Intensive Care Unit Patient Population Research Articles

Derivation and external validation of predictive models for invasive mechanical ventilation in intensive care unit patients with COVID-19

BackgroundThis study aimed to develop prognostic models for predicting the need for invasive mechanical ventilation (IMV) in intensive care unit (ICU) patients with COVID-19 and compare their performance with the Respiratory rate-OXygenation (ROX) index.MethodsA retrospective cohort study was conducted using data collected between March 2020 and August 2021 at three hospitals in Rio de Janeiro, Brazil. ICU patients aged 18 years and older with a diagnosis of COVID-19 were screened. The exclusion criteria were patients who received IMV within the first 24 h of ICU admission, pregnancy, clinical decision for minimal end-of-life care and missing primary outcome data. Clinical and laboratory variables were collected. Multiple logistic regression analysis was performed to select predictor variables. Models were based on the lowest Akaike Information Criteria (AIC) and lowest AIC with significant p values. Assessment of predictive performance was done for discrimination and calibration. Areas under the curves (AUC)s were compared using DeLong’s algorithm. Models were validated externally using an international database.ResultsOf 656 patients screened, 346 patients were included; 155 required IMV (44.8%), 191 did not (55.2%), and 207 patients were male (59.8%). According to the lowest AIC, arterial hypertension, diabetes mellitus, obesity, Sequential Organ Failure Assessment (SOFA) score, heart rate, respiratory rate, peripheral oxygen saturation (SpO2), temperature, respiratory effort signals, and leukocytes were identified as predictors of IMV at hospital admission. According to AIC with significant p values, SOFA score, SpO2, and respiratory effort signals were the best predictors of IMV; odds ratios (95% confidence interval): 1.46 (1.07–2.05), 0.81 (0.72–0.90), 9.13 (3.29–28.67), respectively. The ROX index at admission was lower in the IMV group than in the non-IMV group (7.3 [5.2–9.8] versus 9.6 [6.8–12.9], p < 0.001, respectively). In the external validation population, the area under the curve (AUC) of the ROX index was 0.683 (accuracy 63%), the AIC model showed an AUC of 0.703 (accuracy 69%), and the lowest AIC model with significant p values had an AUC of 0.725 (accuracy 79%).ConclusionsIn the development population of ICU patients with COVID-19, SOFA score, SpO2, and respiratory effort signals predicted the need for IMV better than the ROX index. In the external validation population, although the AUCs did not differ significantly, the accuracy was higher when using SOFA score, SpO2, and respiratory effort signals compared to the ROX index. This suggests that these variables may be more useful in predicting the need for IMV in ICU patients with COVID-19.ClinicalTrials.gov identifier:NCT05663528.

Artificial Intelligence-Based Models for Prediction of Mortality in ICU Patients: A Scoping Review.

Healthcare professionals may be able to anticipate more accurately a patient's timing of death and assess their possibility of recovery by implementing a real-time clinical decision support system. Using such a tool, the healthcare system can better understand a patient's condition and make more informed judgements about distributing limited resources. This scoping review aimed to analyze various death prediction AI (Artificial Intelligence) algorithms that have been used in ICU (Intensive Care Unit) patient populations. The search strategy of this study involved keyword combinations of outcome and patient setting such as mortality, survival, ICU, terminal care. These terms were used to perform database searches in MEDLINE, Embase, and PubMed up to July 2022. The variables, characteristics, and performance of the identified predictive models were summarized. The accuracy of the models was compared using their Area Under the Curve (AUC) values. Databases search yielded an initial pool of 8271 articles. A two-step screening process was then applied: first, titles and abstracts were reviewed for relevance, reducing the pool to 429 articles. Next, a full-text review was conducted, further narrowing down the selection to 400 key studies. Out of 400 studies on different tools or models for prediction of mortality in ICUs, 16 papers focused on AI-based models which were ultimately included in this study that have deployed different AI-based and machine learning models to make a prediction about negative patient outcome. The accuracy and performance of the different models varied depending on the patient populations and medical conditions. It was found that AI models compared with traditional tools like SAP3 or APACHE IV score were more accurate in death prediction, with some models achieving an AUC of up to 92.9%. The overall mortality rate ranged from 5% to more than 60% in different studies. We found that AI-based models exhibit varying performance across different patient populations. To enhance the accuracy of mortality prediction, we recommend customizing models for specific patient groups and medical contexts. By doing so, healthcare professionals may more effectively assess mortality risk and tailor treatments accordingly. Additionally, incorporating additional variables-such as genetic information-into new models can further improve their accuracy.

