Publications by authors named "Elizabeth Colantuoni"

174 Publications

Quantifying the Ripple Effects of Civil War: How Armed Conflict Is Associated with More Severe Violence in the Home.

Health Hum Rights 2021 Jun;23(1):75-89

Associate Professor in the Department of Population, Family and Reproductive Health and Director of the Women's Health and Rights Program at the Center for Public Health Human Rights, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.

Both the fields of public health and that of human rights seek to improve human well-being, including through reducing and preventing all forms of violence, to help individuals attain the highest quality of life. In both fields, mathematical methods can help "visibilize" the hidden architecture of violence, bringing new methods to bear to understand the scope and nuance of how violence affects populations. An increasing number of studies have examined how residing in a conflict-affected place may impact one of the most pervasive forms of violence-intimate partner violence (IPV)-during and after conflict. This paper contributes to this effort by examining whether severe forms of IPV are associated with previous experience of political violence in one conflict-affected country: Liberia. Our findings indicate that living in a district with conflict fatalities increased the risk of IPV among women by roughly 60%. Additionally, living in a district with conflict fatalities increased the risk of a past-year injury from IPV by 50%. This analysis brings to light links between two of the most pervasive forms of violence-political violence and violence against women. The findings suggest that women residing in a district that is more highly affected by conflict, not only people experiencing direct trauma during conflict, may be at risk of increased violence long after peace is declared. These findings point to the need for targeted programs that address IPV postconflict.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233021PMC
June 2021

Six-month and 12-month patient outcomes based on inflammatory subphenotypes in sepsis-associated ARDS: secondary analysis of SAILS-ALTOS trial.

Thorax 2021 Jun 10. Epub 2021 Jun 10.

Outcomes After Critical Illness and Surgery (OACIS) Group, Johns Hopkins University, Baltimore, Maryland, USA

Background: Prior acute respiratory distress syndrome (ARDS) trials have identified hypoinflammatory and hyperinflammatory subphenotypes, with distinct differences in short-term outcomes. It is unknown if such differences extend beyond 90 days or are associated with physical, mental health or cognitive outcomes.

Methods: 568 patients in the multicentre Statins for Acutely Injured Lungs from Sepsis trial of rosuvastatin versus placebo were included and assigned a subphenotype. Among 6-month and 12-month survivors (N=232 and 219, respectively, representing 243 unique survivors), subphenotype status was evaluated for association with a range of patient-reported outcomes (eg, mental health symptoms, quality of life). Patient subsets also were evaluated with performance-based tests of physical function (eg, 6 min walk test) and cognition.

Findings: The hyperinflammatory versus hypoinflammatory subphenotype had lower overall 12-month cumulative survival (58% vs 72%, p<0.01); however, there was no significant difference in survival beyond 90 days (86% vs 89%, p=0.70). Most survivors had impairment across the range of outcomes, with little difference between subphenotypes at 6-month and 12-month assessments. For instance, at 6 months, in comparing the hypoinflammatory versus hyperinflammatory subphenotypes, respectively, the median (IQR) patient-reported SF-36 mental health domain score was 47 (33-56) vs 44 (35-56) (p=0.99), and the per cent predicted 6 min walk distance was 66% (48%, 80%) vs 66% (49%, 79%) (p=0.76).

Interpretation: Comparing the hyperinflammatory versus hypoinflammatory ARDS subphenotype, there was no significant difference in survival beyond 90 days and no consistent findings of important differences in 6-month or 12-month physical, cognitive and mental health outcomes. These findings, when considered with prior results, suggest that inflammatory subphenotypes largely reflect the acute phase of illness and its short-term impact.
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http://dx.doi.org/10.1136/thoraxjnl-2020-216613DOI Listing
June 2021

Heterogeneity in design and analysis of ICU delirium randomized trials: a systematic review.

Trials 2021 May 20;22(1):354. Epub 2021 May 20.

Outcomes After Critical Illness and Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA.

Background: There is a growing number of randomized controlled trials (RCTs) evaluating interventions to prevent or treat delirium in the intensive care unit (ICU). Efforts to improve the conduct of delirium RCTs are underway, but none address issues related to statistical analysis. The purpose of this review is to evaluate heterogeneity in the design and analysis of delirium outcomes and advance methodological recommendations for delirium RCTs in the ICU.

Methods: Relevant databases, including PubMed and Embase, were searched with no restrictions on language or publication date; the search was conducted on July 8, 2019. RCTs conducted on adult ICU patients with delirium as the primary outcome were included where trial results were available. Data on frequency and duration of delirium assessments, delirium outcome definitions, and statistical methods were independently extracted in duplicate. The review was registered with PROSPERO (CRD42020141204).

Results: Among 65 eligible RCTs, 44 (68%) targeted the prevention of delirium. The duration of follow-up varied, with 31 (48%) RCTs having ≤7 days of follow-up, and only 24 (37%) conducting delirium assessments after ICU discharge. The incidence of delirium was the most common outcome (50 RCTs, 77%) for which 8 unique statistical methods were applied. The most common method, applied to 51 of 56 (91%) delirium incidence outcomes, was the two-sample test comparing the proportion of patients who ever experienced delirium. In the presence of censoring of patients at ICU discharge or death, this test may be misleading. The impact of censoring was also not considered in most analyses of the duration of delirium, as evaluated in 24 RCTs, with 21 (88%) delirium duration outcomes analyzed using a non-parametric test or two-sample t test. Composite outcomes (e.g., rank-based delirium- and coma-free days), used in 11 (17%) RCTs, seldom explicitly defined how ICU discharge, and death were incorporated into the definition and were analyzed using non-parametric tests (11 of 13 (85%) composite outcomes).

