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Recent studies have revealed high rates of burnout among respiratory therapists (RTs), which has implications for patient care and outcomes as well as for the health care workforce. We sought to better understand RT well-being during the COVID-19 pandemic. The purpose of this study was to determine rates and identify determinants of well-being, including burnout and professional fulfillment, among RTs in ICUs.We conducted a mixed-methods study comprised of a survey administered quarterly from July 2020-May 2021 to critical-care health care professionals and semi-structured interviews from April-May 2021 with 10 ICU RTs within a single health center. We performed multivariable analyses to compare RT well-being to other professional groups and to evaluate changes in well-being over time. We analyzed qualitative interview data using thematic analysis, followed by mapping themes to the Maslow needs hierarchy.One hundred eight RTs responded to at least one quarterly survey. Eighty-two (75%) experienced burnout; 39 (36%) experienced professional fulfillment, and 62 (58%) reported symptoms of depression. Compared to clinicians of other professions in multivariable analyses, RTs were significantly more likely to experience burnout (odds ratio 2.32 [95% CI 1.41-3.81]) and depression (odds ratio 2.73 [95% CI 1.65-4.51]) and less likely to experience fulfillment (odds ratio 0.51 [95% CI 0.31-0.85]). We found that staffing challenges, safety concerns, workplace conflict, and lack of work-life balance led to burnout. Patient care, use of specialized skills, appreciation and a sense of community at work, and purpose fostered professional fulfillment. Themes identified were mapped to Maslow's hierarchy of needs; met needs led to professional fulfillment, and unmet needs led to burnout.ICU RTs experienced burnout during the pandemic at rates higher than other professions. To address RT needs, institutions should design and implement strategies to reduce burnout across all levels.

In a large health system in the United States, investigators examined whether mortality, receipt of mechanical ventilation, and patient acuity changed over time among adult patients with COVID-19–related critical illness admitted to intensive care units., Visual Abstract. COVID-19–Related Critical Illness In a large health system in the United States, investigators examined whether mortality, receipt of mechanical ventilation, and patient acuity changed over time among adult patients with COVID-19–related critical illness admitted to intensive care units. Visual Abstract. COVID-19–Related Critical Illness In a large health system in the United States, investigators examined whether mortality, receipt of mechanical ventilation, and patient acuity changed over time among adult patients with COVID-19–related critical illness admitted to intensive care units., Background: The coronavirus disease 2019 (COVID-19) pandemic continues to surge in the United States and globally. Objective: To describe the epidemiology of COVID-19–related critical illness, including trends in outcomes and care delivery. Design: Single–health system, multihospital retrospective cohort study. Setting: 5 hospitals within the University of Pennsylvania Health System. Patients: Adults with COVID-19–related critical illness who were admitted to an intensive care unit (ICU) with acute respiratory failure or shock during the initial surge of the pandemic. Measurements: The primary exposure for outcomes and care delivery trend analyses was longitudinal time during the pandemic. The primary outcome was all-cause 28-day in-hospital mortality. Secondary outcomes were all-cause death at any time, receipt of mechanical ventilation (MV), and readmissions. Results: Among 468 patients with COVID-19–related critical illness, 319 (68.2%) were treated with MV and 121 (25.9%) with vasopressors. Outcomes were notable for an all-cause 28-day in-hospital mortality rate of 29.9%, a median ICU stay of 8 days (interquartile range [IQR], 3 to 17 days), a median hospital stay of 13 days (IQR, 7 to 25 days), and an all-cause 30-day readmission rate (among nonhospice survivors) of 10.8%. Mortality decreased over time, from 43.5% (95% CI, 31.3% to 53.8%) to 19.2% (CI, 11.6% to 26.7%) between the first and last 15-day periods in the core adjusted model, whereas patient acuity and other factors did not change. Limitation: Single–health system study; use of, or highly dynamic trends in, other clinical interventions were not evaluated, nor were complications. Conclusion: Among patients with COVID-19–related critical illness admitted to ICUs of a learning health system in the United States, mortality seemed to decrease over time despite stable patient characteristics. Further studies are necessary to confirm this result and to investigate causal mechanisms. Primary Funding Source: Agency for Healthcare Research and Quality.

Pulse oximetry is the mainstay of patient oxygen monitoring. Measurement error from pulse oximetry is more common for those with darker skin pigmentation, yet this topic remains understudied, and evidence-based clinical mitigation strategies do not currently exist. Our objectives were to measure the rate of occult hypoxemia, defined as arterial oxygen saturation (SWe performed a multi-center retrospective cohort study of critically ill subjects.Among 105,467 paired observations from 7,693 subjects, we found occult hypoxemia was more common among minority subjects. The frequency of occult hypoxemia was 7.9% versus 2.9% between Black and white subjects, respectively, (Measurement error in pulse oximetry is common for all racial groups, but occult hypoxemia occurred most commonly in Black subjects. The highly variable magnitude and direction of measurement error preclude an individualized mitigation approach. In advance of technological advancements, we recommend targeting a pulse oximetry saturation goal of 94-98% for all patients.