A stochastic model-based control methodology for glycemic management in the intensive care unit

Introduction: Intensive care unit (ICU) patients exhibit erratic blood glucose (BG) fluctuations, including hypoglycemic and hyperglycemic episodes, and require exogenous insulin delivery to keep their BG in healthy ranges. Glycemic control via glycemic management (GM) is associated with reduced mortality and morbidity in the ICU, but GM increases the cognitive load on clinicians. The availability of robust, accurate, and actionable clinical decision support (CDS) tools reduces this burden and assists in the decision-making process to improve health outcomes. Clinicians currently follow GM protocol flow charts for patient intravenous insulin delivery rate computations.Methods: We present a mechanistic model-based control algorithm that estimates the optimal intravenous insulin rate to keep BG within a target range; the goal is to develop this approach for eventual use within CDS systems. In this control framework, we employed a stochastic model representing BG dynamics in the ICU setting and used the linear quadratic Gaussian control methodology to develop a controller.Results: We designed two experiments, one using virtual (simulated) patients and one using a real-world retrospective dataset. Using these, we evaluated the safety and efficacy of this model-based glycemic control methodology. The presented controller avoids hypoglycemia and hyperglycemia in virtual patients, maintaining BG levels in the target range more consistently than two existing GM protocols. Moreover, this methodology could theoretically prevent a large proportion of hypoglycemic and hyperglycemic events recorded in a real-world retrospective dataset.Discussion: The current version of the methodology shows potential usefulness in GM of ICU patients. However, it is limited to a subgroup of the ICU patient population, who are fed through and enteral tube and delivered intravenous insulin. After extending to a broader ICU patient population who can consume oral nutrition and are delivered subcutaneous insulin for GM, the methodology could be tested with pilot studies and clinical trials for eventual use as a CDS tool.

Evaluating the Accuracy of Off-Label Placement of Pulse Oximetry Sensors in Comparison to On-Label Placement in the Adult Cardiac Intensive Care Unit Patient Population.

Continuous pulse oximetry (Spo2) is a commonly utilized tool to obtain an indirect, noninvasive measurement of hemoglobin oxygen saturation. Difficulty obtaining measurement with Spo2 sensors can lead nurses to try off-label sites until they find placement that provides a signal. Currently, there is limited evidence to support this application. The purpose of this study was to evaluate the accuracy of off-label placement of pulse oximetry sensors in comparison to on-label placement in adult cardiac intensive care patients. Data were collected on 24 participants. At the time of a medically necessary arterial blood gas laboratory draws, 4 Spo2 measurements were gathered from an on-label finger sensor, an off-label finger sensor, an on-label ear sensor, and an off-label ear sensor. Results were analyzed using 4 Pearson correlation coefficients, Bland-Altman plots, and 2 linear mixed-effect models. Our study found that while both our on-label finger and off-label finger pulse oximetry sensor overestimated when compared to the arterial hemoglobin saturation (gold standard), there was greater overestimation found with the off-label placement. Though there was not a significant difference observed between the ear probe on the nose and the gold standard, figures examining off-label ear probe and gold standard measures show that, in lower ranges of oxygen saturation, the off-site probe substantially overestimates true oxygen saturation, while in higher ranges of oxygen saturation, the off-site ear probe underestimates true oxygen saturation. No changes should be made to the current practice of using pulse oximetry sensor placement.

Factors Influencing Morbidity and Mortality Rates in Tertiary Intensive Care Units in Turkey: A Retrospective Cross-Sectional Study.

The objective of this study was to determine the correlation between the prognosis of patients admitted to a tertiary intensive care unit (ICU) and the admitted patient population, intensive care conditions, and the workload of intensive care staff. This was a retrospective cross-sectional study that analyzed data from all tertiary ICUs (a minimum of 40 and a maximum of 59 units per month) of eight training and research hospitals between January 2022 and May 2023. We compared monthly data across hospitals and analyzed factors associated with patient prognosis, including mortality and pressure injuries (PIs). This study analyzed data from 54,312 patients, of whom 51% were male and 58.8% were aged 65 or older. The median age was 69 years. The average number of tertiary ICU beds per unit was 15 ± 6 beds, and the average occupancy rate was 83.57 ± 19.28%. On average, 7 ± 9 pressure injuries (PI) and 10 ± 7 patient deaths per unit per month were reported. The mortality rate (18.66%) determined per unit was similar to the expected rate (15-25%) according to the Acute Physiology and Chronic Health Evaluation (APACHE) II score. There was a statistically significant difference among hospitals on a monthly basis across various aspects, including bed occupancy rate, length of stay (LOS), number of patients per ICU bed, number of patients per nurse in a shift, rate of patients developing PI, hospitalization rate from the emergency department, hospitalization rate from wards, hospitalization rate from the external center, referral rate, and mortality rate (p < 0.05). Although generally reliable in predicting prognosis in tertiary ICUs, the APACHE II scoring system may have limitations when analyzed on a unit-specific basis. ICU-related conditions have an impact on patient prognosis. ICU occupancy rate, work intensity, patient population, and number of working nurses are important factors associated with ICU mortality. In particular, data on the patient population admitted to the unit (emergency patients and patients with a history of malignancy) were most strongly associated with unit mortality.

