The use of extracorporeal blood purification therapies and sequential extracorporeal support in patients with septic shock (EROICASS): a study protocol for a national, non-interventional, observational multicenter, prospective study.

BACKGROUND: Septic shock, a critical condition characterized by organ failure, presents a substantial mortality risk in intensive care units (ICUs), with the 28-day mortality rate possibly reaching 40%. Conventional management of septic shock typically involves the administration of antibiotics, supportive care for organ dysfunction, and, if necessary, surgical intervention to address the source of infection. In recent decades, extracorporeal blood purification therapies (EBPT) have emerged as potential interventions aimed at modulating the inflammatory response and restoring homeostasis in patients with sepsis. Likewise, sequential extracorporeal therapy in sepsis (SETS) interventions offer comprehensive organ support in the setting of multiple organ dysfunction syndrome (MODS). The EROICASS study will assess and describe the utilization of EBPT in patients with septic shock. Additionally, we will evaluate the potential association between EBPT treatment utilization and 90-day mortality in septic shock cases in Italy. METHODS: The EROICASS study is a national, non-interventional, multicenter observational prospective cohort study. All consecutive patients with septic shock at participating centers will be prospectively enrolled, with data collection extending from intensive care unit (ICU) admission to hospital discharge. Variables including patient demographics, clinical parameters, EBPT/SETS utilization, and outcomes will be recorded using a web-based data capture system. Statistical analyses will encompass descriptive statistics, hypothesis testing, multivariable regression models, and survival analysis to elucidate the associations between EBPT/SETS utilization and patient outcomes. CONCLUSIONS: The EROICASS study provides valuable insights into the utilization and outcomes of EBPT and SETS in septic shock management. Through analysis of usage patterns and clinical data, this study aims to guide treatment decisions and enhance patient care. The implications of these findings may impact clinical guidelines, potentially improving survival rates and patient outcomes in septic shock cases.

Early mobilisation in critically ill COVID-19 patients: a subanalysis of the ESICM-initiated UNITE-COVID observational study.

BACKGROUND: Early mobilisation (EM) is an intervention that may improve the outcome of critically ill patients. There is limited data on EM in COVID-19 patients and its use during the first pandemic wave. METHODS: This is a pre-planned subanalysis of the ESICM UNITE-COVID, an international multicenter observational study involving critically ill COVID-19 patients in the ICU between February 15th and May 15th, 2020. We analysed variables associated with the initiation of EM (within 72 h of ICU admission) and explored the impact of EM on mortality, ICU and hospital length of stay, as well as discharge location. Statistical analyses were done using (generalised) linear mixed-effect models and ANOVAs. RESULTS: Mobilisation data from 4190 patients from 280 ICUs in 45 countries were analysed. 1114 (26.6%) of these patients received mobilisation within 72 h after ICU admission; 3076 (73.4%) did not. In our analysis of factors associated with EM, mechanical ventilation at admission (OR 0.29; 95% CI 0.25, 0.35; p = 0.001), higher age (OR 0.99; 95% CI 0.98, 1.00; p ≤ 0.001), pre-existing asthma (OR 0.84; 95% CI 0.73, 0.98; p = 0.028), and pre-existing kidney disease (OR 0.84; 95% CI 0.71, 0.99; p = 0.036) were negatively associated with the initiation of EM. EM was associated with a higher chance of being discharged home (OR 1.31; 95% CI 1.08, 1.58; p = 0.007) but was not associated with length of stay in ICU (adj. difference 0.91 days; 95% CI - 0.47, 1.37, p = 0.34) and hospital (adj. difference 1.4 days; 95% CI - 0.62, 2.35, p = 0.24) or mortality (OR 0.88; 95% CI 0.7, 1.09, p = 0.24) when adjusted for covariates. CONCLUSIONS: Our findings demonstrate that a quarter of COVID-19 patients received EM. There was no association found between EM in COVID-19 patients' ICU and hospital length of stay or mortality. However, EM in COVID-19 patients was associated with increased odds of being discharged home rather than to a care facility. Trial registration ClinicalTrials.gov: NCT04836065 (retrospectively registered April 8th 2021).

Management of hospital admission, patient information and education, and immediate preoperative care.

