Multidrug Resistant Bacterial Co-Infections in Critically Ill Patients with COVID-19: A Review after Three Years of Pandemic

Secondary bacterial infections and co-infections frequently affect COVID-19 patients. However, bacterial coinfection rates increase in patients admitted in the Intensive Care Units (ICUs), and those diseases can be due to superinfections by Multidrug-Resistant (MDR) bacteria. Most of these infections are related to high-risk carbapenemase-producing clones and occasionally with resistance to new β-lactam-β-lactamase inhibitor combinations. This highlights the urgency to revise frequent and empiric prescription of broad-spectrum antibiotics in COVID-19 patients, with more attention to evidence-based studies and the need to maintain antimicrobial stewardship and infection control programs in pandemic crises. Additionally, the SARS-CoV-2 pandemic highlighted the challenge that an emerging pathogen provides in adapting prevention measures regarding both the risk of exposure to caregivers and the need to maintain quality of care

Expiratory flow limitation in intensive care: prevalence and risk factors

Expiratory flow limitation (EFL) is characterised by a markedly reduced expiratory flow insensitive to the expiratory driving pressure. The presence of EFL can influence the respiratory and cardiovascular function and damage the small airways; its occurrence has been demonstrated in different diseases, such as COPD, asthma, obesity, cardiac failure, ARDS, and cystic fibrosis. Our aim was to evaluate the prevalence of EFL in patients requiring mechanical ventilation for acute respiratory failure and to determine the main clinical characteristics, the risk factors and clinical outcome associated with the presence of EFL

Inspiratory pressure waveform influences time to failure, respiratory muscle fatigue, and metabolism during resistive breathing

Abstract Increased ventilatory work beyond working capacity of the respiratory muscles can induce fatigue, resulting in limited respiratory muscle endurance (Tlim). Previous resistive breathing investigations all applied square wave inspiratory pressure as fatigue‐inducing pattern. Spontaneous breathing pressure pattern more closely approximate a triangle waveform. This study aimed at comparing Tlim, maximal inspiratory pressure (PImax), and metabolism between square and triangle wave breathing. Eight healthy subjects (Wei = 76 ± 10 kg, H = 181 ± 7.9 cm, age = 33.5 ± 4.8 years, sex [F/M] = 1/7) completed the study, comprising two randomized matched load resistive breathing trials with square and triangle wave inspiratory pressure waveform. Tlim decreased with a mean difference of 8 ± 7.2 min (p = 0.01) between square and triangle wave breathing. PImax was reduced following square wave (p = 0.04) but not for triangle wave breathing (p = 0.88). Higher VO2 was observed in the beginning and end for the triangle wave breathing compared with the square wave breathing (p = 0.036 and p = 0.048). Despite higher metabolism, Tlim was significantly longer in triangle wave breathing compared with square wave breathing, showing that the pressure waveform has an impact on the function and endurance of the respiratory muscles

Transparent decision support for mechanical ventilation using visualization of clinical preferences

BACKGROUND: Systems aiding in selecting the correct settings for mechanical ventilation should visualize patient information at an appropriate level of complexity, so as to reduce information overload and to make reasoning behind advice transparent. Metaphor graphics have been applied to this effect, but these have largely been used to display diagnostic and physiologic information, rather than the clinical decision at hand. This paper describes how the conflicting goals of mechanical ventilation can be visualized and applied in making decisions. Data from previous studies are analyzed to assess whether visual patterns exist which may be of use to the clinical decision maker. MATERIALS AND METHODS: The structure and screen visualizations of a commercial clinical decision support system (CDSS) are described, including the visualization of the conflicting goals of mechanical ventilation represented as a hexagon. Retrospective analysis is performed on 95 patients from 2 previous clinical studies applying the CDSS, to identify repeated patterns of hexagon symbols. RESULTS: Visual patterns were identified describing optimal ventilation, over and under ventilation and pressure support, and over oxygenation, with these patterns identified for both control and support modes of mechanical ventilation. Numerous clinical examples are presented for these patterns illustrating their potential interpretation at the bedside. CONCLUSIONS: Visual patterns can be identified which describe the trade-offs required in mechanical ventilation. These may have potential to reduce information overload and help in simple and rapid identification of sub-optimal settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12938-021-00974-5