Pharmacokinetics and exposure-safety relationship of ciprofol for sedation in mechanically ventilated patients in the intensive care unit.

Ciprofol (HSK3486) is a newly developed, highly selective γ-aminobutyric acid-A (GABAA) receptor potentiator that is recently approved for a new indication of sedation for patients in the intensive care unit (ICU) in China. This analysis aimed to characterize the population pharmacokinetics (PopPKs) of ciprofol and evaluate the relationship of exposure with hypotension in mechanically ventilated patients in the ICU. A total of 462 subjects with 3918 concentration measurements from two clinical trials of mechanically ventilated patients in the ICU, four clinical trials of elective surgical patients, and six clinical trials of healthy subjects were used in the PopPK analysis. Exposure-safety relationship for hypotension was evaluated based on the data gathered from 112 subjects in two clinical trials of mechanically ventilated patients in the ICU. Ciprofol pharmacokinetics (PKs) was adequately described by a three-compartment linear disposition model with first-order elimination. Body weight, age, sex, blood sampling site (vein vs. arterial), study design (long-term infusion vs. short-term infusion), and patient population (ICU vs. non-ICU) were identified as statistically significant covariates on the PKs of ciprofol. Within the exposure range of the mechanically ventilated ICU patient population, no meaningful association was observed between ciprofol exposure and the incidence of hypotension. These results support the dosing regimen currently used in mechanically ventilated patients in the ICU.

Evaluation of Anti-Methicillin-Resistant Staphylococcus aureus (MRSA) Prescribing Habits in Patients with a Positive MRSA Nasal Swab in the Absence of Positive Cultures.

Methicillin-resistant Staphylococcus aureus (MRSA) polymerase chain reaction (PCR) nasal swabs are guideline-recommended de-escalation tools in certain patients with pneumonia. Prior studies have demonstrated reduced anti-MRSA therapy with negative results, but the impact on durations of therapy has been poorly elucidated in patients with positive PCRs. The objective of this review was to evaluate anti-MRSA treatment durations in patients with a positive MRSA PCR in the absence of MRSA growth on culture. This was a single-center, retrospective observational study evaluating 52 hospitalized, adult patients receiving anti-MRSA therapy with positive MRSA PCRs. The overall median duration of anti-MRSA therapy was five days, including a median of four days after PCR results. This was consistent among intensive care unit (ICU) and non-ICU patient populations and in patients with suspected community-acquired pneumonia (CAP). Among patients with hospital-acquired pneumonia (HAP), the median duration of anti-MRSA therapy was seven days, with a median of six days after PCR results. Overall, patients received a median duration of anti-MRSA therapy that would constitute a full treatment course for many respiratory infections, which indicates that providers may equate a positive MRSA nasal PCR with positive culture growth and highlights the need for education on the interpretation of positive tests.

A NOVEL EQUATION SUCCESSFULLY CALCULATES TIDAL VOLUMES FOR LUNG PROTECTIVE VENTILATION

BackgroundEarly application of low-tidal-volume ventilation (LTVV) has been associated with improved outcomes in the emergency department (ED) and intensive care unit (ICU), but is not consistently applied. The perceived complexity of calculating an ideal body weight (IBW)-based tidal volume (Vt) may contribute to this disparity. We hypothesized that a simplified equation could successfully predict LTVV. ObjectiveTo create a memorable, single-step, sex-independent equation to estimate LTVV based on height. MethodsWe conducted a retrospective observational cohort study of patients who received mechanical ventilation (MV) at 2 EDs from January 2016 to June 2019. Data were abstracted by automatic query. Patients < 18 years old, < 60 inches in height, and with implausible or incomplete data were excluded. LTVV was defined as ≤ 8 mL/kg IBW. We created a formula predicting a 6–8-mL/kg IBW Vt. We applied this formula to a population of ICU patients in the same health care system who received MV from January 2017 to December 2019 using the same exclusion criteria. The outcome was whether the equation predicted a 6–8-mL/kg IBW Vt. ResultsA total of 982 ED patients were included; 753 (76.7%) had an initial Vt < 8 mL/kg IBW. The equation Vt = 20*(Ht-60) + 300 was derived. A total of 3720 ICU patients were included. The Vt equation successfully predicted a Vt of 6–8 mL/kg IBW in 3720 (100%) of ICU patients. ConclusionsA novel equation successfully predicted a 6–8-mL/kg IBW Vt in a cohort of patients with height ≥ 60 inches.

