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The purpose of this document, a result of the harmonisation and revision of Guidelines published separately by the SIMFER, SIOMMMS/SIR, and SIOT associations, is to provide practical indications based on specific levels of evidence and various grades of recommendations, drawn from available literature, for the management of osteoporosis and for the diagnosis, prevention, and treatment of fragility fractures. These indications were discussed and formally approved by the delegates of the Italian Scientific Associations involved in the project (SIE, SIGG, SIMFER, SIMG, SIMI, SIOMMMS, SIR, and SIOT).

Several indicators reflect the quality of care within emergency departments (ED). The length of stay (LOS) of emergency patients represents one of the most important performance measures. Determinants of LOS have not yet been evaluated in large cohorts in Germany. This study analyzed the fixed and influenceable determinants of LOS by evaluating data from the German Emergency Department Data Registry (AKTIN registry). We performed a retrospective evaluation of all adult (age ≥ 18 years) ED patients enrolled in the AKTIN registry for the year 2019. Primary outcome was LOS for the whole cohort; secondary outcomes included LOS stratified by (1) patient-related, (2) organizational-related and (3) structure-related factors. Overall, 304,606 patients from 12 EDs were included. Average LOS for all patients was 3 h 28 min (95% CI 3 h 27 min–3 h 29 min). Regardless of other variables, patients admitted to hospital stayed 64 min longer than non-admitted patients. LOS increased with patients’ age, was shorter for walk-in patients compared to medical referral, and longer for non-trauma presenting complaints. Relevant differences were also found for acuity level, day of the week, and emergency care levels. We identified different factors influencing the duration of LOS in the ED. Total LOS was dependent on patient-related factors (age), disease-related factors (presentation complaint and triage level), and organizational factors (weekday and admitted/non-admitted status). These findings are important for the development of management strategies to optimize patient flow through the ED and thus to prevent overcrowding.

ML algorithms are used to develop prognostic and diagnostic models and so to support clinical decision-making. This study uses eight supervised ML algorithms to predict the need for intensive care, intubation, and mortality risk for COVID-19 patients. The study uses two datasets: (1) patient demographics and clinical data (n = 11,712), and (2) patient demographics, clinical data, and blood test results (n = 602) for developing the prediction models, understanding the most significant features, and comparing the performances of eight different ML algorithms. Experimental findings showed that all prognostic prediction models reported an AUROC value of over 0.92, in which extra tree and CatBoost classifiers were often outperformed (AUROC over 0.94). The findings revealed that the features of C-reactive protein, the ratio of lymphocytes, lactic acid, and serum calcium have a substantial impact on COVID-19 prognostic predictions. This study provides evidence of the value of tree-based supervised ML algorithms for predicting prognosis in health care.

In patients visiting the emergency department (ED), a potential association between electrolytes disturbance and coronavirus disease 2019 (COVID-19) has not been well studied. We aim to describe electrolyte disturbance and explore risk factors for COVID-19 infection in patients visiting the ED. We carried out a case–control study in three hospitals in France, including adult ED inpatients (≥ 18 years old). A total of 594 ED case patients in whom infection with COVID-19 was confirmed, were matched to 594 non-COVID-19 ED patients (controls) from the same period, according to sex and age. Hyponatremia was defined by a sodium of less than 135 mmol/L (reference range 135–145 mmol/L), hypokalemia by a potassium of less than 3.5 mmol/L (reference range 3.5–5.0 mmol/L), and hypochloremia by a chloride of less than 95 mmol/L (reference range 98–108 mmol/L). Among both case patients and controls, the median (IQR) age was 65 years (IQR 51–76), and 44% were women. Hyponatremia was more common among case patients than among controls, as was hypokalemia and hypochloremia. Based on the results of the multivariate logistic regression, hyponatremia, and hypokalemia were associated with COVID-19 among case patients overall, with an adjusted odds ratio of 1.89 [95% CI 1.24–2.89] for hyponatremia and 1.76 [95% CI 1.20–2.60] for hypokalemia. Hyponatremia and hypokalemia are independently associated with COVID-19 infection in adults visiting the ED, and could act as surrogate biomarkers for the emergency physician in suspected COVID-19 patients.