Neuromuscular blockade (NMB) with cisatracurium may improve outcomes in the acute respiratory distress syndrome (ARDS) population; however, optimal dosing strategy remains unknown. Factors affecting pharmacokinetics and pharmacodynamics of cisatracurium may impact the dose required to achieve adequate train-of-four (TOF) response. The aims of this study were to determine cisatracurium dose requirements in a critically ill ARDS population and to identify clinical factors that affect dosing. This was a single-center, retrospective cohort study of medical intensive care patients who received cisatracurium infusion for treatment of ARDS. “Stable dose” was defined as the infusion rate producing 2 consecutive TOFs of 1/4 to 2/4. Factors examined for association with dose were temperature, pH, age, and the presence of acute kidney injury (AKI). The analysis included 39 patients. The median stable dose of cisatracurium was 2.8 (2.0, 3.1) μg/kg/min. Multivariable linear regression model for weight-normalized dose identified AKI as a factor independently associated with steady-state dose requirements (% change −31.4, 95% confidence interval [CI]: −51.9, −2.3). Our study provides information on cisatracurium doses required in patients with ARDS to reduce time required to reach goal TOF. Further studies are needed to determine effect of AKI on cisatracurium dose requirements and clinical outcomes.

OBJECTIVE: Assess clinician perceptions of a machine learning-based early warning system to predict severe sepsis and septic shock (EWS 2.0) DESIGN: Prospective observational study SETTING: Tertiary teaching hospital in Philadelphia, PA PATIENTS: Non-ICU admissions November-December 2016 INTERVENTIONS: During a six-week study period conducted five months after EWS 2.0 alert implementation, nurses and providers were surveyed twice about their perceptions of the alert’s helpfulness and impact on care, first within 6 hours of the alert, and again 48 hours post-alert. MEASUREMENTS AND MAIN RESULTS: For the 362 alerts triggered, 180 nurses (50% response rate) and 107 providers (30% response rate) completed the First Survey. Of these, 43 nurses (24% response rate) and 44 providers (41% response rate) completed a Second Survey. Few (24% nurses, 13% providers) identified new clinical findings after responding to the alert. Perceptions of the presence of sepsis at the time of alert were discrepant between nurses (13%) and providers (40%). The majority of clinicians reported no change in perception of the patient’s risk for sepsis (55% nurses, 62% providers). A third of nurses (30%) but few providers (9%) reported the alert changed management. Almost half of nurses (42%) but less than a fifth of providers (16%) found the alert helpful at 6 hours. CONCLUSIONS: In general, clinical perceptions of EWS 2.0 were poor. Nurses and providers differed in their perceptions of sepsis and alert benefits. These findings highlight the challenges of achieving acceptance of predictive and machine learning-based sepsis alerts.

Objectives:Develop and implement a machine learning algorithm to predict severe sepsis and septic shock and evaluate the impact on clinical practice and patient outcomes.Design:Retrospective cohort for algorithm derivation and validation, pre-post impact evaluation.Setting:Tertiary teaching hospital

BACKGROUND: Staffing strategies used to meet the needs of respiratory care departments during the COVID-19 pandemic included the deployment of respiratory therapist extenders. The purpose of this study was to evaluate respiratory therapist extenders’ comfort level with critical care ventilators while caring for patients with COVID-19. To our knowledge, this is the first study to evaluate the deployment of certified registered nurse anesthetists (CRNAs) in a critical care setting. METHODS: A qualitative survey method was used to assess CRNA experience with critical care ventilators. Prior to deployment in the ICU, CRNAs were trained by clinical lead respiratory therapists. Education included respiratory clinical practices and ventilator management. Sixty-minute sessions were held with demonstration stations set up in ICUs for hands-on experience. RESULTS: Fifty-six CRNAs responded to our survey (63%). A mean ± SD of 9.48 ± 12.27 h was spent training prior to deployment in the ICU. CRNAs were at the bedside a mean ± SD of 73.0 ± 40.6 h during the pandemic. While CRNA comfort level with critical care ventilators increased significantly (P < .001) from the beginning to the end of their work experience, no statistically significant differences were found between CRNA comfort based on years of experience. Differences in comfort level were not found after training (chi-squared test 23.82, P = .09) or after ICU experience was completed (chi-squared test = 15.99, P = .45). Similarly, mean comfort level did not increase based on the number of hours spent working in the ICU (chi-squared test = 13.67, P = .55). CONCLUSIONS: Comfort level with mechanical ventilation increased for CRNAs working alongside respiratory therapists during the COVID-19 pandemic.