An increasing proportion of surgical procedures involves elderly and frail patients in high-income countries, leading to an increased risk of postoperative complications. Complications significantly impact patient outcomes and costs, due to prolonged hospitalization and loss of autonomy. Consequently, it is crucial to evaluate preoperative functional status in older patients, to tailor the perioperative plan, and evaluate risks. The hospital environment often exacerbates cognitive impairments in elderly and frail patients, also increasing the risk of infection, falls, and malnutrition. Thus, it is essential to work on dedicated pathways to reduce hospital readmissions and favor discharges to a familiar environment. In this context, the use of wearable devices and telehealth has been promising. Telemedicine can be used for preoperative evaluations and to allow earlier discharges with continuous monitoring. Wearable devices can track patient vitals both preoperatively and postoperatively. Preoperative education of patient and caregivers can improve postoperative outcomes and is favored by technology-based approach that increases flexibility and reduce the need for in-person clinical visits and associated travel; moreover, such approaches empower patients with a greater understanding of possible risks, moving toward shared decision-making principles. Finally, caregivers play an integral role in patient improvement, for example, in the prevention of delirium. Hence, their inclusion in the care process is not only advantageous but essential to improve perioperative outcomes in this population.

The Good, the Bad, and the Serum Creatinine: Exploring the Effect of Muscle Mass and Nutrition.

Muscle wasting (sarcopenia) is one of the hallmarks of critical illness. Patients admitted to intensive care unit develop sarcopenia through increased protein catabolism, a decrease in protein syntheses, or both. Among the factors known to promote wasting are chronic inflammation and cytokine imbalance, insulin resistance, hypermetabolism, and malnutrition. Moreover, muscle wasting, known to develop in chronic kidney disease patients, is a harmful consequence of numerous complications associated with deteriorated renal function. Plenty of published data suggest that serum creatinine (SCr) reflects increased kidney damage and is also related to body weight. Based on the concept that urea and creatinine are nitrogenous end products of metabolism, the urea:creatinine ratio (UCR) could be applied but with limited clinical usability in case of kidney damage, hypovolemia, excessive, or protein intake, where UCR can be high and independent of catabolism. Recent data suggest that the sarcopenia index should be considered an alternative to serum creatinine. It is more reliable in estimating muscle mass than SCr. However, the optimal biomarker of catabolism is still an unresolved issue. The SCr is not a promising biomarker for renal function and muscle mass based on the influence of several factors. The present review highlights recent findings on the limits of SCr as a surrogate marker of renal function and the assessment modalities of nutritional status and muscle mass measurements.

One-Lung Ventilation and Postoperative Pulmonary Complications After Major Lung Resection Surgery. A Multicenter Randomized Controlled Trial.

OBJECTIVES: The effect of one-lung ventilation (OLV) strategy based on low tidal volume (TV), application of positive end-expiratory pressure (PEEP), and alveolar recruitment maneuvers (ARM) to reduce postoperative acute respiratory distress syndrome (ARDS) and pulmonary complications (PPCs) compared with higher TV without PEEP and ARM strategy in adult patients undergoing lobectomy or pneumonectomy has not been well established. DESIGN: Multicenter, randomized, single-blind, controlled trial. SETTING: Sixteen Italian hospitals. PARTICIPANTS: A total of 880 patients undergoing elective major lung resection. INTERVENTIONS: Patients were randomized to receive lower tidal volume (LTV group: 4 mL/kg predicted body weight, PEEP of 5 cmH2O, and ARMs) or higher tidal volume (HTL group: 6 mL/kg predicted body weight, no PEEP, and no ARMs). After OLV, until extubation, both groups were ventilated using a tidal volume of 8 mL/kg and a PEEP value of 5 cmH2O. The primary outcome was the incidence of in-hospital ARDS. Secondary outcomes were the in-hospital rate of PPCs, major cardiovascular events, unplanned intensive care unit (ICU) admission, in-hospital mortality, ICU length of stay, and in-hospital length of stay. MEASUREMENTS AND MAIN RESULTS: ARDS occurred in 3 of 438 patients (0.7%, 95% CI 0.1-2.0) and in 1 of 442 patients (0.2%, 95% CI 0-1.4) in the LTV and HTV group, respectively (Risk ratio: 3.03 95% CI 0.32-29, p = 0.372). Pulmonary complications occurred in 125 of 438 patients (28.5%, 95% CI 24.5-32.9) and in 136 of 442 patients (30.8%, 95% CI 26.6-35.2) in the LTV and HTV group, respectively (risk ratio: 0.93, 95% CI 0.76-1.14, p = 0.507). The incidence of major complications, in-hospital mortality, and unplanned ICU admission, ICU and in-hospital length of stay were comparable in both groups. CONCLUSIONS: In conclusion, among adult patients undergoing elective lung resection, an OLV with lower tidal volume, PEEP 5 cmH2O, and ARMs and a higher tidal volume strategy resulted in low ARDS incidence and comparable postoperative complications, in-hospital length of stay, and mortality.