Conclusions: To improve delirium RCTs, outcomes should be explicitly defined. To account for censoring due to ICU discharge or death, survival analysis methods should be considered for delirium incidence and duration outcomes; non-parametric tests are recommended for rank-based delirium composite outcomes.

Trial Registration: PROSPERO CRD42020141204 . Registration date: 7/3/2019.
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http://dx.doi.org/10.1186/s13063-021-05299-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136095PMC
May 2021

covid19census: U.S. and Italy COVID-19 metrics and other epidemiological data.

Database (Oxford) 2021 05;2021

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA.

Since the beginning of the coronavirus disease-2019 (COVID-19) pandemic in 2020, there has been a tremendous accumulation of data capturing different statistics including the number of tests, confirmed cases and deaths. This data wealth offers a great opportunity for researchers to model the effect of certain variables on COVID-19 morbidity and mortality and to get a better understanding of the disease at the epidemiological level. However, in order to draw any reliable and unbiased estimate, models also need to take into account other variables and metrics available from a plurality of official and unofficial heterogenous resources. In this study, we introduce covid19census, an R package that extracts from many different repositories and combines together COVID-19 metrics and other demographic, environment- and health-related variables of the USA and Italy at the county and regional levels, respectively. The package is equipped with a number of user-friendly functions that dynamically extract the data over different timepoints and contains a detailed description of the included variables. To demonstrate the utility of this tool, we used it to extract and combine different county-level data from the USA, which we subsequently used to model the effect of diabetes on COVID-19 mortality at the county level, taking into account other variables that may influence such effects. In conclusion, it was observed that the 'covid19census' package allows to easily extract area-level data from both the USA and Italy using few functions. These comprehensive data can be used to provide reliable estimates of the effect of certain variables on COVID-19 outcomes. Database URL: https://github.com/c1au6i0/covid19census.
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http://dx.doi.org/10.1093/database/baab027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8122363PMC
May 2021

Design of Clinical Trials Evaluating Sedation in Critically Ill Adults Undergoing Mechanical Ventilation: Recommendations From Sedation Consortium on Endpoints and Procedures for Treatment, Education, and Research (SCEPTER) Recommendation III.

Crit Care Med 2021 Apr 28. Epub 2021 Apr 28.

1 Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY. 2 University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. 3School of Health Sciences, University of London, London, United Kingdom. 4 School of Nursing and Midwifery, Griffith University, Brisbane, QLD, Australia. 5 Center of Healthy Aging, Self-Management, and Complex Care, The Ohio State University, College of Nursing, Columbus, OH. 6 Clear Consults, LLC, Hayward, WI. 7 Leslie Dan Faculty of Pharmacy, Mount Sinai Hospital, University of Toronto, Toronto, ON, Canada. 8 Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University School of Medicine, Baltimore, MD. 9 Departments of Anesthesiology and Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI. 10 School of Pharmacy, Northeastern University, Boston, MA 11 Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA. 12 Department of Anesthesia, University of Iowa, Iowa City, IA. 13 Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY. 14 Department of Anesthesiology, University of Utah, Salt Lake City, UT. 15 Faculty of Health, University of Technology Sydney, Sydney, NSW, Australia. 16 Intensive Care Unit, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark. 17 Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Palo Alto, CA. 18 Department of Medicine, Tufts University School of Medicine, Maine Medical Center, Portland, ME. 9 Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA. 20 Division of Anesthesiology and CCM, Hadassah Medical Center, The Hebrew University School of Medicine, Jerusalem, Israel. 21 Psychology Department and Neuroscience Center, Brigham Young University, Provo, UT. 22 Center for Humanizing Critical Care, Intermountain Medical Center, Murray, UT. 23 Department of Medicine, Section of Pulmonary and Critical Care, The University of Chicago, Chicago, IL. 24 Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, CA. 25 Division of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD. 26 Department of Anesthesiology and the Critical Illness, Vanderbilt University Medical Center, Nashville, TN. 27 Department of Critical Care Services, Maine Medical Center, Portland, ME. 28 Department of Outcomes Research, Cleveland Clinic, Cleveland, OH. 29 Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Palo Alto, CA. 30 Monash Health School of Clinical Sciences - Department of Intensive Care Medicine - Critical Care Research, Melbourne, VIC, Australia. 31 Department of Anesthesiology and Operative Intensive Care Medicine, Charité - Universitätsmedizin Berlin, Campus Charité Mitte & Campus Virchow-Klinikum, Berlin, Germany. 32 Department of Anesthesiology, Columbia University Medical Center, New York, NY. 33 Department of Anesthesia and Critical Care, The University of Chicago, Chicago, IL. 34 Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.

Objectives: Clinical trials evaluating the safety and effectiveness of sedative medication use in critically ill adults undergoing mechanical ventilation differ considerably in their methodological approach. This heterogeneity impedes the ability to compare results across studies. The Sedation Consortium on Endpoints and Procedures for Treatment, Education, and Research Recommendations convened a meeting of multidisciplinary experts to develop recommendations for key methodologic elements of sedation trials in the ICU to help guide academic and industry clinical investigators.