Due to the global shortage of PPE caused by increasing number of COVID-19 patients in recent months, many hospitals have had difficulty procuring adequate PPE for the clinicians who care for these patients. Faced with a shortage, hospitals have had to implement new PPE conservation policies. In this paper, we describe a tool to help hospitals better project PPE needs under various conservation policies. Though this tool is built on top of projections of the number of hospitalized COVID-19 patients, it is agnostic as to which model—of which many are available—provides these projections. The tool combines COVID-19 patient census projections with information like staffing ratios and frequency of patient contact to provide projections of the number of items of key types of PPE needed under three built-in conservation scenarios: standard, contingency, and crisis. Users are also able to customize the tool to the specifics of their hospital and design custom conservation policies.

Objectives Sepsis is associated with high early and total in-hospital mortality. Despite recent revisions in the diagnostic criteria for sepsis that sought to improve predictive validity for mortality, it remains difficult to identify patients at greatest risk of death. We compared the utility of nine biomarkers to predict mortality in subjects with clinically suspected bacterial sepsis. Design Cohort study. Setting The medical and surgical ICUs at an academic medical center. Subjects We enrolled 139 subjects who met two or more systemic inflammatory response syndrome (systemic inflammatory response syndrome) criteria and received new broad-spectrum antibacterial therapy. Interventions We assayed nine biomarkers (α-2 macroglobulin, C-reactive protein, ferritin, fibrinogen, haptoglobin, procalcitonin, serum amyloid A, serum amyloid P, and tissue plasminogen activator) at onset of suspected sepsis and 24, 48, and 72 hours thereafter. We compared biomarkers between groups based on both 14-day and total in-hospital mortality and evaluated the predictive validity of single and paired biomarkers via area under the receiver operating characteristic curve. Measurements and main results Fourteen-day mortality was 12.9%, and total in-hospital mortality was 29.5%. Serum amyloid P was significantly lower (4/4 timepoints) and tissue plasminogen activator significantly higher (3/4 timepoints) in the 14-day mortality group, and the same pattern held for total in-hospital mortality (Wilcoxon p ≤ 0.046 for all timepoints). Serum amyloid P and tissue plasminogen activator demonstrated the best individual predictive performance for mortality, and combinations of biomarkers including serum amyloid P and tissue plasminogen activator achieved greater predictive performance (area under the receiver operating characteristic curve > 0.76 for 14-d and 0.74 for total mortality). Conclusions Combined biomarkers predict risk for 14-day and total mortality among subjects with suspected sepsis. Serum amyloid P and tissue plasminogen activator demonstrated the best discriminatory ability in this cohort.

Background: Acid-base disturbances are frequent in critically ill patients. Arterial blood gas (ABG) is the gold standard in the diagnosis of these disturbances, but it is invasive with potential hazards. For patients with a central venous catheter, venous blood gas (VBG) sampling may be an alternative, less-invasive diagnostic tool. However, the accuracy of a central VBG-based acid-base disorder diagnosis compared to an ABG is unknown. The primary objective of this study was to assess the accuracy of a central VBG-based acid-base disorder diagnosis compared to the “gold standard” ABG in critically ill patients. Methods: This was a study of adult patients in a medical intensive care unit that had simultaneously drawn ABG and central VBG samples. Expert acid-base diagnosticians, all nephrologists, diagnosed the acid-base disorder(s) in each blood gas sample. The central VBG diagnostic accuracy was assessed with percent agreement, sensitivity, and specificity compared to the ABG-based diagnosis. Results: The study involved 23 participants. Overall, the central VBG had 100% sensitivity for metabolic acidosis, metabolic alkalosis, and respiratory acidosis, and lower sensitivity (71%) for respiratory alkalosis, and high percent agreement, ranging from 75 to 94%. VBG-based diagnoses in vasopressor-dependent patients (n = 13, 56.5%) performed similarly to the entire sample. Conclusions: In critically ill adult patients, central VBG may be used to detect and diagnose acid-base disturbances with reasonable diagnostic accuracy, even in shock states, compared to the ABG. This study supports the use of central VBG for diagnosis of acid-base disturbances in critically ill patients.