Postoperative pulmonary complications and mortality after major abdominal surgery. An observational multicenter prospective study.

BACKGROUND: Postoperative pulmonary complications (PPCs) significantly contribute to postoperative morbidity and mortality. We conducted a study to determine the incidence of PPCs after major elective abdominal surgery and their association with early and 1-year mortality in patient without pre-existing respiratory disease. METHODS: We conducted a multicenter observational prospective clinical study in 40 Italian centers. 1542 patients undergoing elective major abdominal surgery were recruited in a time period of 14 days and clinically managed according to local protocol. The primary outcome was to determine the incidence of PPCs. Further, we aimed to identify independent predictors for PPCs and examine the association between PPCs and mortality. RESULTS: PPCs occurred in 12.6% (95% CI 11.1-14.4%) of patients with significant differences among general (18.3%, 95% CI 15.7-21.0%), gynecological (3.7%, 95% CI 2.1-6.0%) and urological surgery (9.0%, 95% CI 6.0-12.8%). PPCs development was associated with known pre- and intraoperative risk factors. Patients who developed PPCs had longer length of hospital stay, higher risk of 30-days hospital readmission, and increased in-hospital and one-year mortality (OR 3.078, 95% CI 1.825-5.191; P<0.001). CONCLUSIONS: The incidence of PPCs in patients without pre-existing respiratory disease undergoing elective abdominal surgery is high and associated with worse clinical outcome at one year after surgery. General surgery is associated with higher incidence of PPCs and mortality compared to gynecological and urological surgery.

Implementing Artificial Intelligence: Assessing the Cost and Benefits of Algorithmic Decision-Making in Critical Care.

This article provides an overview of the most useful artificial intelligence algorithms developed in critical care, followed by a comprehensive outline of the benefits and limitations. We begin by describing how nurses and physicians might be aided by these new technologies. We then move to the possible changes in clinical guidelines with personalized medicine that will allow tailored therapies and probably will increase the quality of the care provided to patients. Finally, we describe how artificial intelligence models can unleash researchers' minds by proposing new strategies, by increasing the quality of clinical practice, and by questioning current knowledge and understanding.

Sepsis-induced Coagulopathy Subphenotype Identification by Latent Class Analysis

Background: Recent studies have shown that anticoagulant therapy has heterogeneous treatment effects on patients with sepsis-induced coagulopathy (SIC). Aims: To identify the latent phenotypes of patients with SIC. Study design: Retrospective cohort study. Methods: We obtained data of patients with SIC from the Medical Information Mart for Intensive Care IV database. SIC subphenotypes were identified by latent class analysis (LCA) and K-means clustering. Clinical and laboratory variables were obtained in patients who met the diagnostic criteria for SIC. The baseline characteristics of the patients and the association between the heterogeneity of anticoagulant therapy and clinical outcomes (28-day and in-hospital mortality) were compared between the subphenotypes. Results: We identified 4,993 patients with SIC. The LCA and K-means clustering analysis robustly identified three subphenotypes of SIC. Class 1 patients (n = 1,808) had the lowest blood cell counts (leukocytes, erythrocytes, and platelets). Class 2 patients (n = 1,157) had severe coagulopathy with a high prothrombin time and international normalized ratio, multiple-organ dysfunction, high lactate, sequential organ failure assessment score, and mortality. Class 3 (n = 2,028) were older, had more comorbidities, a higher fibrinogen concentration, and lower plasma and platelet infusion rates. After variable adjustments, heparin therapy reduced the 28-day mortality (odds ratio [OR] 0.39, 0.30-0.49, p < 0.001) and in-hospital mortality (OR 0.42, 0.33-0.53, p < 0.001) only in class 2. Conclusion: Three SIC subphenotypes were defined using clinical findings and laboratory variables. The effects of heparin treatment differ between the subphenotypes. This finding will facilitate the identification of target patients with SIC who should receive anticoagulant therapy.