Algorithm-based detection of acute kidney injury according to full KDIGO criteria including urine output following cardiac surgery: a descriptive analysis

BackgroundAutomated data analysis and processing has the potential to assist, improve and guide decision making in medical practice. However, by now it has not yet been fully integrated in a clinical setting. Herein we present the first results of applying algorithm-based detection to the diagnosis of postoperative acute kidney injury (AKI) comprising patient data from a cardiac surgical intensive care unit (ICU).MethodsFirst, we generated a well-defined study population of cardiac surgical ICU patients by implementing an application programming interface (API) to extract, clean and select relevant data from the archived digital patient management system. Health records of N = 21,045 adult patients admitted to the ICU following cardiac surgery between 2012 and 2022 were analyzed. Secondly, we developed a software functionality to detect the incidence of AKI according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria, including urine output. Incidence, severity, and temporal evolution of AKI were assessed.ResultsWith the use of our automated data analyzing model the overall incidence of postoperative AKI was 65.4% (N = 13,755). Divided by stages, AKI 2 was the most frequent maximum disease stage with 30.5% of patients (stage 1 in 17.6%, stage 3 in 17.2%). We observed considerable temporal divergence between first detections and maximum AKI stages: 51% of patients developed AKI stage 2 or 3 after a previously identified lower stage. Length of ICU stay was significantly prolonged in AKI patients (8.8 vs. 6.6 days, p < 0.001) and increased for higher AKI stages up to 10.1 days on average. In terms of AKI criteria, urine output proved to be most relevant, contributing to detection in 87.3% (N = 12,004) of cases.ConclusionThe incidence of postoperative AKI following cardiac surgery is strikingly high with 65.4% when using full KDIGO-criteria including urine output. Automated data analysis demonstrated reliable early detection of AKI with progressive deterioration of renal function in the majority of patients, therefore allowing for potential earlier therapeutic intervention for preventing or lessening disease progression, reducing the length of ICU stay, and ultimately improving overall patient outcomes.Graphical

Racial and Ethnic Composition of Neonatal Nurse Practitioner Faculty and Students in the United States.

Neonatal nurse practitioners have a strong presence in the neonatal intensive care unit and are primed to lead efforts to induce change related to health disparities. Underrepresented minority nurse practitioners offer valuable perspectives in the care of underrepresented minority patients. However, there remains a current racial and ethnic discordance between neonatal providers and patients. Efforts to eliminate health disparities must begin before nursing school. The current racial and ethnic composition of neonatal nurse practitioner faculty in comparison to students in the United States is unknown. The purpose of this study was to determine the racial and ethnic composition of neonatal nurse practitioner faculty and students in the United States and contrast this data with available data for the racial and ethnic composition of the neonatal intensive care unit patient population. This cross-sectional study used a nonexperimental survey to describe the racial and ethnic composition of neonatal nurse practitioner faculty and students in the United States. There was no significant difference in the racial and ethnic composition between neonatal nurse practitioner faculty and students. There were significant differences for all race distributions between neonatal nurse practitioner students and neonatal intensive care unit admissions. The discordance between neonatal nurse practitioner students and neonates in the neonatal intensive care unit is important in addressing disparities and begins before nursing school. Identification of barriers and strategies for recruitment and retention of underrepresented minority nursing students and faculty is needed. https://journals.lww.com/advancesinneonatalcare/pages/video.aspx?v=62.

Acuity Tools for the Antepartum and Neonatal Intensive Care Units.

To evaluate content validity and interrater reliability for acuity tools developed for the antepartum and neonatal intensive care unit (NICU) patient population. Antepartum and NICU acuity tools were developed to better evaluate nurse staffing assignment equity and patient needs. Following several iterations with staff nurses and nurse leaders, content validity of the acuity tools was established via a panel of experts in each substantive area using the Content Validity Index. The final tools were then evaluated for interrater reliability using Intraclass Correlation. Content validity for the Antepartum Acuity Tool was S-CVI/Ave = 0.87 and for the NICU Acuity Tool was S-CVI/Ave = 0.98. Interrater Reliability for the Antepartum Acuity tool was ICC = 0.88, and the NICU Acuity Tool was ICC = 0.95. These tools have established content validity and interrater reliability and are appropriate for use in the antepartum and NICU settings to determine patient acuity and promote appropriate nurse-to-patient assignments.