OBJECTIVES:. Prior studies have demonstrated suboptimal adherence to lung protective ventilation among patients with acute respiratory distress syndrome. A common barrier to providing this evidence-based practice is diagnostic uncertainty. We sought to test the hypothesis that patients with acute respiratory distress syndrome due to coronavirus disease 2019, in whom acute respiratory distress syndrome is easily recognized, would be more likely to receive low tidal volume ventilation than concurrently admitted acute respiratory distress syndrome patients without coronavirus disease 2019. DESIGN:. Retrospective cohort study. SETTING:. Five hospitals of a single health system. PATIENTS:. Mechanically ventilated patients with coronavirus disease 2019 or noncoronavirus disease 2019 acute respiratory distress syndrome as identified by an automated, electronic acute respiratory distress syndrome finder in clinical use at study hospitals. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. Among 333 coronavirus disease 2019 patients and 234 noncoronavirus disease 2019 acute respiratory distress syndrome patients, the average initial tidal volume was 6.4 cc/kg predicted body weight and 6.8 cc/kg predicted body weight, respectively. Patients had tidal volumes less than or equal to 6.5 cc/kg predicted body weight for a mean of 70% of the first 72 hours of mechanical ventilation in the coronavirus disease 2019 cohort, compared with 52% in the noncoronavirus disease 2019 cohort (unadjusted p < 0.001). After adjusting for height, gender, admitting hospital, and whether or not the patient was admitted to a medical specialty ICU, coronavirus disease 2019 diagnosis was associated with a 21% higher percentage of time receiving tidal volumes less than or equal to 6.5 cc/kg predicted body weight within the first 72 hours of mechanical ventilation (95% CI, 14–28%; p < 0.001). CONCLUSIONS:. Adherence to low tidal volume ventilation during the first 72 hours of mechanical ventilation is higher in patients with coronavirus disease 2019 than with acute respiratory distress syndrome without coronavirus disease 2019. This population may present an opportunity to understand facilitators of implementation of this life-saving evidence-based practice.

Hospital readmission is common after sepsis, yet the relationship between the index admission and readmission remains poorly understood. We sought to examine the relationship between infection during the index acute care hospitalization and readmission and to identify potentially modifiable factors during the index sepsis hospitalization associated with readmission.In a retrospective cohort study, we evaluated 444 sepsis survivors at risk of an unplanned hospital readmission in 2012. The primary outcome was 30-day unplanned hospital readmission.Three hospitals within an academic healthcare system.Four hundred forty-four sepsis survivors.Of 444 sepsis survivors, 23.4% (95% CI, 19.6-27.6%) experienced an unplanned 30-day readmission compared with 10.1% (95% CI, 9.6-10.7%) among 11,364 nonsepsis survivors over the same time period. The most common cause for readmission after sepsis was infection (69.2%, 72 of 104). Among infection-related readmissions, 51.4% were categorized as recurrent/unresolved. Patients with sepsis present on their index admission who also developed a hospital-acquired infection ("second hit") were nearly twice as likely to have an unplanned 30-day readmission compared with those who presented with sepsis at admission and did not develop a hospital-acquired infection or those who presented without infection and then developed hospital-acquired sepsis (38.6% vs 22.2% vs 20.0%, p = 0.04). Infection-related hospital readmissions, specifically, were more likely in patients with a "second hit" and patients receiving a longer duration of antibiotics. The use of total parenteral nutrition (p = 0.03), longer duration of antibiotics (p = 0.047), prior hospitalizations, and lower discharge hemoglobin (p = 0.04) were independently associated with hospital readmission.We confirmed that the majority of unplanned hospital readmissions after sepsis are due to an infection. We found that patients with sepsis at admission who developed a hospital-acquired infection, and those who received a longer duration of antibiotics, appear to be high-risk groups for unplanned, all-cause 30-day readmissions and infection-related 30-day readmissions.

BACKGROUND: Delayed mechanical ventilation monitoring may impede recognition of life-threatening acidemia. Coordination of multidisciplinary processes can be improved by using a checklist and time-out procedure. The study objective was to evaluate process-related outcomes after implementation of a post-intubation checklist and time out. METHODS: An observational study of a 24-bed medical ICU in Philadelphia, Pennsylvania, was conducted from January to December 2011. A random sample of mechanically ventilated adults was selected from the pre-intervention ( n = 80) and post-intervention ( n = 144) periods. The primary outcome was the proportion of subjects with an arterial blood gas (ABG) result within 60 min of mechanical ventilation initiation. Secondary outcomes included rates of respiratory acidosis, moderate-severe acidemia (pH

Sepsis remains a diagnostic challenge in the intensive care unit (ICU), and the use of biomarkers may help in differentiating bacterial sepsis from other causes of systemic inflammatory syndrome (SIRS). The goal of this study was to assess test characteristics of a number of biomarkers for identifying ICU patients with a very low likelihood of bacterial sepsis. A prospective cohort study was conducted in a medical ICU of a university hospital. Immunocompetent patients with presumed bacterial sepsis were consecutively enrolled from January 2012 to May 2013. Concentrations of nine biomarkers (α-2 macroglobulin, C-reactive protein [CRP], ferritin, fibrinogen, haptoglobin, procalcitonin [PCT], serum amyloid A, serum amyloid P, and tissue plasminogen activator) were determined at baseline and at 24 h, 48 h, and 72 h after enrollment. Performance characteristics were calculated for various combinations of biomarkers for discrimination of bacterial sepsis from other causes of SIRS. Seventy patients were included during the study period; 31 (44%) had bacterial sepsis, and 39 (56%) had other causes of SIRS. PCT and CRP values were significantly higher at all measured time points in patients with bacterial sepsis. A number of combinations of PCT and CRP, using various cutoff values and measurement time points, demonstrated high negative predictive values (81.1% to 85.7%) and specificities (63.2% to 79.5%) for diagnosing bacterial sepsis. Combinations of PCT and CRP demonstrated a high ability to discriminate bacterial sepsis from other causes of SIRS in medical ICU patients. Future studies should focus on the use of these algorithms to improve antibiotic use in the ICU setting.

