Characteristics And Outcomes of Sepsis Patients With And Without COVID-19

Background: The aim of this study was to describe and compare clinical characteristics and outcomes in critically ill septic patients with and without COVID-19.Methods: From February 2020 to March 2021, patients from surgical and medical ICUs at the University Hospital Dresden were screened for sepsis. Patient characteristics and outcomes were assessed descriptively. Patient survival was analyzed using the Kaplan-Meier estimator. Associations between in-hospital mortality and risk factors were modeled using robust Poisson regression, which facilitates derivation of adjusted relative risks.Results: In 177 ICU patients treated for sepsis, COVID-19 was diagnosed and compared to 191 septic ICU patients without COVID-19. Age and sex did not differ significantly between sepsis patients with and without COVID-19, but SOFA score at ICU admission was significantly higher in septic COVID-19 patients. In-hospital mortality was significantly higher in COVID-19 patients with 59% compared to 29% in Non-COVID patients. Statistical analysis resulted in an adjusted relative risk for in-hospital mortality of 1.74 (95%-CI=1.35-2-24) in the presence of COVID-19 compared to other septic patients. Age, procalcitonin maximum value over 2 ng/ml, need for renal replacement therapy, need for invasive ventilation and septic shock were identified as additional risk factors for in-hospital mortality.Conclusion: COVID-19 was identified as independent risk factor for higher in-hospital mortality in sepsis patients. The need for invasive ventilation and renal replacement therapy as well as the presence of septic shock and higher PCT should be considered to identify high-risk patients.

Sleep in the Intensive Care Unit through the Lens of Breathing and Heart Rate Variability: A Cross-Sectional Study

Background. Full polysomnography, the gold standard of sleep measurement, is impractical for widespread use in the intensive care unit (ICU). Wrist-worn actigraphy and subjective sleep assessments do not measure sleep physiology adequately. Here, we explore the feasibility of estimating conventional sleep indices in the ICU with heart rate variability (HRV) and respiration signals using artificial intelligence methods. Methods. We used deep learning models to stage sleep with HRV (through electrocardiogram) and respiratory effort (through a wearable belt) signals in critically ill adult patients admitted to surgical and medical ICUs, and in covariate-matched sleep laboratory patients. We analyzed the agreement of the determined sleep stages between the HRV- and breathing-based models, computed sleep indices, and quantified breathing variables during sleep. Results. We studied 102 adult patients in the ICU across multiple days and nights, and 220 patients in a clinical sleep laboratory. We found that sleep stages predicted by HRV- and breathing-based models showed agreement in 60% of the ICU data and in 81% of the sleep laboratory data. In the ICU, deep NREM (N2 + N3) proportion of total sleep duration was reduced (ICU 39%, sleep laboratory 57%, p<0.01), REM proportion showed heavy-tailed distribution, and the number of wake transitions per hour of sleep (median = 3.6) was comparable to sleep laboratory patients with sleep-disordered breathing (median = 3.9). Sleep in the ICU was also fragmented, with 38% of sleep occurring during daytime hours. Finally, patients in the ICU showed faster and less variable breathing patterns compared to sleep laboratory patients. Conclusions. Cardiovascular and respiratory signals encode sleep state information, which can be utilized to measure sleep state in the ICU. Using these easily measurable variables can provide automated information about sleep in the ICU.

Impact of ABCDE Bundle Implementation in the Intensive Care Unit on Specific Patient Costs

Objectives: To measure the impact of full versus partial ABCDE bundle implementation on specific cost centers and related resource utilization. Design: Retrospective cohort study. Setting: Two medical ICUs within Montefiore Health System (Bronx, NY). Patients: Four hundred and seventy-two mechanically ventilated patients admitted to the medical ICUs during a hospitalization which began and ended between January 1, 2013 and December 31, 2013. Interventions: The full (A)wakening, (B)reathing, (C)oordination, (D)elirium Monitoring/Management and (E)arly Mobilization bundle was implemented in the intervention ICU while a portion of the bundle (A, B, and D components) was implemented in the comparison ICU. Measurements and Main Results: Relative to the comparison ICU, implementation of the entire bundle in the intervention ICU was associated with a 27.3% (95% CI: 9.9%, 41.3%; P = 0.004) decrease in total hospital laboratory costs and a 2,888.6% (95% CI: 77.9%, 50,113.2%; P = 0.018) increase in total hospital physical therapy costs. Cost of total hospital medications, diagnostic radiology and respiratory therapy were unchanged. Relative to the comparison ICU, total hospital resource use decreased in the intervention ICU (incidence rate ratio [95% CI], laboratory: 0.68 [0.54, 0.87], P = 0.002; diagnostic radiology: 0.75 [0.59, 0.96], P = 0.020). Conclusions: Full ABCDE bundle implementation resulted in a decrease in total hospital laboratory costs and total hospital laboratory and diagnostic resource utilization while leading to an increase in physical therapy costs.