932: A SIMPLIFIED EQUATION TO ESTIMATE TIDAL VOLUME FOR LUNG-PROTECTIVE VENTILATION

Introduction: Low tidal volume ventilation (LTVV) has been associated with improved patient-centered outcomes in the emergency department (ED) and intensive care unit (ICU). However, disparities exist in the application of LTVV. Shorter, female, and obese patients are less likely to receive appropriate tidal volumes (Vt). Misestimation of patient size, “preset” tidal volumes, and the perceived complexity of calculating an IBW-based Vt may contribute to this disparity. The current approach to calculating an IBW-based Vt may not always be practical. We hypothesized that a single-step height-based formula could successfully predict LTVV. Methods: We first conducted a retrospective observational cohort study of patients who received mechanical ventilation (MV) at 2 EDs from January 2016 to June 2019. An automatic query abstracted patient demographics, MV, and outcome data. Patients < 18 years old, < 60 inches in height (lower limit of the Devine formula), and with implausible or incomplete MV or demographic data were excluded. LTVV was defined as ≤ 8mL/kg IBW as calculated by the Divine formula. We then created a formula that predicted a 6-8 mL/kg IBW Vt. Next, we applied this formula to a population of ICU patients in the same healthcare system who received MV from January 2017 to December 2019 using the same exclusion criteria. The primary outcome was whether the proposed equation predicted a Vt of 6-8 mL/kg IBW. Results: We included a total of 982 ED patients; 753 (76.7%) had an initial Vt < 8 mL/kg IBW. Initial Vt was set at 450, 500, or 550 mL in 82.8% of patients. The following equation for VtL was derived: VtL = 20 x (Htin-60) + 300. A total of 3720 ICU patients were included; 2511 (64.9%) had an initial Vt < 8mL/kg IBW. The VtL equation successfully predicted a Vt of 6-8 mL/kg IBW in 3720 (100%) patients. Conclusions: A simplified, single-step height-based equation successfully predicted tidal volumes for LTVV in a cohort of ICU patients ≥ 60 inches independent of sex.

Pressure injury prevalence in Australian intensive care units: A secondary analysis

BackgroundPressure injuries (PIs) are an enduring problem for patients in the intensive care unit (ICU) because of their vulnerability and numerous risk factors. MethodThis study reports Australian data as a subset of data from an international 1-day point prevalence study of ICU-acquired PI in adult patients. Patients aged 18 years or older and admitted to the ICU on the study day were included. The outcome measure was the identification of a PI by direct visual skin assessment on the study day. Data collected included demographic data and clinical risk factors, PI location and stage, and PI prevention strategies used. Descriptive statistics were used to describe PI characteristics, and odds ratios (ORs) were used to identify factors associated with the development of a PI. ResultsData were collected from 288 patients from 16 Australian ICUs. ICU-acquired PI prevalence was 9.7%, with 40 PIs identified on 28 patients. Most PIs were of stage 1 and stage 2 (26/40, 65.0%). Half of the ICU-acquired PIs were found on the head and face. The odds of developing an ICU-acquired PI increased significantly with renal replacement therapy (OR: 4.25, 95% confidence interval [CI]: 1.49–12.11), impaired mobility (OR: 3.13, 95% CI: 1.08–9.12), fastest respiratory rate (OR: 1.05 [per breath per minute], 95% CI: 1.00–1.10), longer stay in the ICU (OR: 1.04 [per day], 95% CI: 1.01–1.06), and mechanical ventilation on admission (OR: 0.36, CI: 0.14–0.91). ConclusionThis study found that Australian ICU-acquired PI prevalence was 9.7% and these PIs were associated with many risk factors. Targeted PI prevention strategies should be incorporated into routine prevention approaches to reduce the burden of PIs in the Australian adult ICU patient population.

Plasma Neutrophil Gelatinase-Associated Lipocalin Is Useful for Predicting Mortality in Critically Ill Patients.