Thoracic UltrasONOgraphy Reporting: The TUONO Consensus.

The widespread use of the lung ultrasound (LUS) has not been followed by the development of a comprehensive standardized tool for its reporting in the intensive care unit (ICU) which could be useful to promote consistency and reproducibility during clinical examination. This work aims to define the essential features to be included in a standardized reporting tool and provides a structured model form to fully express the diagnostic potential of LUS and facilitate intensivists in the use of a LUS in everyday clinical ICU examination. We conducted a modified Delphi process to build consensus on the items to be integrated in a standardized report form and on its structure. A committee of 19 critical care physicians from 19 participating ICUs in Italy was formed, including intensivists experienced in ultrasound from both teaching hospitals and referral hospitals, and internationally renowned experts on the LUS. The consensus for 31 statements out of 33 was reached at the third Delphi round. A structured model form was developed based on the approved statements. The development of a standardized model as a backbone to report a LUS may facilitate the guidelines' application in clinical practice and increase inter-operator agreement. Further studies are needed to evaluate the effects of standardized reports in critically ill patients.

Fitbit Data to Assess Functional Capacity in Patients Before Elective Surgery: Pilot Prospective Observational Study.

BACKGROUND: Preoperative assessment is crucial to prevent the risk of complications of surgical operations and is usually focused on functional capacity. The increasing availability of wearable devices (smartwatches, trackers, rings, etc) can provide less intrusive assessment methods, reduce costs, and improve accuracy. OBJECTIVE: The aim of this study was to present and evaluate the possibility of using commercial smartwatch data, such as those retrieved from the Fitbit Inspire 2 device, to assess functional capacity before elective surgery and correlate such data with the current gold standard measure, the 6-Minute Walk Test (6MWT) distance. METHODS: During the hospital visit, patients were evaluated in terms of functional capacity using the 6MWT. Patients were asked to wear the Fitbit Inspire 2 for 7 days (with flexibility of -2 to +2 days) after the hospital visit, before their surgical operation. Resting heart rate and daily steps data were retrieved directly from the smartwatch. Feature engineering techniques allowed the extraction of heart rate over steps (HROS) and a modified version of Non-Exercise Testing Cardiorespiratory Fitness. All measures were correlated with 6MWT. RESULTS: In total, 31 patients were enrolled in the study (n=22, 71% men; n=9, 29% women; mean age 76.06, SD 4.75 years). Data were collected between June 2021 and May 2022. The parameter that correlated best with the 6MWT was the Non-Exercise Testing Cardiorespiratory Fitness index (r=0.68; P<.001). The average resting heart rate over the whole acquisition period for each participant had r=-0.39 (P=.03), even if some patients did not wear the device at night. The correlation of the 6MWT distance with the HROS evaluated at 1% quantile was significant, with Pearson coefficient of -0.39 (P=.04). Fitbit step count had a fair correlation of 0.59 with 6MWT (P<.001). CONCLUSIONS: Our study is a promising starting point for the adoption of wearable technology in the evaluation of functional capacity of patients, which was strongly correlated with the gold standard. The study also identified limitations in the availability of metrics, variability of devices, accuracy and quality of data, and accessibility as crucial areas of focus for future studies.

Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study.

Preoperative identification of high-risk groups has been extensively studied to improve patients' outcomes. Wearable devices, which can track heart rate and physical activity data, are starting to be evaluated for patients' management. We hypothesized that commercial wearable devices (WD) may provide data associated with preoperative evaluation scales and tests, to identify patients with poor functional capacity at increased risk for complications. We conducted a prospective observational study including seventy-year-old patients undergoing two-hour surgeries under general anesthesia. Patients were asked to wear a WD for 7 days before surgery. WD data were compared to preoperatory clinical evaluation scales and with a 6-min walking test (6MWT). We enrolled 31 patients, with a mean age of 76.1 (SD ± 4.9) years. There were 11 (35%) ASA 3-4 patients. 6MWT results averaged 328.9 (SD ± 99.5) m. Daily steps and 𝑉𝑂2𝑚𝑎𝑥 as recorded using WD and were associated with 6MWT performance (R = 0.56, p = 0.001 and r = 0.58, p = 0.006, respectively) and clinical evaluation scales. This is the first study to evaluate WD as preoperative evaluation tools; we found a strong association between 6MWT, preoperative scales, and WD data. Low-cost wearable devices are a promising tool for the evaluation of cardiopulmonary fitness. Further research is needed to validate WD in this setting.