Design: A 2-day in-person meeting was held in Washington, DC, on March 28-29, 2019, followed by a three-round, online modified Delphi consensus process.

Participants: Thirty-six participants from academia, industry, and the Food and Drug Administration with expertise in relevant content areas, including two former ICU patients attended the in-person meeting, and the majority completed an online follow-up survey and participated in the modified Delphi process.

Measurements And Main Results: The final recommendations were iteratively refined based on the survey results, participants' reactions to those results, summaries written by panel moderators, and a review of the meeting transcripts made from audio recordings. Fifteen recommendations were developed for study design and conduct, subject enrollment, outcomes, and measurement instruments. Consensus recommendations included obtaining input from ICU survivors and/or their families, ensuring adequate training for personnel using validated instruments for assessments of sedation, pain, and delirium in the ICU environment, and the need for methodological standardization.

Conclusions: These recommendations are intended to assist researchers in the design, conduct, selection of endpoints, and reporting of clinical trials involving sedative medications and/or sedation protocols for adult ICU patients who require mechanical ventilation. These recommendations should be viewed as a starting point to improve clinical trials and help reduce methodological heterogeneity in future clinical trials.
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http://dx.doi.org/10.1097/CCM.0000000000005049DOI Listing
April 2021

Influenza Vaccination and COVID-19 Mortality in the USA: An Ecological Study.

Vaccines (Basel) 2021 Apr 24;9(5). Epub 2021 Apr 24.

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA.

The COVID-19 mortality rate is higher in the elderly and in those with pre-existing chronic medical conditions. The elderly also suffer from increased morbidity and mortality from seasonal influenza infections; thus, an annual influenza vaccination is recommended for them. In this study, we explore a possible county-level association between influenza vaccination coverage in people aged 65 years and older and the number of deaths from COVID-19. To this end, we used COVID-19 data up to 14 December 2020 and US population health data at the county level. We fit quasi-Poisson regression models using influenza vaccination coverage in the elderly population as the independent variable and the COVID-19 mortality rate as the outcome variable. We adjusted for an array of potential confounders using different propensity score regression methods. Results show that, on the county level, influenza vaccination coverage in the elderly population is negatively associated with mortality from COVID-19, using different methodologies for confounding adjustment. These findings point to the need for studying the relationship between influenza vaccination and COVID-19 mortality at the individual level to investigate any underlying biological mechanisms.
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http://dx.doi.org/10.3390/vaccines9050427DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145634PMC
April 2021

A structured methodology review showed analyses of functional outcomes are frequently limited to "survivors only" in trials enrolling patients at high risk of death.

J Clin Epidemiol 2021 Apr 7;137:126-132. Epub 2021 Apr 7.

Outcomes After Critical Illness and Surgery (OACIS) Group, Johns Hopkins University, Baltimore, Maryland, USA; Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Objective: This structured methodology review evaluated statistical approaches used in randomized controlled trials (RCTs) enrolling patients at high risk of death and makes recommendations for reporting future RCTs.

Study Design And Setting: Using PubMed, we searched for RCTs published in five general medicine journals from January 2014 to August 2019 wherein mortality was ≥10% in at least one randomized group. We abstracted primary and secondary outcomes, statistical analysis methods, and patient samples evaluated (all randomized patients vs. "survivors only").

Results: Of 1947 RCTs identified, 434 met eligibility criteria. Of the eligible RCTs, 91 (21%) and 351 (81%) had a primary or secondary functional outcome, respectively, of which 36 (40%) and 263 (75%) evaluated treatment effects among "survivors only". In RCTs that analyzed all randomized patients, the most common methods included use of ordinal outcomes (e.g., modified Rankin Scale) or creating composite outcomes (primary: 41 of 91 [45%]; secondary: 57 of 351 [16%]).

Conclusion: In RCTs enrolling patients at high risk of death, statistical analyses of functional outcomes are frequently conducted among "survivors only," for which conclusions might be misleading. Given the growing number of RCTs conducted among patients hospitalized with COVID-19 and other critical illnesses, standards for reporting should be created.
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http://dx.doi.org/10.1016/j.jclinepi.2021.03.027DOI Listing
April 2021

Diagnostic Stewardship of Endotracheal Aspirate Cultures in a PICU.

Pediatrics 2021 May 7;147(5). Epub 2021 Apr 7.

Departments of Pediatrics and.

Background: Clinicians commonly obtain endotracheal aspirate cultures (EACs) in the evaluation of suspected ventilator-associated infections. However, bacterial growth in EACs does not distinguish bacterial colonization from infection and may lead to overtreatment with antibiotics. We describe the development and impact of a clinical decision support algorithm to standardize the use of EACs from ventilated PICU patients.

Methods: We monitored EAC use using a statistical process control chart. We compared the rate of EACs using Poisson regression and a quasi-experimental interrupted time series model and assessed clinical outcomes 1 year before and after introduction of the algorithm.

Results: In the preintervention year, there were 557 EACs over 5092 ventilator days; after introduction of the algorithm, there were 234 EACs over 3654 ventilator days (an incident rate of 10.9 vs 6.5 per 100 ventilator days). There was a 41% decrease in the monthly rate of EACs (incidence rate ratio [IRR]: 0.59; 95% confidence interval [CI] 0.51-0.67; < .001). The interrupted time series model revealed a preexisting 2% decline in the monthly culture rate (IRR: 0.98; 95% CI 0.97-1.0; = .01), immediate 44% drop (IRR: 0.56; 95% CI 0.45-0.70; = .02), and stable rate in the postintervention year (IRR: 1.03; 95% CI 0.99-1.07; = .09). In-hospital mortality, hospital length of stay, 7-day readmissions, and All Patients Refined Diagnosis Related Group severity and mortality scores were stable. The estimated direct cost savings was $26 000 per year.