Elevated neutrophil gelatinase-associated lipocalin (NGAL) occurs in a wide range of systemic diseases. This study examined the clinical utility of plasma NGAL to predict intensive care unit (ICU) and in-hospital mortality in critically ill patients. A total of 62 patients hospitalized in a mixed ICU were included; pNGAL, creatinine, and C-reactive protein (CRP) were assayed on four consecutive days (D1-D4) following ICU admission. APACHE II score (Acute Physiology and Chronic Health Evaluation) was calculated 24 h post-admission. ICU mortality reached 35% and in-hospital mortality was 39%. The median pNGAL at admission was 142.5 (65.6–298.3) ng/mL. pNGAL was significantly higher in non-survivors compared to survivors. The highest accuracy for ICU mortality prediction was achieved at the pNGAL cutoff of 93.91 ng/mL on D4 area under the curve (AUC) = 0.89; 95%CI 0.69–0.98 and for in-hospital mortality prediction was achieved at the pNGAL cutoff of 176.64 ng/mL on D3 (AUC = 0.86; 95%CI 0.69–0.96). The APACHE II score on ICU admission predicted ICU mortality with AUC = 0.89 (95%CI 0.79–0.96) and in-hospital mortality with AUC = 0.86 (95%CI 0.75–0.94). Although pNGAL on D1 poorly correlated with APACHE II (R = 0.3; p = 0.01), the combination of APACHE II and pNGAL on D1 predicted ICU mortality with AUC = 0.90 (95%CI 0.79–0.96) and in-hospital mortality with AUC = 0.95 (95%CI 0.78–0.99). Maximal CRP during study observation failed to predict ICU mortality (AUC = 0.62; 95%CI 0.49–0.74), but helped to predict in-hospital mortality (AUC = 0.67; 95%CI 0.54–0.79). Plasma NGAL with combination with the indices of critical illness is a useful biomarker for predicting mortality in heterogeneous population of ICU patients.

Natural language processing to assess the epidemiology of delirium-suggestive behavioural disturbances in critically ill patients

Background: There is no gold standard approach for delirium diagnosis, making the assessment of its epidemiology difficult. Delirium can only be inferred though observation of behavioural disturbance and described with relevant nouns or adjectives. Objective: We aimed to use natural language processing (NLP) and its identification of words descriptive of behavioural disturbance to study the epidemiology of delirium in critically ill patients. Study design: Retrospective study using data collected from the electronic health records of a university-affiliated intensive care unit (ICU) in Melbourne, Australia. Participants: 12 375 patients Intervention: Analysis of electronic progress notes. Identification using NLP of at least one of a list of words describing behavioural disturbance within such notes. Results: We analysed 199 648 progress notes in 12 375 patients. Of these, 5108 patients (41.3%) had NLP-diagnosed behavioural disturbance (NLP-Dx-BD). Compared with those who did not have NLP-Dx-DB, these patients were older, more severely ill, and likely to have medical or unplanned admissions, neurological diagnosis, chronic kidney or liver disease and to receive mechanical ventilation and renal replacement therapy (P < 0.001). The unadjusted hospital mortality for NLP-Dx-BD patients was 14.1% versus 9.6% for patients without NLP-Dx-BD. After adjustment for baseline characteristics and illness severity, NLP-Dx-BD was not associated with increased risk of death (odds ratio [OR], 0.94; 95% CI, 0.80-1.10); a finding robust to multiple sensitivity, subgroups and time of observation subcohort analyses. In mechanically ventilated patients, NLP-Dx-BD was associated with decreased hospital mortality (OR, 0.80; 95% CI, 0.65-0.99) after adjustment for baseline severity of illness and year of admission. Conclusions: NLP enabled rapid assessment of large amounts of data identifying a population of ICU patients with typical high risk characteristics for delirium. Moreover, this technique enabled identification of previously poorly understood associations. Further investigations of this technique appear justified.

Effect of gut microbiota modulation on feeding tolerance of enterally fed critically ill adult patients: a systematic review

PurposeThe objective of this systematic review was to evaluate the effect of pre-, pro-, and synbiotics on feeding tolerance of enterally fed critically ill adult patients.MethodsMEDLINE, Science Direct, Web of Knowledge, and the Cochrane Central Register of Controlled Trials were searched up to November 2019. English language randomized controlled trials reporting the effect of pre, pro or synbiotics on the feeding tolerance of enterally fed critically ill adult patients were included.ResultsOverall, 15 papers were selected for review. Among six studies reporting the energy intake, only two studies showed significantly higher energy intake in the prebiotic-receiving groups. Among four RCTs reporting frequency or time to achieve the target calorie, only one found a significant effect of probiotics to reduce the time to achieve a target dose of calorie. About the prevalence or duration of diarrhea, 7 out of 12 RCTs reported a beneficial effect. All but one study found no beneficial effects for gut microbiota manipulation on clinical endpoints including length of stay (LOS) in hospital and intensive care unit (ICU).ConclusionIt should be noticed that the heterogeneity in study designs, product format, and ICU patient populations makes it difficult to draw any general conclusion. Overall, it seems that pre, pro, or synbiotics have no significant beneficial effect on feeding tolerance and clinical endpoints in critically ill adults, but they may reduce the prevalence or duration of diarrhea.