Kinetics of the Cell Cycle Arrest Biomarkers (TIMP2 and IGFBP7) for the Diagnosis of Acute Kidney Injury in Critically Ill COVID-19 Patients.

BACKGROUND: Acute kidney injury (AKI) is highly prevalent in critical COVID-19 patients. The diagnosis and staging of AKI are based on serum creatinine (sCr) and urinary output criteria, with limitations in the functional markers. New cell-cycle arrest biomarkers [TIMP2]*[IGFBP7] have been proposed for early detection of AKI, but their role in critically ill COVID-19 patients is poorly understood. METHODS: We conducted an observational study to assess the performance of [TIMP2]*[IGFBP7] for the detection of AKI in critical COVID-19 patients admitted to our intensive care unit (ICU). We sampled urinary [TIMP2]*[IGFBP7] levels at ICU admission, 12 h, 24 h, and 48 h, and compared the results to the development of AKI, as well as baseline and laboratory data. RESULTS: Forty-one patients were enrolled. The median age was 66 years [57-72] and most were males (85%). Thirteen patients (31.7%) developed no/mild stage AKI, 19 patients (46.3%) moderate AKI, and nine patients (22.0%) severe AKI. The ICU mortality was 29.3%. sCr levels in the Emergency Department or at ICU admission were not significantly different according to AKI stage. [TIMP-2]*[IGFBP-7] urinary levels were elevated in severe AKI at 12 h after ICU admission, but not at ICU admission or 24 h or 48 h after ICU admission. CONCLUSION: Urinary biomarkers [TIMP-2]*[IGFBP-7] were generally increased in this population with a high prevalence of AKI, and were higher in patients with severe AKI measured at 12 h from ICU admission. Further studies are needed to evaluate the best timing of these biomarkers in this population.

REVersal of nEuromusculAr bLocking Agents in Patients Undergoing General Anaesthesia (REVEAL Study).

Background: Neuromuscular blocking agent (NMBA) monitoring and reversals are key to avoiding residual curarization and improving patient outcomes. Sugammadex is a NMBA reversal with favorable pharmacological properties. There is a lack of real-world data detailing how the diffusion of sugammadex affects anesthetic monitoring and practice. Methods: We conducted an electronic health record analysis study, including all adult surgical patients undergoing general anesthesia with orotracheal intubation, from January 2016 to December 2019, to describe changes and temporal trends of NMBAs and NMBA reversals administration. Results: From an initial population of 115,046 surgeries, we included 37,882 procedures, with 24,583 (64.9%) treated with spontaneous recovery from neuromuscular block and 13,299 (35.1%) with NMBA reversals. NMBA reversals use doubled over 4 years from 25.5% to 42.5%, mainly driven by sugammadex use, which increased from 17.8% to 38.3%. Rocuronium increased from 58.6% (2016) to 94.5% (2019). Factors associated with NMBA reversal use in the multivariable analysis were severe obesity (OR 3.33 for class II and OR 11.4 for class III obesity, p-value < 0.001), and high ASA score (OR 1.47 for ASA III). Among comorbidities, OSAS, asthma, and other respiratory diseases showed the strongest association with NMBA reversal administration. Conclusions: Unrestricted availability of sugammadex led to a considerable increase in pharmacological NMBA reversal, with rocuronium use also rising. More research is needed to determine how unrestricted and safer NMBA reversal affects anesthesia intraoperative monitoring and practice.

Thoracic UltrasONOgraphy Reporting: The TUONO Study.