Conclusions: A clinical decision support algorithm standardizing EAC obtainment from ventilated PICU patients was associated with a sustained decline in the rate of EACs, without changes in mortality, readmissions, or length of stay.
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http://dx.doi.org/10.1542/peds.2020-1634DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086005PMC
May 2021

Impact of postnatal age on neonatal intensive care unit bloodstream infection reporting.

Am J Infect Control 2021 Apr 2. Epub 2021 Apr 2.

Department of Pediatrics, Division of Infectious Diseases, Johns Hopkins University, Baltimore, MD; Department of Healthcare Epidemiology and Infection Prevention, Johns Hopkins Health System, Baltimore, MD. Electronic address:

Due to their short- and long-term impact on patients in the neonatal intensive care unit (NICU), bloodstream infections are a closely monitored quality measure. NICU infection rates are risk-adjusted for birth weight, but not postnatal age. Our findings suggest that infection rates are not constant over time in neonates with long NICU lengths of stay and adjusting for postnatal age in addition to birth weight may improve unit comparisons.
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http://dx.doi.org/10.1016/j.ajic.2021.03.018DOI Listing
April 2021

The Effect of a Quality Improvement Intervention on Sleep and Delirium in Critically Ill Patients in a Surgical ICU.

Chest 2021 Mar 24. Epub 2021 Mar 24.

Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego, School of Medicine, La Jolla, CA.

Background: Delirium is a deleterious condition affecting up to 60% of patients in the surgical ICU (SICU). Few SICU-focused delirium interventions have been implemented, including those addressing sleep-wake disruption, a modifiable delirium risk factor common in critically ill patients.

Research Question: What is the effect on delirium and sleep quality of a multicomponent nonpharmacologic intervention aimed at improving sleep-wake disruption in patients in the SICU setting?

Study Design And Methods: Using a staggered pre-post design, we implemented a quality improvement intervention in two SICUs (general surgery or trauma and cardiovascular) in an academic medical center. After a preintervention (baseline) period, a multicomponent unit-wide nighttime (ie, efforts to minimize unnecessary sound and light, provision of earplugs and eye masks) and daytime (ie, raising blinds, promotion of physical activity) intervention bundle was implemented. A daily checklist was used to prompt staff to complete intervention bundle elements. Delirium was evaluated twice daily using the Confusion Assessment Method for the Intensive Care Unit. Patient sleep quality ratings were evaluated daily using the Richards-Campbell Sleep Questionnaire (RCSQ).

Results: Six hundred forty-six SICU admissions (332 baseline, 314 intervention) were analyzed. Median age was 61 years (interquartile range, 49-70 years); 35% of the cohort were women and 83% were White. During the intervention period, patients experienced fewer days of delirium (proportion ± SD of ICU days, 15 ± 27%) as compared with the preintervention period (20 ± 31%; P = .022), with an adjusted pre-post decrease of 4.9% (95% CI, 0.5%-9.2%; P = .03). Overall RCSQ-perceived sleep quality ratings did not change, but the RCSQ noise subscore increased (9.5% [95% CI, 1.1%-17.5%; P = .02).

Interpretation: Our multicomponent intervention was associated with a significant reduction in the proportion of days patients experienced delirium, reinforcing the feasibility and effectiveness of a nonpharmacologic sleep-wake bundle to reduce delirium in critically ill patients in the SICU.

Trial Registry: ClinicalTrials.gov; No.: NCT03313115; URL: www.clinicaltrials.gov.
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http://dx.doi.org/10.1016/j.chest.2021.03.030DOI Listing
March 2021

Cerebral autoregulation in the operating room and intensive care unit after cardiac surgery.

Br J Anaesth 2021 May 23;126(5):967-974. Epub 2021 Mar 23.

Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address:

Background: Cerebral autoregulation monitoring is a proposed method to monitor perfusion during cardiac surgery. However, limited data exist from the ICU as prior studies have focused on intraoperative measurements. Our objective was to characterise cerebral autoregulation during surgery and early ICU care, and as a secondary analysis to explore associations with delirium.

Methods: In patients undergoing cardiac surgery (n=134), cerebral oximetry values and arterial BP were monitored and recorded until the morning after surgery. A moving Pearson's correlation coefficient between mean arterial proessure (MAP) and near-infrared spectroscopy signals generated the cerebral oximetry index (COx). Three metrics were derived: (1) globally impaired autoregulation, (2) MAP time and duration outside limits of autoregulation (MAP dose), and (3) average COx. Delirium was assessed using the 3-Minute Diagnostic Interview for CAM-defined Delirium (3D-CAM) and the Confusion Assessment Method for the ICU (CAM-ICU). Autoregulation metrics were compared using χ and rank-sum tests, and associations with delirium were estimated using regression models, adjusted for age, bypass time, and logEuroSCORE.