We implemented an electronic early warning and response system (EWRS) to improve detection of and response to severe sepsis. Sustainability of such a system requires stakeholder acceptance. We hypothesized that clinicians receiving such alerts perceive them to be useful and effective.To survey clinicians after EWRS notification about perceptions of the system.For a 6-week study period 1 month after EWRS implementation in a large tertiary referral medical center, bedside clinicians, including providers (physicians, advanced practice providers) and registered nurses (RNs), were surveyed confidentially within 2 hours of an alert.For the 247 alerts that triggered, 127 providers (51%) and 105 RNs (43%) completed the survey. Clinicians perceived most patients as stable before and after the alert. Approximately half (39% providers, 48% RNs) felt the alert provided new information, and about half (44% providers, 56% RNs) reported changes in management as a result of the alert, including closer monitoring and additional interventions. Over half (54% providers, 65% RNs) felt the alert was appropriately timed. Approximately one-third found the alert helpful (33% providers, 40% RNs) and fewer felt it improved patient care (24% providers, 35% RNs).A minority of responders perceived the EWRS to be useful, likely related to the perception that most patients identified were stable. However, management was altered half the time after an alert. These results suggest further improvements to the system are needed to enhance clinician perception of the system's utility.

Rationale: The epidemiology of post–acute care use and hospital readmission after sepsis remains largely unknown.Objectives: To examine the rate of post–acute care use and hospital readmission after sepsis and to examine risk factors and outcomes for hospital readmissions after sepsis.Methods: In an observational cohort study conducted in an academic health care system (2010–2012), we compared post–acute care use at discharge and hospital readmission after 3,620 sepsis hospitalizations with 108,958 nonsepsis hospitalizations. We used three validated, claims-based approaches to identify sepsis and severe sepsis.Measurements and Main Results: Post–acute care use at discharge was more likely after sepsis, driven by skilled care facility placement (35.4% after sepsis vs. 15.8%; P

Septic shock is associated with increased long-term morbidity and mortality. However, little is known about the use of hospital-based acute care in survivors after hospital discharge. The objectives of the study were to examine the frequency, timing, causes, and risk factors associated with emergency department visits and hospital readmissions within 30 days of discharge.Retrospective cohort study.Tertiary, academic hospital in the United States.Patients admitted with septic shock (serum lactate≥4 mmol/L or refractory hypotension) and discharged alive to a nonhospice setting between 2007 and 2010.None.The coprimary outcomes were all-cause hospital readmission and emergency department visits (treat-and-release encounters) within 30 days to any of the three health system hospitals. Of 269 at-risk survivors, 63 (23.4%; 95% CI, 18.2-28.5) were readmitted within 30 days of discharge and another 12 (4.5%; 95% CI, 2.3-7.7) returned to the emergency department for a treat-and-release visit. Readmissions occurred within 15 days of discharge in 75% of cases and were more likely in oncology patients (p=0.001) and patients with a longer hospital length of stay (p=0.04). Readmissions were frequently due to another life-threatening condition and resulted in death or discharge to hospice in 16% of cases. The reasons for readmission were deemed potentially related to the index septic shock hospitalization in 78% (49 of 63) of cases. The most common cause was infection related, accounting for 46% of all 30-day readmissions, followed by cardiovascular or thromboembolic events (18%).The use of hospital-based acute care appeared to be common in septic shock survivors. Encounters often led to readmission within 15 days of discharge, were frequently due to another acute condition, and appeared to result in substantial morbidity and mortality. Given the potential public health implications of these findings, validation studies are needed.