The Prevalence and the Impacts of Pulmonary Bacterial Coinfections and Secondary Bacterial Pneumonia in Patients with Severe Influenza Pneumonitis

Background: This study investigated the prevalence and clinical outcomes of pulmonary bacterial coinfections and secondary bacterial pneumonia in patients with severe influenza pneumonitis. The causative pathogens and their clinical impacts were analyzed. Methods: We retrospectively analyzed the data of adult patients with severe influenza pneumonitis admitted to our medical ICUs from January 2014 to May 2018. Bacterial confection (in first 48 h) and secondary bacterial pneumonia (from 48 h to 1 week) were confirmed by chest radiographs and positive findings in the respiratory specimen obtained from lower airway. The risk factors of pulmonary coinfection were evaluated. The outcomes of patients with or without pulmonary coninfection or secondary bacterial pneumonia were also analyzed.Results: We identified 117 critically ill patients with laboratory-confirmed influenza pneumonitis admitted to the medical ICUs. Klebsiella pneumoniae (31.4%) and Staphylococcus aureus (22.8%) were the most commonly identified bacteria in patients with bacterial coinfection. A high proportion of methicillin-resistant Staphylococcus aureus was noted. Liver cirrhosis and diabetes mellitus were the independent risk factors for bacterial coinfection. Acinetobacter baumannii (28%) and S. aureus (25%) were the most often identified bacteria in patients with secondary bacterial pneumonia. Patients with secondary bacterial pneumonia had longer period of mechanical ventilation, longer ICU stay and hospital stay, and higher mortality.Conclusions: Bacterial coinfection or secondary infection in patients with severe influenza pneumonitis were associated with higher rates of morbidity and mortality in ICU patients. Earlier diagnosis and appropriate therapy, especially in patients with liver cirrhosis and diabetes mellitus, should be cautiously considered.

Staphylococcus aureus ventilator-associated pneumonia in patients with COVID-19: clinical features and potential inference with lung dysbiosis

Background Hospitalized patients with COVID-19 admitted to the intensive care unit (ICU) and requiring mechanical ventilation are at risk of ventilator-associated bacterial infections secondary to SARS-CoV-2 infection. Our study aimed to investigate clinical features of Staphylococcus aureus ventilator-associated pneumonia (SA-VAP) and, if bronchoalveolar lavage samples were available, lung bacterial community features in ICU patients with or without COVID-19. Methods We prospectively included hospitalized patients with COVID-19 across two medical ICUs of the Fondazione Policlinico Universitario A. Gemelli IRCCS (Rome, Italy), who developed SA-VAP between 20 March 2020 and 30 October 2020 (thereafter referred to as cases). After 1:2 matching based on the simplified acute physiology score II (SAPS II) and the sequential organ failure assessment (SOFA) score, cases were compared with SA-VAP patients without COVID-19 (controls). Clinical, microbiological, and lung microbiota data were analyzed. Results We studied two groups of patients (40 COVID-19 and 80 non-COVID-19). COVID-19 patients had a higher rate of late-onset (87.5% versus 63.8%; p = 0.01), methicillin-resistant (65.0% vs 27.5%; p < 0.01) or bacteremic (47.5% vs 6.3%; p < 0.01) infections compared with non-COVID-19 patients. No statistically significant differences between the patient groups were observed in ICU mortality (p = 0.12), clinical cure (p = 0.20) and microbiological eradication (p = 0.31). On multivariable logistic regression analysis, SAPS II and initial inappropriate antimicrobial therapy were independently associated with ICU mortality. Then, lung microbiota characterization in 10 COVID-19 and 16 non-COVID-19 patients revealed that the overall microbial community composition was significantly different between the patient groups (unweighted UniFrac distance, R2 0.15349; p < 0.01). Species diversity was lower in COVID-19 than in non COVID-19 patients (94.4 ± 44.9 vs 152.5 ± 41.8; p < 0.01). Interestingly, we found that S. aureus (log2 fold change, 29.5), Streptococcus anginosus subspecies anginosus (log2 fold change, 24.9), and Olsenella (log2 fold change, 25.7) were significantly enriched in the COVID-19 group compared to the non–COVID-19 group of SA-VAP patients. Conclusions In our study population, COVID-19 seemed to significantly affect microbiological and clinical features of SA-VAP as well as to be associated with a peculiar lung microbiota composition.