Continuous infusion versus intermittent administration of meropenem in critically ill patients (MERCY): A multicenter randomized double-blind trial. Rationale and design

ObjectiveMeropenem is a β-lactam, carbapenem antibacterial agent with antimicrobial activity against gram-negative, gram-positive and anaerobic micro-organisms and is important in the empirical treatment of serious infections in Intensive Care Unit (ICU) patients. Multi-drug resistant gram-negative organisms, coupled with scarcity of new antibiotic classes, forced healthcare community to optimize the therapeutic potential of available antibiotics. Our aim is to investigate the effect of continuous infusion of meropenem against bolus administration, as indicated by a composite outcome of reducing death and emergence of extensive or pan drug-resistant pathogens in a population of ICU patients. DesignDouble blind, double dummy, multicenter randomized controlled trial (1:1 allocation ratio). SettingTertiary and University hospitals. Interventions600 ICU patients with sepsis or septic shock, needing by clinical judgment antibiotic therapy with meropenem, will be randomized to receive a continuous infusion of meropenem 3 g/24 h or an equal dose divided into three daily boluses (i.e. 1g q8h). MeasurementsThe primary endpoint will be a composite outcome of reducing death and emergence of extensive or pan drug-resistant pathogens. Secondary endpoints will be death from any cause at day 90, antibiotic-free days at day 28, ICU-free days at day 28, cumulative SOFA-free (Sequential Organ Failure Assessment) score from randomization to day 28 and the two, separate, components of the primary endpoint. We expect a primary outcome reduction from 52 to 40% in the continuous infusion group. ConclusionsThe trial will provide evidence for choosing intermittent or continuous infusion of meropenem for critically ill patients with multi-drug resistant gram-negative infections.

The Efficacy of Passive Valve Antimicrobial Swab Caps Against Existing Clabsi Prevention Bundle in an Adult Hematology Inpatient Population: A Quality Improvement Initiative

Background : Central line associated blood stream infections (CLABSI) have been the costliest of all healthcare associated infections. The average CLABSI cost is approximately $46,000 (Haddadin &amp; Regunath, 2019). Most cases may be preventable with utilization of aseptic techniques, surveillance, and management through local protocols. The majority of CLABSI occur more than five days after central vascular access (CVA); therefore, there has been a growing focus on central line handling and maintenance techniques. CLABSI prevention data has been largely focused on the intensive care unit (ICU) patient population where an average of about half of patients have CVA. There have been few studies exploring the rates of CLABSI in the adult hematology population, a population with unique risk factors due to their immunosuppressing treatments and prolonged immunocompromised states. There has been emerging data that suggests the use of new technology in addition to existing central line maintenance recommendations by the Center for Disease Control may further reduce the rate of CLABSI occurrences in high-risk patient populations. Aim: To determine the efficacy of passive valve antimicrobial swab caps on the reduction of CLABSI in an inpatient hematology patient population when compared to current existing local practices. Outcomes of reported incidents of CLABSI have been evaluated against pre-interventional data for this setting. Methods : Retrospective analysis of medical records from January 2016 - September 2019 identified the existing rate of CLABSI occurrence among inpatient hematology patients at a single institution. We utilized the intervention of antimicrobial swab caps for 10 months and tracked the rate of CLABSI during this time. The nursing staff were educated on the quality improvement project, the use of the new equipment, and expectations that existing standard practices per local policy for CLABSI prevention bundles would be adhered to prior to the start of the intervention. To evaluate the impact of the antimicrobial swab caps on the rate of CLABSI we compared the number of infections pre- and post-intervention. Randomized audits, including chart reviews for compliance with existing standard CLABSI bundle practices were performed during the initial 3 months of the intervention. Results : Prior to the introduction of the passive valve antimicrobial swab cap to the existing CLABSI prevention protocol, CLABSI rates on the hematology unit exceeded the standardized infection ratio 75th percentile on 9 of the previous 15 calendar quarters. The intervention was observed for 6,674 central line days. The CLABSI rate during the intervention was 0.4495 per 1,000 central line days. The CLABSIs identified were due to nosocomial opportunistic infection in setting of immunosuppressed status (66%) and gastrointestinal translocation (33%). The common diagnosis in setting of CLABSI was refractory/relapse diffuse large B-cell lymphoma (66%) and active acute myeloid leukemia (33%). The two patients who were diagnosed with CLABSI were neutropenic with an absolute neutrophil count of 0 at time of CLABSI diagnosis. The organisms identified at time of CLABSI diagnosis were Clostridium ramosom, Enterococcus faecium, Staphylococcus epidermisis, and Candida parapsilosis. When considering the cost of a CLABSI to be about $46,000 per event and the annual cost for the inpatient hematology unit's use of the caps of approximately $19,710, the implementation of the antimicrobial swab cap reduced the cost associated with CLASBI in the hematology unit by approximately $26,290 annually. Conclusions : The introduction of the passive valve antimicrobial swab caps appears to demonstrate potential for reduced costs due to CLABSI when implemented into current CLABSI prevention bundles. This resulted in a 25% reduction in rates of CLABSI in the adult hematology patient population when compared to the previous year. The prevention of CLABSI in hematology patients with central vascular access remains challenging, however, standardized protocols for CLABSI prevention and use of antimicrobial swab caps may help further reduce the rate of CLABSI in hematology patients. Disclosures: No relevant conflicts of interest to declare. Disclosures Glennie: Pharmacyclics: Speakers Bureau; Janssen: Speakers Bureau. Bensinger:BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding, Speakers Bureau; Regeneron: Consultancy, Honoraria, Research Funding, Speakers Bureau. Patel:Celgene/BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Speakers Bureau; AstraZeneca: Consultancy, Research Funding, Speakers Bureau; BeiGene: Consultancy; Adaptive Biotechnologies: Consultancy; Genentech: Consultancy, Speakers Bureau; Kite: Consultancy; Pharmacyclics: Consultancy, Speakers Bureau.