Supplemental Digital Content is available in the text., Objectives: Sedation minimization and ventilator liberation protocols improve outcomes but are challenging to implement. We sought to demonstrate proof-of-concept and impact of an electronic application promoting sedation minimization and ventilator liberation. Design: Multi-ICU proof-of-concept study and a single ICU before-after study. Setting: University hospital ICUs. Patients: Adult patients receiving mechanical ventilation. Interventions: An automated application consisting of 1) a web-based dashboard with real-time data on spontaneous breathing trial readiness, sedation depth, sedative infusions, and nudges to wean sedation and ventilatory support and 2) text-message alerts once patients met criteria for a spontaneous breathing trial and spontaneous awakening trial. Pre-intervention, sedation minimization, and ventilator liberation were reviewed daily during a multidisciplinary huddle. Post-intervention, the dashboard was used during the multidisciplinary huddle, throughout the day by respiratory therapists, and text alerts were sent to bedside providers. Measurements and Main Results: We enrolled 115 subjects in the proof-of-concept study. Spontaneous breathing trial alerts were accurate (98.3%), usually sent while patients were receiving mandatory ventilation (88.5%), and 61.9% of patients received concurrent spontaneous awakening trial alerts. We enrolled 457 subjects in the before-after study, 221 pre-intervention and 236 post-intervention. After implementation, patients were 28% more likely to be extubated (hazard ratio, 1.28; 95% CI, 1.01–1.63; p = 0.042) and 31% more likely to be discharged from the ICU (hazard ratio, 1.31; 95% CI, 1.03–1.67; p = 0.027) at any time point. After implementation, the median duration of mechanical ventilation was 2.20 days (95% CI, 0.09–4.31 d; p = 0.042) shorter and the median ICU length of stay was 2.65 days (95% CI, 0.13–5.16 d; p = 0.040) shorter, compared with the expected durations without the application. Conclusions: Implementation of an electronic dashboard and alert system promoting sedation minimization and ventilator liberation was associated with reductions in the duration of mechanical ventilation and ICU length of stay.

BACKGROUND A multidisciplinary team, including critical care nurses?and specialists, critical care intensivist physicians and infection?preventionists developed and implemented a new care leadership model to direct the assessment of central venous catheters?and central line bloodstream infection (CLABSI) risk in a medical intensive care unit (MICU) within an academic quaternary care hospital. METHODS The MICU unit based clinical leadership (UBCL) introduced weekly multidisciplinary central line rounding that incorportated assessments at the bedside from physicians, nurses, advanced practice providers and infection preventionists. Each discipline assessed each patient's central access from his or her professional perspective. This new practice widened the scope of assessments to include proper insertion practices, choice of line location and discussions about line removal. Additionally, this allowed a forum for direct feedback and discussion at the bedside and provided an opportunity for caregivers to learn from these experts. Technology supported the function of this team by introducing the use of mobile devices and?sophisticated research software providing a communication and?auditing arena. REDCap was implemented to structure the information efficiently. This allowed data to be securely accessed and completed at the bedside using a mobile phone or IPad. The team also used photographs to track their progress. “Before” and “after” photos of problematic lines visually depicted their success, and also provided education to staff in the unit newsletter, Central Line Rewind. RESULTS The MICU compared its CLABSI performance over a five month period in 2017 to 2018 (7/1 to 11/30). In 2017, the MICU incurred six (6) CLABSIs. In 2018, it incurred three (3). CONCLUSIONS The MICU reduced the number of CLABSIs by 50%. A consistent, comprehensive, interdisciplinary approach to assessing the central lines has allowed the MICU to more effectively assess the central lines. In addition, implementing a technological solution has enabled real-time peer review, including results from effective interventions.

SummaryPulmonary embolism (PE) is a major cause of morbidity and mortality world-wide, and the use of thrombolytic therapy has been associated with favourable clinical outcomes in certain patient subsets. These potential benefits are counterbalanced by the risk of bleeding complications, the most devastating of which is intracranial haemorrhage (ICH). We retrospectively evaluated 9703 patients from the 2003–2012 nationwide in-patient sample database (NIS) who received thrombolytics for PE. All patients with ICH during the PE hospitalisation were identified and a clinical risk score model was developed utilizing demographics and comorbidities. The dataset was divided 1:1 into derivation and validation cohorts. During 2003–2012, 176/9705 (1.8 %) patients with PE experienced ICH after thrombolytic use. Four independent prognostic factors were identified in a backward logistic regression model, and each was assigned a number of points proportional to its regression coefficient: pre-existing Peripheral vascular disease (1 point), age greater than 65 years (Elderly) (1 point), prior Cerebrovascular accident with residual deficit (5 points), and prior myocardial infarction (Heart attack) (1 point). In the derivation cohort, scores of 0, 1, 2 and ≥ 5 points were associated with ICH risks of 1.2 %, 1.9 %, 2.4 % and 17.8 %, respectively. Rates of ICH were similar in the validation cohort. The C-statistic for the risk score was 0.65 (0.61–0.70) in the derivation cohort and 0.66 (0.60–0.72) in the validation cohort. A novel risk score, derived from simple clinical historical elements was developed to predict ICH in PE patients treated with thrombolytics.Supplementary Material to this article is available online at www.thrombosis-online.com.