Results: The prevalence of globally impaired autoregulation was higher in the operating room vs ICU (40% vs 13%, P<0.001). The MAP dose outside limits of autoregulation was similar in the operating room and ICU (median 16.9 mm Hg×h; inter-quartile range [IQR] 10.1-38.8 vs 16.9 mm Hg×h; IQR 5.4-35.1, P=0.20). In exploratory adjusted analyses, globally impaired autoregulation in the ICU, but not the operating room, was associated with delirium. The MAP dose outside limits of autoregulation in the operating room and ICU was also associated with delirium.

Conclusions: Metrics of cerebral autoregulation are altered in the ICU, and may be clinically relevant with respect to delirium. Further studies are needed to investigate these findings and determine possible benefits of autoregulation-based MAP targeting in the ICU.
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http://dx.doi.org/10.1016/j.bja.2020.12.043DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132879PMC
May 2021

Clarifying the Impact of Predicted Versus Observed Control Arm Mortality Rates on Randomized Trials in Critical Illness.

Crit Care Med 2021 Apr;49(4):e483-e484

Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.

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http://dx.doi.org/10.1097/CCM.0000000000004866DOI Listing
April 2021

Functional electrical stimulation in-bed cycle ergometry in mechanically ventilated patients: a multicentre randomised controlled trial.

Thorax 2021 07 15;76(7):656-663. Epub 2020 Dec 15.

Melbourne School of Health Sciences, The University of Melbourne, Parkville, Victoria, Australia.

Purpose: To investigate the effect of functional electrical stimulation-assisted cycle ergometry (FES-cycling) on muscle strength, cognitive impairment and related outcomes.

Methods: Mechanically ventilated patients aged ≥18 years with sepsis or systemic inflammatory response syndrome were randomised to either 60 min of FES-cycling 5 days/week while in the intensive care unit (ICU) plus usual care rehabilitation versus usual care rehabilitation alone, with evaluation of two primary outcomes: (1) muscle strength at hospital discharge and (2) cognitive impairment at 6-month follow-up.

Results: We enrolled 162 participants, across four study sites experienced in ICU rehabilitation in Australia and the USA, to FES-cycling (n=80; mean age±SD 59±15) versus control (n=82; 56±14). Intervention participants received a median (IQR) of 5 (3-9) FES-cycling sessions with duration of 56 (34-63) min/day plus 15 (10-23) min/day of usual care rehabilitation. The control group received 15 (8-15) min/day of usual care rehabilitation. In the intervention versus control group, there was no significant differences for muscle strength at hospital discharge (mean difference (95% CI) 3.3 (-5.0 to 12.1) Nm), prevalence of cognitive impairment at 6 months (OR 1.1 (95% CI 0.30 to 3.8)) or secondary outcomes measured in-hospital and at 6 and 12 months follow-up.

Conclusion: In this randomised controlled trial, undertaken at four centres with established rehabilitation programmes, the addition of FES-cycling to usual care rehabilitation did not substantially increase muscle strength at hospital discharge. At 6 months, the incidence of cognitive impairment was almost identical between groups, but potential benefit or harm of the intervention on cognition cannot be excluded due to imprecision of the estimated effect.

Trial Registration Number: ACTRN 12612000528853, NCT02214823.
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http://dx.doi.org/10.1136/thoraxjnl-2020-215093DOI Listing
July 2021

Frailty subtypes and recovery in older survivors of acute respiratory failure: a pilot study.

Thorax 2021 04 9;76(4):350-359. Epub 2020 Dec 9.

Pulmonary, Allergy, and Critical Care, Columbia University Irving Medical Center, New York, New York, USA.

Background: Identifying subtypes of acute respiratory failure survivors may facilitate patient selection for post-intensive care unit (ICU) follow-up clinics and trials.

Methods: We conducted a single-centre prospective cohort study of 185 acute respiratory failure survivors, aged ≥ 65 years. We applied latent class modelling to identify frailty subtypes using frailty phenotype and cognitive impairment measurements made during the week before hospital discharge. We used Fine-Gray competing risks survival regression to test associations between frailty subtypes and recovery, defined as returning to a basic Activities of Daily Living disability count less than or equal to the pre-hospitalisation count within 6 months. We characterised subtypes by pre-ICU frailty (Clinical Frailty Scale score ≥ 5), the post-ICU frailty phenotype, and serum inflammatory cytokines, hormones and exosome proteomics during the week before hospital discharge.

Results: We identified five frailty subtypes. The recovery rate decreased 49% across each subtype independent of age, sex, pre-existing disability, comorbidity and Acute Physiology and Chronic Health Evaluation II score (recovery rate ratio: 0.51, 95% CI 0.41 to 0.63). Post-ICU frailty phenotype prevalence increased across subtypes, but pre-ICU frailty prevalence did not. In the subtype with the slowest recovery, all had cognitive impairment. The three subtypes with the slowest recovery had higher interleukin-6 levels (p=0.03) and a higher prevalence of ≥ 2 deficiencies in insulin growth factor-1, dehydroepiandrostersone-sulfate, or free-testosterone (p=0.02). Exosome proteomics revealed impaired innate immunity in subtypes with slower recovery.

Conclusions: Frailty subtypes varied by prehospitalisation frailty and cognitive impairment at hospital discharge. Subtypes with the slowest recovery were similarly characterised by greater systemic inflammation and more anabolic hormone deficiencies at hospital discharge.
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http://dx.doi.org/10.1136/thoraxjnl-2020-214998DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187474PMC
April 2021

idem: An R Package for Inferences in Clinical Trials with Death and Missingness.

J Stat Softw 2020 May;93

Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore MD, 21205, United States of America.