Measuring Empiric Antibiotic Spectrum Patterns Across Space and Time

Background: Quantitative evaluation of antibiotic spectrum is an important, underutilized metric in measuring antibiotic use (AU) and may assist antimicrobial stewards in identifying targets and strategy for intervention. We evaluated the spectrum of initial antibiotic choices by hospital location, day of the week, and time of day to determine whether these factors may be associated with broad-spectrum antibiotic choices. Methods: We identified all admissions with antibiotic exposure in medical and surgical wards and critical care units in a tertiary academic medical center between July 1, 2014, and July 1, 2019. The antibiotic spectrum index (ASI), proposed by Gerber et al, is a numeric score based on the number of pathogens covered by a particular agent. We defined ASI for initial antibiotic choice as follows: ASI for each unique antibiotic administered within 24 hours of the first antibiotic administration was summed and assigned to the administration time of the first dose. We categorized time into 4 distinct categories: weekday days (Monday–Friday, 7 a.m.–7 p.m.), weekday nights, weekend days, and weekend nights. Weekend time began 7 p.m. Friday and ended 7 a.m. Monday. We constructed heatmaps stratified by hospital location. Mann-Whitney U tests were applied to evaluate differences in the distributions of ASI using weekday days as a reference. Results: Data included 90,455 unique antibiotic admissions with initial antibiotic starts in medical and surgical wards and critical care units. Patterns of ASI for initial antibiotic choice varied between unit locations and time (Figs. 1 and 2). Mean and median ASIs for initial antibiotic choices were higher for medical ward and medical ICUs than for surgical wards and surgical ICUs. Initial antibiotic choices had higher ASIs during overnight hours for all units except the surgical ICU. Notable differences in ASIs were identified between weekday and weekend prescribing for surgical units, whereas medical units demonstrated less extreme differences. Conclusion: We observed a “weekend effect” across hospital units; the most extreme occurred in surgical wards. This observation may be due to differences in patient volume and rounding patterns. For example, hospitalist and critical care units have 7-day schedules, whereas surgical wards are highly influenced by operating room schedules. Antimicrobial stewardship teams may use these data to identify strategies targeting the most opportune time and place to intervene on the spectrum of initial antibiotic choice.Funding: NoneDisclosures: None

Equal critical care consideration for both immunocompromised and immunocompetent patients during the COVID-19 surge

Background: SARS-CoV-2 disease (COVID) affects all sections of the community, but some people contract the disease in a form requiring ICU admission. Immunocompromised patients (ICP) figure among the fragile patients whose access to critical care may be denied in the event of ICU bed-shortage. Our aims were: 1) to describe our management experience in seeking to assure equal critical-care consideration for both ICP and immuno-competent patients during the COVID surge, 2) to assess how successful this would be in terms of outcome for all patients, 3) to compare ICU stays of ICP, whether they survived or not, so as to detect possible prognostic factors.Methods: We conducted a cohort study in medical ICUs of a university-affiliated hospital hit by an uncontrolled cluster of COVID. We compared the levels of activity before and during COVID: number of patients (whether COVID+ or COVID-, whether ICP or not); bed-occupancy and bed-availability; mortality rates and the need for sanitary evacuations analyzed to avoid triage decisions.Results: During the pre-COVID period, 396 patients, including 9.3% ICP, were admitted. During the COVID period, 547 patients, including 243 COVID+ (of whom 24 ICP), were admitted: this required an 8 ICU bed-extension (+14.5% beds), a transfer of 69 immuno-competent COVID- patients to surgical ICU step-down beds, and the transfer of 22 immuno-competent COVID patients to distant hospitals. Despite sanitary evacuations, there was a daily average of 2 ICU-access refusals, the patients being taken in charge by step-down units. Health evacuations were decided on when the weekly number of COVID admissions doubled. No ICP was denied access to the ICU; no COVID- ICP was hospitalized during the first 9 weeks of the surge. 28-day mortality was 41.6% in ICP versus 27.3% in immuno-competent patients (p=0.021, log-rank test). With the exception of SAPSII and SOFA, no factor was different between clinical and ICU-stay characteristics among ICP, whether surviving or not.Conclusion and Relevance: Equal critical-care consideration for both immuno-compromised and immunocompetent patients during the COVID-19 surge was possible with acceptable outcome. Sanitary doctrine and fine-tuned hospital logistics were mandatory both at local and national level to reach this goal.