Lung ultrasound (LUS) is a validated technique for the prompt diagnosis and bedside monitoring of critically ill patients due to its availability, safety profile, and cost-effectiveness. The aim of this work is to detect similarities and differences among LUS reports performed in ICUs and to provide a common ground for an integrated report form. We collected all LUS reports during an index week in 21 ICUs from the GiViTI network. First, we considered signs, chest areas, and terminology reported. Then, we compared different report structures and categorized them as structured reports (SRs), provided with a predefined model form, and free unstructured text reports (FTRs) that had no predetermined structure. We analyzed 171 reports from 21 ICUs, and 59 reports from 5 ICUs were structured. All the reports presented a qualitative description that mainly focused on the presence of B-lines, consolidations, and pleural effusion. Zones were defined in 66 reports (39%). In SRs, a complete examination of all the regions was more frequently achieved (96% vs. 74%), and a higher impact on therapeutic strategies was observed (17% vs. 6%). LUS reports vary significantly among different centers. Adopting an integrated SR seems to promote a systematic approach in scanning and reporting, with a potential impact on LUS clinical applications.

Incidence of Acute Kidney Injury in Polytrauma Patients and Predictive Performance of TIMP2 × IGFBP7 Biomarkers for Early Identification of Acute Kidney Injury.

Background: Acute kidney injury (AKI) is a common cause of organ failure in trauma patients who survive their initial injuries. It is independently associated with increased morbidity and mortality and prolongs the length of hospital stays. The objectives of this study were to describe the incidence of early AKI and influence of risk factors in polytrauma patients and evaluate the predictive potential of TIMP2 × IGFBP7 biomarkers in this patient cohort. Methods: We conducted a retrospective cohort study of severely injured adult patients who were consecutively admitted to a multidisciplinary ICU from May 2017 to May 2019. Detailed patient data was retrieved from ICU medical records. Fluid balance, urinary output, and sCr values up to 72 h were collected. Urine samples for measuring TIMP2 × IGFBP7 concentrations were obtained and analyzed from ICU admission to 72 h. Results: Among the 153 patients eligible for analysis, 45 were included in the AKI, and 108 in the no AKI cohorts. The incidence of AKI within 72 h, based on KDIGO criteria, was 28.8%. There were no differences in ISS, type and mechanism of injury, heart rate, and systolic BP at admission between groups. Patients with early AKI were older (68 vs. 49 years, p < 0.001), obese (BMI 26.2 vs. 24.7, p < 0.048), and more likely to have previous cardiac disease (27% vs. 5.6%, p < 0.001). TIMP2 × IGFBP7 values on ICU admission were associated with subsequent AKI in patients without evidence of AKI at the time of ICU admission. They were also higher in the AKI cohort and significantly correlated with renal replacement therapy (RRT) and episodes of hypotension. Multivariable analysis confirmed age, previous cardiac disease, and NephroCheck as the variables mostly associated with AKI, with AUC 0.792. Conclusions: TIMP2 × IGFBP7 may help identify trauma patients with tubular damage that may evolve into a clinically manifested syndrome. Prospective studies of TIMP2 × IGFBP7, as a trigger for early AKI bundle care, are warranted.

Impact of dexamethasone on the incidence of ventilator-associated pneumonia in mechanically ventilated COVID-19 patients: a propensity-matched cohort study.