Transitions to outpatient care are crucial after critical illness, but the documentation practices in discharge documents after critical illness are unknown.To characterize the rates of documentation of various features of critical illness in discharge documents of patients diagnosed with acute respiratory distress syndrome (ARDS) during their hospital stay.We used natural language processing tools to build a keyword-based classifier that categorizes discharge documents by presence of terms from four groups of keywords related to critical illness. We used a multivariable modified Poisson regression model to infer patient- and hospital-level characteristics associated with documentation of relevant keywords. A manual chart review was used to validate the accuracy of the keyword-based classifier, and to assess for ARDS documentation during the hospital stay.Of 815 discharge documents, ARDS was identified in only 111 (13%). Mechanical ventilation was identified in 770 (92%) and intensive care unit (ICU) admission in 693 (83%) of discharge documents. Symptoms or recommendations related to post-intensive care syndrome were included in 306 (38%) of discharge documents. Patient age (older; relative risk [RR] = 0.97/yr, 95% confidence interval [CI] = 0.96-0.98) and higher PaO2:FiO2 (decreasing illness severity; RR = 0.96/10-unit increment, 95% CI = 0.93-0.98) were associated with decreased documentation of ARDS. Being discharged from a surgical (RR = 0.33, 95% CI = 0.22-0.50) compared with a medicine service was also associated with decreased rates of ARDS documentation. The manual chart review revealed 98% concordance between ARDS documentation in the discharge summary and during the hospital stay. Accuracy of the document classifier was 100% for ARDS and mechanical ventilation, 98% for ICU admission, and 95% for symptoms of post-intensive care syndrome.In the discharge documents of survivors of ARDS, ARDS itself is rarely mentioned, but mechanical ventilation and ICU stay frequently are. The low rates of documentation of ARDS appear to be concordant with low rates of documentation during the hospital stay, consistent with known underrecognition in the ICU. Natural language processing tools can be used to effectively analyze large numbers of discharge documents of patients with critical illness.

Background Lower respiratory tract infection (LRTI) is a major contributor to respiratory failure requiring intubation and mechanical ventilation. LRTI also occurs during mechanical ventilation, increasing the morbidity and mortality of intubated patients. We sought to understand the dynamics of respiratory tract microbiota following intubation and the relationship between microbial community structure and infection. Results We enrolled a cohort of 15 subjects with respiratory failure requiring intubation and mechanical ventilation from the medical intensive care unit at an academic medical center. Oropharyngeal (OP) and deep endotracheal (ET) secretions were sampled within 24 h of intubation and every 48–72 h thereafter. Bacterial community profiling was carried out by purifying DNA, PCR amplification of 16S ribosomal RNA (rRNA) gene sequences, deep sequencing, and bioinformatic community analysis. We compared enrolled subjects to a cohort of healthy subjects who had lower respiratory tract sampling by bronchoscopy. In contrast to the diverse upper respiratory tract and lower respiratory tract microbiota found in healthy controls, critically ill subjects had lower initial diversity at both sites. Diversity further diminished over time on the ventilator. In several subjects, the bacterial community was dominated by a single taxon over multiple time points. The clinical diagnosis of LRTI ascertained by chart review correlated with low community diversity and dominance of a single taxon. Dominant taxa matched clinical bacterial cultures where cultures were obtained and positive. In several cases, dominant taxa included bacteria not detected by culture, including Ureaplasma parvum and Enterococcus faecalis. Conclusions Longitudinal analysis of respiratory tract microbiota in critically ill patients provides insight into the pathogenesis and diagnosis of LRTI. 16S rRNA gene sequencing of endotracheal aspirate samples holds promise for expanded pathogen identification. Electronic supplementary material The online version of this article (doi:10.1186/s40168-016-0151-8) contains supplementary material, which is available to authorized users.