Frailty trajectories in ICU survivors: A comparison between the clinical frailty scale and the Tilburg frailty Indicator and association with 1 year mortality

Purpose: To test the agreement of the Clinical Frailty Scale (CFS) and the Tilburg Frailty Indicator (TFI), their association with 3, 6 months and 1-year mortality and the trajectory of frailty in a mixed population of ICU survivors. Material and methods: This is a prospective, multicenter, longitudinal study on ICU survivors ≥18 years old with an ICU stay >72 h. For each patient, sociodemographic and clinical data were collected. Frailty was assessed during ICU stay and at 3, 6, 12 months after ICU discharge, through both CFS and TFI. Results: 124 patients with a mean age of 66 years old were enrolled. The baseline prevalence of frailty was 15.3% by CFS and 44.4% by TFI. Baseline CFS and TFI correlated but showed low agreement (Cohen's K = 0.23, p < 0.001). Baseline CFS score, but not TFI, was significantly associated to 1 year mortality. Moreover, CFS score during the follow-up was independently associated 1-year mortality (OR = 1.43; 95% CI: 1.18-1.73). Conclusions: CFS and TFI identify different populations of frail ICU survivors. Frail patients before ICU according to CFS have a significantly higher mortality after ICU discharge. The CFS during follow-up is an independent negative prognostic factor of long-term mortality in the ICU population

Lymphopaenia in cardiac arrest patients

Background: A decrease in circulating lymphocytes has been described as a marker of poor prognosis after septic shock; however, scarce data are available after cardiac arrest (CA). The aim of this study was to evaluate the impact of lymphopaenia after successful cardiopulmonary resuscitation. Methods: This is a retrospective analysis of an institutional database including all adult CA patients admitted to the intensive care unit (ICU) between January 2007 and December 2014 who survived for at least 24 h. Demographic, CA-related data and ICU mortality were recorded as was lymphocyte count on admission and for the first 48 h. A cerebral performance category score of 3â\u80\u935 at 3 months was considered as an unfavourable neurological outcome. Results: Data from 377 patients were analysed (median age: 62 [IQRs: 52â\u80\u9375] years). Median time to return of spontaneous circulation (ROSC) was 15 [8â\u80\u9325] min and 232 (62%) had a non-shockable initial rhythm. ICU mortality was 58% (n = 217) and 246 (65%) patients had an unfavourable outcome at 3 months. The median lymphocyte count on admission was 1208 [700â\u80\u932350]/mm3 and 151 (40%) patients had lymphopaenia (lymphocyte count <1000/mm3). Predictors of lymphopaenia on admission were older age, a shorter time to ROSC, prior use of corticosteroid therapy and high C-reactive protein levels on admission. ICU non-survivors had lower lymphocyte counts on admission than survivors (1100 [613â\u80\u932317] vs. 1316 [891â\u80\u932395]/mm3; p = 0.05) as did patients with unfavourable compared to those with favourable neurological outcomes (1100 [600â\u80\u932013] vs. 1350 [919â\u80\u932614]/mm3; p = 0.003). However, lymphopaenia on admission was not an independent predictor of poor outcomes in the entire population, but only among OHCA patients. Conclusions: A low lymphocyte count is common in CA survivors and is associated with poor outcome after OHCA

Diaphragm ultrasound evaluation during weaning from mechanical ventilation in COVID-19 patients: a pragmatic, cross-section, multicenter study