Pharmacy Personnel’s Involvement in Transitions of Care of Intensive Care Unit Patients: A Systematic Review

Objective: Do pharmacy personnel- (ie, pharmacist or pharmacy technician) driven interventions at transitions of care into or out of the intensive care unit (ICU) improve medication safety measures compared to interventions made by other health-care team members or no intervention? Data Sources: A literature search of MEDLINE and Embase limited to English language and humans was performed (from 1969 until January 2019). Bibliographies of included investigations were reviewed for additional citations. Methods: Investigations were selected if they described a pharmacy-driven intervention at any point of transfer into or out of an ICU setting. Ten investigations were included. Five described interventions relevant to the entire ICU population, and 5 described interventions targeted to specific medications or disease. Results: A variety of interventions were utilized in the 10 included investigations. A significant improvement was demonstrated with pharmacy-driven intervention in all 4 studies that evaluated the entire ICU patient population. Interventions specific to certain medication and disease improved medication safety measures but were not always statistically significant. Medication error rates are high in patients transferred into and out of the ICU, and limited data exist to address this concern. This review compares and evaluates the current literature to guide future interventions and research in this area. Conclusions: Although pharmacy-driven interventions demonstrated some benefit in various medication safety measures in the majority of studies, additional randomized and prospective trials with patient-centered outcomes that assess morbidity and mortality are needed.

Predicting need for intensive care unit admission in adult emphysematous pyelonephritis patients at emergency departments: comparison of five scoring systems

This study assesses the performance of National Early Warning Score (NEWS), Quick Sepsis-related Organ Failure Assessment (qSOFA), Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS), and Rapid Acute Physiology Score (RAPS) in predicting emphysematous pyelonephritis (EPN) patients’ need for intensive care unit (ICU) admission. A retrospective analysis was conducted at four training and research hospitals’ emergency departments (EDs) on all EPN adult patients from January 2007 to August 2017. Data extracted were used to calculate raw scores for five physiologic scoring systems. Mann-Whitney U tests and χ2 tests were done for numerical and categorical variables respectively to examine differences between characteristics of ICU and non-ICU patient populations. Predictability of ICU admission was evaluated with AUROC analysis. ICU patients had lower GCS scores, SpO2, platelet counts, and estimated glomerular filtration rate; and higher bands, blood urea nitrogen, creatinine, and incidences of septic shock and nephrectomy. NEWS performed best, with 73.85% accuracy at optimal cut-off of 3. In this multicentre ED EPN series, we recommend using NEWS in early identification of critical EPN patients and advance planning for ICU admission. This would reduce delays in ICU transfer and ultimately improve patient outcomes.