Title: Can a Computerized Sepsis Screening and Alert System Accurately Diagnose Sepsis in Hospitalized Floor Patients and Potentially Provide Opportunities for Early Intervention? A Pilot Study. Background: Sepsis Syndromes are major causes of morbidity and mortality for hospitalized patients. Several evidence-based interventions have been shown to improve outcomes but they must be instituted early to achieve better outcomes. However, early recognition of sepsis syndromes in hospitalized patients is challenging. Regrettably, SIRS is overly sensitive and not specific in the patient populations at greatest risk for developing sepsis. In addition, many hospitalized patients have baseline end-organ dysfunction, wherein subtle trends in laboratory abnormalities may escape detection. Electronic detection and alert systems offer a more focused and efficient methodology. This strategy has been deployed successfully in other aspects of critical care, e.g. in the early recognition of acute respiratory distress syndrome. We developed an electronic recognition and alert system to identify floor patients with sepsis syndromes. The objective of this study was to test the feasibility, accuracy, and potential value of a computerized sepsis screening and alert system in a large university hospital. Methods and findings: The sepsis alert used an abnormal white blood cell count coupled with a blood culture order to define sepsis. Cases were categorized as severe sepsis by meeting specified changes in laboratory tests for organ dysfunction in accordance with consensus conference criteria. Using a retrospective cohort study design, we evaluated 97 consecutive, non-intensive care unit patients who triggered a sepsis alert at a large, urban, academic medical center. The charts of the patients were reviewed and abstracted manually to determine whether sepsis was present. For confirmed sepsis cases, we determined adherence with sepsis care bundle measures, including the recognition of sepsis (using physician documentation as a proxy measure), measurement of serum lactate, administration of antibiotics, and intravenous fluid resuscitation for severe sepsis cases. Within the 97 patient cohort, 72 were confirmed to have sepsis or severe sepsis (positive predictive value of 74%). Sepsis or severe sepsis was not documented in 79%, serum lactate was not measured in 57%, antibiotics were not administered in 14% of patients with severe sepsis, and fluid boluses were not administered in 17% of patients with severe sepsis who had lactic acidosis, hypotension, and/or acute kidney injury. In patients with sepsis or severe sepsis, adherence to the complete sepsis bundle did not occur in 65%. Opportunities to improve sepsis care were more common when sepsis was not documented. Conclusion: A computerized sepsis screening and alert system designed to identify sepsis in hospitalized medical ward patients without the use of vital signs was feasible to implement and predictive for sepsis. This suggests that implementation of this system may improve the quality of sepsis care in hospitalized ward patients.

Among surgical intensive care unit (SICU) patients, it is difficult to distinguish bacterial sepsis from other causes of systemic inflammatory response syndrome (SIRS). Biomarkers have proven useful to identify the presence of bacterial infection. We enrolled a prospective cohort of 69 SICU patients with suspected sepsis and assayed the concentrations of 9 biomarkers (α-2 macroglobulin [A2M], C-reactive protein, ferritin, fibrinogen, haptoglobin, procalcitonin [PCT], serum amyloid A, serum amyloid P, and tissue plasminogen activator) at baseline, 24, 48, and 72hours. Forty-two patients (61%) had bacterial sepsis by chart review. A2M concentrations were significantly lower, and PCT concentrations were significantly higher in subjects with bacterial sepsis at 3 of 4 time points. Using optimal cutoff values, the combination of baseline A2M and 72-hour PCT achieved a negative predictive value of 75% (95% confidence interval, 54-96%). The combination of A2M and PCT discriminated bacterial sepsis from other SIRS among SICU patients with suspected sepsis.

Summary Background Acute kidney injury often goes unrecognised in its early stages when effective treatment options might be available. We aimed to determine whether an automated electronic alert for acute kidney injury would reduce the severity of such injury and improve clinical outcomes in patients in hospital. Methods In this investigator-masked, parallel-group, randomised controlled trial, patients were recruited from the hospital of the University of Pennsylvania in Philadelphia, PA, USA. Eligible participants were adults aged 18 years or older who were in hospital with stage 1 or greater acute kidney injury as defined by Kidney Disease Improving Global Outcomes creatinine-based criteria. Exclusion criteria were initial hospital creatinine 4·0 mg/dL (to convert to μmol/L, multiply by 88·4) or greater, fewer than two creatinine values measured, inability to determine the covering provider, admission to hospice or the observation unit, previous randomisation, or end-stage renal disease. Patients were randomly assigned (1:1) via a computer-generated sequence to receive an acute kidney injury alert (a text-based alert sent to the covering provider and unit pharmacist indicating new acute kidney injury) or usual care, stratified by medical versus surgical admission and intensive care unit versus non-intensive care unit location in blocks of 4–8 participants. The primary outcome was a composite of relative maximum change in creatinine, dialysis, and death at 7 days after randomisation. All analyses were by intention to treat. This study is registered with ClinicalTrials.gov, number NCT01862419. Findings Between Sept 17, 2013, and April 14, 2014, 23 664 patients were screened. 1201 eligible participants were assigned to the acute kidney injury alert group and 1192 were assigned to the usual care group. Composite relative maximum change in creatinine, dialysis, and death at 7 days did not differ between the alert group and the usual care group (p=0·88), or within any of the four randomisation strata (all p>0·05). At 7 days after randomisation, median maximum relative change in creatinine concentrations was 0·0% (IQR 0·0–18·4) in the alert group and 0·6% (0·0–17·5) in the usual care group (p=0·81); 87 (7·2%) patients in the alert group and 70 (5·9%) patients in usual care group had received dialysis (odds ratio 1·25 [95% CI 0·90–1·74]; p=0·18); and 71 (5·9%) patients in the alert group and 61 (5·1%) patients in the usual care group had died (1·16 [0·81–1·68]; p=0·40). Interpretation An electronic alert system for acute kidney injury did not improve clinical outcomes among patients in hospital. Funding Penn Center for Healthcare Improvement and Patient Safety.