Background Diaphragmatic dysfunction is a major factor responsible for weaning failure in patients that underwent prolonged invasive mechanical ventilation for acute severe respiratory failure from COVID-19. This study hypothesizes that ultrasound measured diaphragmatic thickening fraction (DTF) could provide corroborating information for weaning COVID-19 patients from mechanical ventilation. Methods This was an observational, pragmatic, cross-section, multicenter study in 6 Italian intensive care units. DTF was assessed in COVID-19 patients undergoing weaning from mechanical ventilation from 1st March 2020 to 30th June 2021. Primary aim was to evaluate whether DTF is a predictive factor for weaning failure. Results Fifty-seven patients were enrolled, 25 patients failed spontaneous breathing trial (44%). Median length of invasive ventilation was 14 days (IQR 7-22). Median DTF within 24 h since the start of weaning was 28% (IQR 22-39%), RASS score (- 2 vs - 2; p = 0.031); Kelly-Matthay score (2 vs 1; p = 0.002); inspiratory oxygen fraction (0.45 vs 0.40; p = 0.033). PaO2/FiO(2) ratio was lower (176 vs 241; p = 0.032) and length of intensive care stay was longer (27 vs 16.5 days; p = 0.025) in patients who failed weaning. The generalized linear regression model did not select any variables that could predict weaning failure. DTF was correlated with pH (RR 1.56 x 10(27); p = 0.002); Kelly-Matthay score (RR 353; p &lt; 0.001); RASS (RR 2.11; p = 0.003); PaO2/FiO(2) ratio (RR 1.03; p = 0.05); SAPS2 (RR 0.71; p = 0.005); hospital and ICU length of stay (RR 1.22 and 0.79, respectively; p &lt; 0.001 and p = 0.004). Conclusions DTF in COVID-19 patients was not predictive of weaning failure from mechanical ventilation, and larger studies are needed to evaluate it in clinical practice further. Registered: ClinicalTrial.gov (NCT05019313, 24 August 2021)

Lung Recruitment Assessed by Electrical Impedance Tomography (RECRUIT):A Multicenter Study of COVID-19 Acute Respiratory Distress Syndrome

Rationale: Defining lung recruitability is needed for safe positive end-expiratory pressure (PEEP) selection in mechanically ventilated patients. However, there is no simple bedside method including both assessment of recruitability and risks of overdistension as well as personalized PEEP titration. Objectives: To describe the range of recruitability using electrical impedance tomography (EIT), effects of PEEP on recruitability, respiratory mechanics and gas exchange, and a method to select optimal EIT-based PEEP. Methods: This is the analysis of patients with coronavirus disease (COVID-19) from an ongoing multicenter prospective physiological study including patients with moderate-severe acute respiratory distress syndrome of different causes. EIT, ventilator data, hemodynamics, and arterial blood gases were obtained during PEEP titration maneuvers. EIT-based optimal PEEP was defined as the crossing point of the overdistension and collapse curves during a decremental PEEP trial. Recruitability was defined as the amount of modifiable collapse when increasing PEEP from 6 to 24 cm H2O (DCollapse24–6). Patients were classified as low, medium, or high recruiters on the basis of tertiles of DCollapse24–6. Measurements and Main Results: In 108 patients with COVID-19, recruitability varied from 0.3% to 66.9% and was unrelated to acute respiratory distress syndrome severity. Median EIT-based PEEP differed between groups: 10 versus 13.5 versus 15.5 cm H2O for low versus medium versus high recruitability (P, 0.05). This approach assigned a different PEEP level from the highest compliance approach in 81% of patients. The protocol was well tolerated; in four patients, the PEEP level did not reach 24 cm H2O because of hemodynamic instability. Conclusions: Recruitability varies widely among patients with COVID-19. EIT allows personalizing PEEP setting as a compromise between recruitability and overdistension.</p

A serum proteome signature to predict mortality in severe COVID-19 patients.

Here, we recorded serum proteome profiles of 33 severe COVID-19 patients admitted to respiratory and intensive care units because of respiratory failure. We received, for most patients, blood samples just after admission and at two more later time points. With the aim to predict treatment outcome, we focused on serum proteins different in abundance between the group of survivors and non-survivors. We observed that a small panel of about a dozen proteins were significantly different in abundance between these two groups. The four structurally and functionally related type-3 cystatins AHSG, FETUB, histidine-rich glycoprotein, and KNG1 were all more abundant in the survivors. The family of inter-α-trypsin inhibitors, ITIH1, ITIH2, ITIH3, and ITIH4, were all found to be differentially abundant in between survivors and non-survivors, whereby ITIH1 and ITIH2 were more abundant in the survivor group and ITIH3 and ITIH4 more abundant in the non-survivors. ITIH1/ITIH2 and ITIH3/ITIH4 also showed opposite trends in protein abundance during disease progression. We defined an optimal panel of nine proteins for mortality risk assessment. The prediction power of this mortality risk panel was evaluated against two recent COVID-19 serum proteomics studies on independent cohorts measured in other laboratories in different countries and observed to perform very well in predicting mortality also in these cohorts. This panel may not be unique for COVID-19 as some of the proteins in the panel have previously been annotated as mortality markers in aging and in other diseases caused by different pathogens, including bacteria