In randomized controlled trials of seriously ill patients, death is common and often defined as the primary endpoint. Increasingly, non-mortality outcomes such as functional outcomes are co-primary or secondary endpoints. Functional outcomes are not defined for patients who die, referred to as "truncation due to death", and among survivors, functional outcomes are often unobserved due to missed clinic visits or loss to follow-up. It is well known that if the functional outcomes "truncated due to death" or missing are handled inappropriately, treatment effect estimation can be biased. In this paper, we describe the package that implements a procedure for comparing treatments that is based on a composite endpoint of mortality and the functional outcome among survivors. Among survivors, the procedure incorporates a missing data imputation procedure with a sensitivity analysis strategy. A web-based graphical user interface is provided in the package to facilitate users conducting the proposed analysis in an interactive and user-friendly manner. We demonstrate using data from a recent trial of sedation interruption among mechanically ventilated patients.
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http://dx.doi.org/10.18637/jss.v093.i12DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710152PMC
May 2020

Racial and ethnic disparities in hospital observation in Maryland.

Am J Emerg Med 2020 Nov 11. Epub 2020 Nov 11.

Johns Hopkins University School of Medicine, Department of Emergency Medicine, Baltimore, MD, USA. Electronic address:

Objectives: Hospital observation is a key disposition option from the emergency department (ED) and encompasses up to one third of patients requiring post-ED care. Observation has been associated with higher incidence of catastrophic financial costs and has downstream effects on post-discharge clinical services. Yet little is known about the non-clinical determinants of observation assignment. We sought to evaluate the impact of patient-level demographic factors on observation designation among Maryland patients.

Methods: We conducted a retrospective analysis of all ED encounters in Maryland between July 2012 and January 2017 for four priority diagnoses (heart failure, chronic obstructive pulmonary disease [COPD], pneumonia, and acute chest pain) using multilevel logistic models allowing for heterogeneity of the effects across hospitals. The primary exposure was self-reported race and ethnicity. The primary outcome was the initial status assignment from the ED: hospital observation versus inpatient admission.

Results: Across 46 Maryland hospitals, 259,788 patient encounters resulted in a disposition of inpatient admission (65%) or observation designation (35%). Black (adjusted odds ratio [aOR]: 1.19; 95% confidence interval [CI]: 1.16-1.23) and Hispanic (aOR: 1.11; 95% CI: 1.01-1.21) patients were significantly more likely to be placed in observation than white, non-Hispanic patients. These differences were consistent across the majority of acute-care hospitals in Maryland (27/46).

Conclusion: Black and Hispanic patients in Maryland are more likely to be treated under the observation designation than white, non-Hispanic patients independent of clinical presentation. Race agnostic, time-based status assignments may be key in eliminating these disparities.
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http://dx.doi.org/10.1016/j.ajem.2020.11.010DOI Listing
November 2020

Participant retention in trauma intensive care unit (ICU) follow-up studies: a post-hoc analysis of a previous scoping review.

Trauma Surg Acute Care Open 2020 4;5(1):e000584. Epub 2020 Nov 4.

Outcomes After Critical Illness and Surgery Group, Johns Hopkins University, Baltimore, Maryland, USA.

Background: The study aimed to synthesize participant retention-related data for longitudinal follow-up studies of survivors from trauma intensive care units (ICUs).

Methods: Within a published scoping review evaluating ICU patient outcomes after hospital discharge, two screeners independently searched for trauma ICU survivorship studies.

Results: There were 11 trauma ICU follow-up studies, all of which were cohort studies. Twelve months (range: 1-60 months) was the most frequent follow-up time point for assessment (63% of studies). Retention rates ranged from 54% to 94% across time points and could not be calculated for two studies (18%). Pooled retention rates at 3, 6, and 12 months were 75%, 81%, and 81%, respectively. Mean patient age (OR 0.85 per 1-year increase, 95% CI 0.73 to 0.99, p=0.036), percent of men (OR 1.07, 95% CI 1.04 to 1.10, p=0.002), and publication year (OR 0.89 per 1-year increase, 95% CI 0.82 to 0.95, p=0.007) were associated with retention rates. Early (3-month) versus later (6-month, 12-month) follow-up time point was not associated with retention rates.

Discussion: Pooled retention rates were >75%, at 3-month, 6-month, and 12-month time points, with wide variability across studies and time points. There was little consistency with reporting participant retention methodology and related data. More detailed reporting guidelines, with better author adherence, will help improve reporting of participant retention data. Utilization of existing research resources may help improve participant retention.

Level Of Evidence: Level III: meta-analyses (post-hoc analyses) of a prior scoping review.
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http://dx.doi.org/10.1136/tsaco-2020-000584DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7643521PMC
November 2020

Factors Associated With Home Visits in a 5-Year Study of Acute Respiratory Distress Syndrome Survivors.

Am J Crit Care 2020 11;29(6):429-438

Victor D. Dinglas is a research associate in the Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, and a member of the Outcomes After Critical Illness and Surgery Group, Johns Hopkins University.

Background: Participant retention is vital for longitudinal studies. Home visits may increase retention, but little is known about the subset of patients they benefit.

Objective: To evaluate patient-related variables associated with home visits.