P0637SAFETY, EFFICACY AND OUTCOMES OF SLOW LOW EFFICIENCY DIALYSIS (SLED) IN CRITICALLY ILL PATIENTS WITH ACUTE KIDNEY INJURY (AKI) IN MEDICAL INTENSIVE CARE UNITS (ICU)- A PROSPECTIVE STUDY IN A TERTIARY CARE HOSPITAL IN INDIA

Background and Aims Slow low efficiency dialysis (SLED) is increasingly being used as a renal replacement therapy in hemodynamically unstable, critically ill patients with acute kidney injury (AKI). SLED may reduce intradialytic hemodynamic instability as compared with conventional intermittent haemodialysis, while reducing resource demands of continuous renal replacement therapies (CRRT). There are very few studies which have evaluated its safety, efficacy and outcome despite its increasing use, especially in Indian subcontinent. Method We conducted a single centre, prospective study to demonstrate safety, efficacy and outcome of SLED.. Net fluid removal and duration of SLED were based on need and hemodynamic status of the individual patient as decided by treating nephrologist. SOFA score was used as severity illness score. Efficacy of SLED was studied in terms of ability to achieve ultrafiltration goal, correction of acidosis and urea reduction ratio. Safety was studied in terms of hemodynamic and cardiovascular stability and complications during and after SLED. Outcomes were noted at time of discharge and six months later in terms of dialysis dependence, renal parameters (if dialysis independent) and mortality (In hospital and 6 months following discharge). We included hemodynamically unstable patients with AKI from medical ICUs with age &gt;18 years of either gender. We excluded patients with AKI who could tolerate conventional haemodialysis or ESRD on maintenance haemodialysis. Results We analysed 228 patients with AKI in medical ICUs who underwent 576 SLED sessions over period of six months. Mean age was 57.48 ± 15.67 years and 74% (n=169) were male. Comorbidities were hypertension (56%), diabetes mellitus (43%), CKD (33%) and cardiovascular diseases (28%). Sepsis (93%) and hypoperfusion (68%) were most common causes for AKI. Refractory fluid overload (91%) and refractory metabolic acidosis (79%) were most common indications for SLED. Mean SOFA score was 12.2 ± 7.75 with 61 % patients had SOFA score more than 11. 66% were on mechanical ventilator. Out of 576 sessions, 555 sessions (96%) completed the planned duration without any adverse event. Planned ultrafiltration goal was achieved in 94%. SLED was able to correct metabolic acidosis in majority (86.1%). 68% SLED sessions required a vasopressor support and 34.8 % of SLED sessions were associated with hemodynamic instability. Total 14(6.2 %) patients died during SLED session. No documented arrhythmias developed after starting SLED. In-hospital mortality occurred in 61% patients. At 6 months follow up, another 13% patients died. In subgroup analysis, mortality was significantly higher in patients with SOFA score more than 11 (P&lt;0.0001). Ventilatory requirement was also significantly high in non-survivors(P&lt;0.0001). Univariate logistic regression analysis showed that inotropic requirement, higher SOFA severity score, acidosis with pH &lt;7.25 and presence of underlying CKD were associated with significant mortality. Conclusion Our study demonstrated efficacy and safety of SLED in critically ill AKI patients in medical ICU. SLED was able to achieve planned ultrafiltration goal and correct metabolic acidosis in majority of patients. SLED had good hemodynamic tolerability. Mortality was noted in 61 % of patients (not attributable to SLED per se). High SOFA score, underlying co morbidities, vasopressor requirement and severe acidosis (pH &lt;7.25) were associated with high mortality. SLED is a reasonable cost-effective option of RRT in hemodynamically unstable patients with AKI especially in developing countries.