OBJECTIVE: To assess the impact of treatment with steroids on the incidence and outcome of ventilator-associated pneumonia (VAP) in mechanically ventilated COVID-19 patients. DESIGN: Propensity-matched retrospective cohort study from February 24 to December 31, 2020, in 4 dedicated COVID-19 Intensive Care Units (ICU) in Lombardy (Italy). PATIENTS: Adult consecutive mechanically ventilated COVID-19 patients were subdivided into two groups: (1) treated with low-dose corticosteroids (dexamethasone 6 mg/day intravenous for 10 days) (DEXA+); (2) not treated with corticosteroids (DEXA-). A propensity score matching procedure (1:1 ratio) identified patients' cohorts based on: age, weight, PEEP Level, PaO2/FiO2 ratio, non-respiratory Sequential Organ Failure Assessment (SOFA) score, Charlson Comorbidity Index (CCI), C reactive protein plasma concentration at admission, sex and admission hospital (exact matching). INTERVENTION: Dexamethasone 6 mg/day intravenous for 10 days from hospital admission. MEASUREMENTS AND MAIN RESULTS: Seven hundred and thirty-nine patients were included, and the propensity-score matching identified two groups of 158 subjects each. Eighty-nine (56%) DEXA+ versus 55 (34%) DEXA- patients developed a VAP (RR 1.61 (1.26-2.098), p = 0.0001), after similar time from hospitalization, ICU admission and intubation. DEXA+ patients had higher crude VAP incidence rate (49.58 (49.26-49.91) vs. 31.65 (31.38-31.91)VAP*1000/pd), (IRR 1.57 (1.55-1.58), p < 0.0001) and risk for VAP (HR 1.81 (1.31-2.50), p = 0.0003), with longer ICU LOS and invasive mechanical ventilation but similar mortality (RR 1.17 (0.85-1.63), p = 0.3332). VAPs were similarly due to G+ bacteria (mostly Staphylococcus aureus) and G- bacteria (mostly Enterobacterales). Forty-one (28%) VAPs were due to multi-drug resistant bacteria. VAP was associated with almost doubled ICU and hospital LOS and invasive mechanical ventilation, and increased mortality (RR 1.64 [1.02-2.65], p = 0.040) with no differences among patients' groups. CONCLUSIONS: Critically ill COVID-19 patients are at high risk for VAP, frequently caused by multidrug-resistant bacteria, and the risk is increased by corticosteroid treatment. TRIAL REGISTRATION: NCT04388670, retrospectively registered May 14, 2020.

Outcome prediction during an ICU surge using a purely data-driven approach: A supervised machine learning case-study in critically ill patients from COVID-19 Lombardy outbreak.

PURPOSE: COVID-19 disease frequently affects the lungs leading to bilateral viral pneumonia, progressing in some cases to severe respiratory failure requiring ICU admission and mechanical ventilation. Risk stratification at ICU admission is fundamental for resource allocation and decision making. We assessed performances of three machine learning approaches to predict mortality in COVID-19 patients admitted to ICU using early operative data from the Lombardy ICU Network. METHODS: This is a secondary analysis of prospectively collected data from Lombardy ICU network. A logistic regression, balanced logistic regression and random forest were built to predict survival on two datasets: dataset A included patient demographics, medications before admission and comorbidities, and dataset B included respiratory data the first day in ICU. RESULTS: Models were trained on 1484 patients on four outcomes (7/14/21/28 days) and reached the greatest predictive performance at 28 days (F1-score: 0.75 and AUC: 0.80). Age, number of comorbidities and male gender were strongly associated with mortality. On dataset B, mode of ventilatory assistance at ICU admission and fraction of inspired oxygen were associated with an increase in prediction performances. CONCLUSIONS: Machine learning techniques might be useful in emergency phases to reach good predictive performances maintaining interpretability to gain knowledge on complex situations and enhance patient management and resources.

Benchmark of Intraoperative Activity in Cardiac Surgery: A Comparison between Pre- and Post-Operative Prognostic Models.

OBJECTIVES: Despite its large diffusion and improvements in safety, the risks of complications after cardiac surgery remain high. Published predictive perioperative scores (EUROSCORE, STS, ACEF) assess risk on preoperative data only, not accounting for the intraopertive period. We propose a double-fold model, including data collected before surgery and data collected at the end of surgery, to evaluate patient risk evolution over time and assess the direct contribution of surgery. METHODS: A total of 15,882 cardiac surgery patients from a Margherita-Prosafe cohort study were included in the analysis. Probability of death was estimated using two logistic regression models (preoperative data only vs. post-operative data, also including information at discharge from the operatory theatre), testing calibration and discrimination of each model. RESULTS: Pre-operative and post-operative models were built and demonstrate good discrimination and calibration with AUC = 0.81 and 0.87, respectively. Relative difference in pre- and post-operative mortality in separate centers ranged from -0.36 (95% CI: -0.44--0.28) to 0.58 (95% CI: 0.46-0.71). The usefulness of this two-fold preoperative model to benchmark medical care in single hospital is exemplified in four cases. CONCLUSIONS: Predicted post-operative mortality differs from predicted pre-operative mortality, and the distance between the two models represent the impact of surgery on patient outcomes. A double-fold model can assess the impact of the intra-operative team and the evolution of patient risk over time, and benchmark different hospitals on patients subgroups to promote an improvement in medical care in each center.