Methods: In a 5-year, longitudinal, multisite, prospective study of 195 survivors of acute respiratory distress syndrome, in-person assessments were conducted at a research clinic. Home visits were offered to participants who could not attend the clinic. Associations between having a home visit, prior follow-up visit status, and baseline and in-hospital patient variables were evaluated with multivariable, random-intercept logistic regression models. The association between home visits and patients' posthospital clinical status was evaluated with a subsequent regression model adjusted for these variables.

Results: Participants had a median age of 49 years and were 56% male and 58% White. The following had independent associations with home visits (adjusted odds ratio [95% CI]): age (per year: 1.03 [1.00-1.05]) and immediately preceding visit incomplete (2.46 [1.44-4.19]) or at home (8.24 [4.57-14.86]). After adjustment for prior-visit status and baseline and hospitalization variables, these posthospital patient outcome variables were associated with a subsequent home visit: instrumental activities of daily living (≥ 2 vs < 2 dependencies: 2.32 [1.29-4.17]), EQ-5D utility score (per 0.1-point decrease: 1.15 [1.02-1.30]), and 6-minute walk test (per 10-percentage-point decrease in percent-predicted distance: 1.50 [1.26-1.79]).

Conclusions: Home visits were important for retaining older and more physically impaired study participants, helping reduce selection bias caused by excluding them.
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http://dx.doi.org/10.4037/ajcc2020966DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7640764PMC
November 2020

Measuring Structural Racism and Its Association With BMI.

Am J Prev Med 2020 10 27;59(4):530-537. Epub 2020 Aug 27.

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.

Introduction: Structural racism has attracted increasing interest as an explanation for racial disparities in health, including differences in adiposity. Structural racism has been measured most often with single-indicator proxies (e.g., housing discrimination), which may leave important aspects of structural racism unaccounted for. This paper develops a multi-indicator scale measuring county structural racism in the U.S. and evaluates its association with BMI.

Methods: County structural racism was estimated with a confirmatory factor model including indicators reflecting education, housing, employment, criminal justice, and health care. Using Behavioral Risk Factor Surveillance Survey data (2011-2012) and a mixed-effects model, individual BMI was regressed on county structural racism, controlling for county characteristics (mean age, percentage black, percentage female, percentage rural, median income, and region). Analysis occurred 2017-2019.

Results: The study included 324,572 U.S. adults. A 7-indicator county structural racism model demonstrated acceptable fit. County structural racism was associated with lower BMI. Structural racism and black race exhibited a qualitative interaction with BMI, such that racism was associated with lower BMI in whites and higher BMI in blacks. In a further interaction analysis, county structural racism was associated with larger increases in BMI among black men than black women. County structural racism was associated with reduced BMI for white men and no change for white women.

Conclusions: The results confirm structural racism as a latent construct and demonstrate that structural racism can be measured in U.S. counties using publicly available data with methods offering a strong conceptual underpinning and content validity. Further study is necessary to determine whether addressing structural racism may reduce BMI among blacks.
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http://dx.doi.org/10.1016/j.amepre.2020.05.019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147662PMC
October 2020

Inter-rater reliability of the Johns Hopkins Highest Level of Mobility Scale (JH-HLM) in the intensive care unit.

Braz J Phys Ther 2021 May-Jun;25(3):352-355. Epub 2020 Aug 8.

Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Outcomes After Critical Illness and Surgery (OACIS) Group, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address:

Background: The Johns Hopkins Highest Level of Mobility (JH-HLM) scale is used to document the observed mobility of hospitalized patients, including those patients in the intensive care unit (ICU) setting.

Objective: To evaluate the inter-rater reliability of the JH-HLM, completed by physical therapists, across medical, surgical, and neurological adult ICUs at a single large academic hospital.

Methods: The JH-HLM is an ordinal scale for documenting a patient's highest observed level of activity, ranging from lying in bed (score = 1) to ambulating >250 feet (score = 8). Eighty-one rehabilitation sessions were conducted by eight physical therapists, with 1 of 2 reference physical therapist rater simultaneously observing the session and independently scoring the JH-HLM. The intraclass correlation coefficient was used to determine the inter-rater reliability.

Results: A total of 77 (95%) of 81 assessments had perfect agreement. The overall intraclass correlation coefficient for inter-rater reliability was 0.98 (95% confidence interval: 0.96, 0.99), with similar scores in the medical, surgical, and neurological ICUs. A Bland-Altman plot revealed a mean difference in JH-HLM scoring of 0 (limits of agreement: -0.54 to 0.61).

Conclusion: The JH-HLM has excellent inter-rater reliability as part of routine physical therapy practice, across different types of adult ICUs.
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http://dx.doi.org/10.1016/j.bjpt.2020.07.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134787PMC
August 2020

How good is our diagnostic intuition? Clinician prediction of bacteremia in critically ill children.

BMC Med Inform Decis Mak 2020 07 2;20(1):144. Epub 2020 Jul 2.

Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Background: Clinical intuition and nonanalytic reasoning play a major role in clinical hypothesis generation; however, clinicians' intuition about whether a critically ill child is bacteremic has not been explored. We endeavored to assess pediatric critical care clinicians' ability to predict bacteremia and to evaluate what affected the accuracy of those predictions.

Methods: We conducted a retrospective review of clinicians' responses to a sepsis screening tool ("Early Sepsis Detection Tool" or "ESDT") over 6 months. The ESDT was completed during the initial evaluation of a possible sepsis episode. If a culture was ordered, they were asked to predict if the culture would be positive or negative. Culture results were compared to predictions for each episode as well as vital signs and laboratory data from the preceding 24 h.