BackgroundAssessing the evolutive risk of septic patients in the emergency department (ED) is very complex. Predictive tools are available, but at an early stage, none of them can detect the tissue microvascular alterations underlying the septic process. Hypoalbuminemia is present in critically ill patients in the ICU, and some early indications also suggest its early role in septic patients.AimTo investigate the role of serum albumin concentration in predicting 30-day mortality among patients with sepsis at their first evaluation in the ED.MethodsProspective observational study enrolling all patients with sepsis evaluated consecutively at the ED of the Merano Hospital from January to December 2021. The serum albumin concentration on admission was measured immediately upon patient arrival. A multivariate logistic regression model adjusted for possible confounders assessed the association between albumin levels at admission and 30-day mortality. Kaplan–Meier survival analysis was used to evaluate 30-day mortality between groups, and receiver operating characteristic (ROC) curve analysis was used to assess the discriminatory ability of albumin in predicting mortality.Results459 patients with community-acquired sepsis were included. 17% (78/459) of patients died within 30 days. In surviving patients, the mean albumin level was 3.6 g/dL (SD 0.5), while among non-survivors it was 3.1 g/dL (SD 0.4), p < 0.001. The area under the ROC was 0.754 (95% CI 0.701–0.807). Multivariate analysis found that albumin was an independent risk factor for 30-day mortality, with an adjusted risk ratio of 2.991 (95% CI 1.619–5.525, p < 0.001) for each 1 g/dL decrease in albumin.ConclusionsSerum albumin concentration measured during initial ED assessment can be a useful prognostic marker of 30-day mortality in septic patients.

The first wave (FW) of COVID-19 led to a rapid reduction in total emergency department (ED) visits and hospital admissions for other diseases. Whether this represented a transient “lockdown and fear” phenomenon, or a more persisting trend, is unknown. We divided acute from post-wave changes in ED flows, diagnoses, and hospital admissions, in an Italian city experiencing a FW peak followed by nadir. This multicenter, retrospective, cross-sectional study involved five general EDs of a large Italian city (January–August 2020). Percent changes were calculated versus 2019, using four 14-day periods (FW peak, early/mid/late post-wave). ED visits were 147,446 in 2020, versus 214,868 in 2019. During the FW peak, visits were reduced by 66.4% (P < 0.001). The drop was maximum during daytime (69.8%) and for pediatric patients (89.4%). Critical triage codes were unchanged. Reductions were found for all non-COVID-19 diagnoses. Non-COVID-19 hospital admissions were reduced by 39.5% (P < 0.001), involving all conditions except hematologic, metabolic/endocrine, respiratory diseases, and traumas. In the early, mid, and late post-wave periods, visits were reduced by 25.4%, 25.3% and 23.5% (all P < 0.001) respectively. In the late period, reduction was greater for female (27.9%) and pediatric patients (44.6%). Most critical triage codes were unchanged. Oncological, metabolic/endocrine, and hematological diagnoses were unchanged, while other diagnoses had persistent reductions. Non-COVID-19 hospital admissions were reduced by 12.8% (P = 0.001), 6.3% (P = 0.1) and 12.2% (P = 0.001), respectively. Reductions in ED flows, led by non-critical codes, persisted throughout the summer nadir of COVID-19. Hospital admissions for non-COVID-19 diseases had transient changes.

This study explored the relationship between body temperature and adverse outcomes in patients with heat stroke to identify the optimal target body temperature within the first 24 h. This retrospective, multicentre study enrolled 143 patients admitted to the emergency department and diagnosed with heat stroke. The primary outcome was the in-hospital mortality rate, while secondary outcomes included the presence and number of damaged organs and neurological sequelae at discharge. A body temperature curve was built using a generalized additive mixed model, and the association between body temperatures and outcomes was established by logistic regression. The threshold and saturation effects were used to explore the targeted body temperature management. Cases were divided into the surviving and non-surviving groups. The cooling rate within the first 2 h was significantly higher in the survival group than the non-survival group (β: 0.47; 95% confidence interval [CI]: 0.09–0.84; P = 0.014), while the non-survival group exhibited a lower body temperature within 24 h (β: − 0.06; 95% CI: − 0.08 to − 0.03; P ≤ 0.001). Body temperature after 2 h (odds ratio [OR]: 2.27; 95% CI: 1.14–4.50; P = 0.019) and lowest temperature within 24 h (OR: 0.18; 95% CI: 0.06–0.55; P = 0.003) were significantly related to in-hospital mortality rate. When the body temperature at 0.5 h was 38.5–40.0 °C, the number of damaged organs was at its lowest. In patients with heat stroke, both hyperthermia and hypothermia were associated with adverse outcomes. Hence, an accurate body temperature management is required during the early stages of care.

