase in the use of CPAP. Our study confirmed a trend towards younger and healthier patients over time but also showed an independent effect of the period on mortality and ICU admission. The appearance of new viral variants, the starting of vaccination, and organizational improvements in tracking, outpatients and inpatients management could have influenced these trends.

Background: Since the outbreak of the COVID-19 pandemic, identifying the main risk factors has been imperative to properly manage the public health challenges that the pandemic exposes, such as organizing effective vaccination campaigns. In addition to gender and age, multimorbidity seems to be 1 of the predisposing factors coming out of many studies investigating the possible causes of increased susceptibility to SARS-CoV-2 infection and adverse outcomes. However, only a few studies conducted have used large samples. Objective: The objective is to evaluate the association between multimorbidity, the probability to be tested, susceptibility, and the severity of SARS-CoV-2 infection in the Piedmont population (Northern Italy, about 4 million inhabitants). For this purpose, we considered 5 main outcomes: access to the swab, positivity to SARS-CoV-2, hospitalization, intensive care unit (ICU) admission, and death within 30 days from the first positive swab. Methods: Data were obtained from different Piedmont health administrative databases. Subjects aged from 45 to 74 years and infections diagnosed from February to May 2020 were considered. Multimorbidity was defined both with the Charlson Comorbidity Index (CCI) and by identifying patients with previous comorbidities, such as diabetes and oncological, cardiovascular, and respiratory diseases. Multivariable logistic regression models (adjusted for age and month of infection and stratified by gender) were performed for each outcome. Analyses were also conducted by separating 2 age groups (45-59 and 60-74 years). Results: Of 1,918,549 subjects, 85,348 (4.4%) performed at least 1 swab, of whom 12,793 (14.9%) tested positive for SARS-CoV-2. Of these 12,793 subjects, 4644 (36.3%) were hospitalized, 1508 (11.8%) were admitted to the ICU, and 749 (5.9%) died within 30 days from the first positive swab. Individuals with a higher CCI had a higher probability of being swabbed but a lower probability of testing positive. We observed the same results when analyzing subjects with previous oncological and cardiovascular diseases. Moreover, especially in the youngest group, we identified a greater risk of being hospitalized and dying. Among comorbidities considered in the study, respiratory diseases seemed to be the most likely to increase the risk of having a positive swab and worse disease outcomes. Conclusions: Our study shows that patients with multimorbidity, although swabbed more frequently, are less likely to get infected with SARS-CoV-2, probably due to greater attention on protective methods. Moreover, a history of respiratory diseases is a risk factor for a worse prognosis of COVID-19. Nonetheless, whatever comorbidities affect the patients, a strong dose-response effect was observed between an increased CCI score and COVID-19 hospitalization, ICU admission, and death. These results are important in terms of public health because they help in identifying a group of subjects who are more prone to worse SARS-CoV-2 outcomes. This information is important for promoting targeted prevention and developing policies for the prioritization of public health interventions.

Objective: To assess the psychological impact of a mass casualty incident (MCI) in a subset of personnel in a level I hospital.Methods: Emergency department staff responded to an MCI in June 2017 in Turin, Italy by an unexpected sudden surge of casualties following a stampede (mass escape). Participants completed the Psychological Simple Triage and Rapid Treatment Responder Self-Triage System (PsySTART-R), which classified the potential risk of psychological distress in “no risk” versus “at risk” categorization and identified a range of impacts aggregated for the population of medical responders. Participants were administered a questionnaire on the perceived effectiveness of management of the MCI. Two months later, the participants were evaluated using the Hospital Anxiety and Depression Scale (HADS), the Kessler Psychological Distress Scale (K6), and the Posttraumatic Stress Disorder Checklist (PCL-5).Results: The majority of the responders were classified as “no risk” by the PsySTART-R; no significant differences on HADS, K6, and PCL-5 were found in the participants grouped by the PsySTART-R categories. The personnel acquainted to work in emergency contexts (emergency department and intensive care unit) scored significantly lower in the HADS than the personnel usually working in other wards. The number of positive PsySTART-R criteria correlated with the HADS depression score.Conclusions: Most of the adverse psychological implications of the MCI were well handled and averted by the responders. A possible explanation could be related to factors such as the clinical condition of the victims (most were not severely injured, no fatalities), the small number of casualties (87) brought to the hospital, the event not being considered life-threatening, and its brief duration, among others. Responders had mainly to cope with a sudden surge in casualties and with organizational issues.

The prognostic value of mid-regional proADM (MR-proADM) in septic patients presenting to the emergency department (ED) is not well established. In this prospective observational study enrolling septic patients evaluated in two EDs, MR-proADM was measured at arrival (t0) and after 72 h (t72). MR-proADM_%change was calculated as follows: (MR-proADM_t72h − MR-proADM_t0)/MR-proADM_t0. In total, 147 patients were included in the study, including 109 with a final diagnosis of sepsis and 38 with septic shock, according to the Sepsis-3 criteria. The overall 28-day mortality (outcome) rate was 12.9%. The AUC for outcome prognostication was 0.66 (95% CI 0.51–0.80) for MR-proADM_t0, 0.77 (95% CI 0.63–0.92) for MR-proADM_t72 and 0.74 (95% CI 0.64–0.84) for MR-proADM_%change. MR-proADM_t0 ≥ 2.78 nmol/L, MR-proADM_t72 ≥ 2.7 nmol/L and MR-proADM_%change ≥ −15.2% showed statistically significant log-rank test results and sensitivity/specificity of 81/65%, 69/80% and 75/70% respectively. In regression analysis, MR-proADM_%change was a significant outcome predictor both in univariate and multivariate analysis, after adjustment for age, SOFA and APACHEII scores, providing up to 80% of added prognostic value. In conclusion, time trends of MR-proADM may provide additional insights for patient risk stratification over single sampling. MR-proADM levels sampled both at presentation and after 72 h predicted 28-day survival in septic patients presenting to the ED.