Some patients affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) experience acute hypoxemic respiratory failure progressing toward atypical acute respiratory distress syndrome (ARDS). The aim of the study is to evaluate whether a correlation between ratio of peripheral saturation of oxygen (SpO2) and fraction of inspired oxygen (S/F) and ratio of arterial partial pressure of oxygen and fraction of inspired oxygen (P/F) exists in COVID-19-related ARDS as already known in classical ARDS. In this multicenter, retrospective, observational study, consecutive, adult (≥ 18 years) patients with symptomatic coronavirus disease 2019 (COVID-19) admitted to different COVID-19 divisions in Italy between March and December 2020 were included. Patients with SpO2 > 97% or missing information were excluded. We included 1,028 patients (median age 72 years, prevalence of males [62.2%]). A positive correlation was found between P/F and S/F (r = 0.938, p < 0.0001). A receiver operating characteristic (ROC) curve analysis showed that S/F accurately recognizes the presence of ARDS (P/F ≤ 300 mmHg) in COVID-19 patients, with a cut-off of ≤ 433% showing good sensitivity and specificity. S/F was also tested against P/F values ≤ 200 and ≤ 100 mmHg (suggestive for moderate and severe ARDS, respectively), the latter showing great accuracy for S/F ≤ 178%. S/F was accurate in predicting ARDS for SpO2 ≥ 92%. In conclusion, our findings support the routine use of S/F as a reliable surrogate of P/F in patients with COVID-19-related ARDS.

Several widely used scoring systems for septic patients have been validated in an ICU setting, and may not be appropriate for other settings like Emergency Departments (ED) or High-Dependency Units (HDU), where a relevant number of these patients are managed. The purpose of this study is to find reliable tools for prognostic assessment of septic patients managed in an ED-HDU. In 742 patients diagnosed with sepsis/severe sepsis/septic shock, not-intubated, admitted in ED between June 2008 and April 2016, SOFA, qSOFA, PIRO, MEWS, Charlson Comorbidity Index, MEDS, and APACHE II were calculated at ED admission (T0); SOFA and MEWS were also calculated after 24 h of ED-High-Dependency Unit stay (T1). Discrimination and incremental prognostic value of SOFA score over demographic data and parameters of sepsis severity were tested. Primary outcome is 28-day mortality. Twenty-eight day mortality rate is 31%. The different scores show a modest-to-moderate discrimination (T0 SOFA 0.695; T1 SOFA 0.741; qSOFA 0.625; T0 MEWS 0.662; T1 MEWS 0.729; PIRO: 0.646; APACHE II 0.756; Charlson Comorbidity Index 0.596; MEDS 0.674, all p < 0.001). At a multivariate stepwise Cox analysis, including age, Charlson Comorbidity Index, MEWS, and lactates, SOFA shows an incremental prognostic ability both at T0 (RR 1.165, IC 95% 1.009–1.224, p < 0.0001) and T1 (RR 1.168, IC 95% 1.104–1.234, p < 0.0001). SOFA score shows a moderate prognostic stratification ability, and demonstrates an incremental prognostic value over the previous medical conditions and clinical parameters in septic patients.

The current evidence suggests that higher levels of crowding in the Emergency Department (ED) have a negative impact on patient outcomes, including mortality. However, only limited data are available about the association between crowding and mortality, especially for patients discharged from the ED. The primary objective of this study was to establish the association between ED crowding and overall 10-day mortality for non-critical patients. The secondary objective was to perform a subgroup analysis of mortality risk separately for both admitted and discharged patients. An observational single-centre retrospective study was conducted in the Tampere University Hospital ED from January 2018 to February 2020. The ED Occupancy Ratio (EDOR) was used to describe the level of crowding and it was calculated both at patient’s arrival and at the maximum point during the stay in the ED. Age, gender, Emergency Medical Service transport, triage acuity, and shift were considered as confounding factors in the analyses. A total of 103,196 ED visits were included. The overall 10-day mortality rate was 1.0% (n = 1022). After controlling for confounding factors, the highest quartile of crowding was identified as an independent risk factor for 10-day mortality. The results were essentially similar whether using the EDOR at arrival (OR 1.31, 95% CI 1.07–1.61, p = 0.009) or the maximum EDOR (OR 1.27, 95% CI 1.04–1.56, p = 0.020). A more precise, mortality-associated threshold of crowding was identified at EDOR 0.9. The subgroup analysis did not yield any statistically significant findings. The risk for 10-day mortality increased among non-critical ED patients treated during the highest EDOR quartile.