Results: From January to July 2017, 266 ESDTs were completed. Of the 135 blood culture episodes, 15% of cultures were positive. Clinicians correctly predicted patients with bacteremia in 82% of cases, but the positive predictive value was just 28% as there was a tendency to overestimate the presence of bacteremia. The negative predictive value was 96%. The presence of bandemia, thrombocytopenia, and abnormal CRP were associated with increased likelihood of correct positive prediction.

Conclusions: Clinicians are accurate in predicting critically ill children whose blood cultures, obtained for symptoms of sepsis, will be negative. Clinicians frequently overestimate the presence of bacteremia. The combination of evidence-based practice guidelines and bedside judgment should be leveraged to optimize diagnosis of bacteremia.
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http://dx.doi.org/10.1186/s12911-020-01165-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330962PMC
July 2020

Influenza Vaccination and COVID19 Mortality in the USA.

medRxiv 2020 Jun 26. Epub 2020 Jun 26.

COVID-19 mortality rate is higher in the elderly and in those with preexisting chronic medical conditions. The elderly also suffer from increased morbidity and mortality from seasonal influenza infection, and thus annual influenza vaccination is recommended for them. In this study, we explore a possible area-level association between influenza vaccination coverage in people aged 65 years and older and the number of deaths from COVID-19. To this end, we used COVID-19 data until June 10, 2020 together with population health data for the United States at the county level. We fit quasi-Poisson regression models using influenza vaccination coverage in the elderly population as the independent variable and the number of deaths from COVID-19 as the outcome variable. We adjusted for a wide array of potential confounding variables using both county-level generalized propensity scores for influenza vaccination rates, as well as direct adjustment. Our results suggest that influenza vaccination coverage in the elderly population is negatively associated with mortality from COVID-19. This finding is robust to using different analysis periods, different thresholds for inclusion of counties, and a variety of methodologies for confounding adjustment. In conclusion, our results suggest a potential protective effect of the influenza vaccine on COVID-19 mortality in the elderly population. The significant public health implications of this possibility point to an urgent need for studying the relationship between influenza vaccination and COVID-19 mortality at the individual level, to investigate both the epidemiology and any underlying biological mechanism.
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http://dx.doi.org/10.1101/2020.06.24.20129817DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7325191PMC
June 2020

Inter-rater reliability of activity measure for post-acute care '6-Clicks' inpatient mobility short form in the intensive care unit.

Physiother Res Int 2020 Oct 24;25(4):e1849. Epub 2020 May 24.

Outcomes After Critical Illness and Surgery (OACIS) Group, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Objective: Examine the inter-rater reliability of the activity measure for post-acute care (AM-PAC) inpatient mobility short form (IMSF) when completed by physical therapists (PTs), during routine clinical practice, in a variety of patients with critical illness.

Methods: A prospective observational evaluation at single, large academic hospital in the United States. Patients (n = 76) in surgical, medical and neurological intensive care units (ICUs) were evaluated as part of routine clinical practice using the AM-PAC IMSF administered by eight PTs with at least 6 months of experience using this tool. One of two reference rater PTs observed the physical therapy session, and simultaneously scored the AM-PAC IMSF. The reference rater and clinical PTs were blinded to each other's scores with a minimum of 10 assessments completed by each clinical PT. Bland-Altman plots were constructed and intra-class correlation coefficients (ICC) were computed using a random intercept (physical therapy session) model.

Results: Eighty one assessments (five patients assessed twice) were scored by both a clinical PT and reference rater PT (total assessments = 162). Bland-Altman plots revealed a mean difference in AM-PAC IMSF scoring of 0.0 (95% limits of agreement: -3.0 to +3.0), with an ICC (95% confidence interval) of 0.957 (0.947-0.964). The ICC (95% confidence interval) for patients in surgical, medical and neurological ICUs was very similar: 0.949 (0.927-0.959), 0.963 (0.946-0.971) and 0.936 (0.886-0.955), respectively.

Conclusions: The AM-PAC IMSF demonstrates excellent reliability compared with reference rater PTs when performed by PTs during clinical care across surgical, medical and neurological ICUs.
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http://dx.doi.org/10.1002/pri.1849DOI Listing
October 2020

Participant Retention in Follow-Up Studies of Acute Respiratory Failure Survivors.

Respir Care 2020 Sep 31;65(9):1382-1391. Epub 2020 Mar 31.

Outcomes After Critical Illness and Surgery Group, Johns Hopkins University, Baltimore, Maryland.

Background: With an increasing number of follow-up studies of acute respiratory failure survivors, there is need for a better understanding of participant retention and its reporting in this field of research. Hence, our objective was to synthesize participant retention data and associated reporting for this field.

Methods: Two screeners independently searched for acute respiratory failure survivorship studies within a published scoping review to evaluate subject outcomes after hospital discharge in critical illness survivors.

Results: There were 21 acute respiratory failure studies ( = 4,342 survivors) over 47 follow-up time points. Six-month follow-up (range: 2-60 months) was the most frequently reported time point, in 81% of studies. Only 1 study (5%) reported accounting for loss to follow-up in sample-size calculation. Retention rates could not be calculated for 5 (24%) studies. In 16 studies reporting on retention across all time points, retention ranged from 32% to 100%. Pooled retention rates at 3, 6, 12, and 24 months were 85%, 89%, 82%, and 88%, respectively. Retention rates did not significantly differ by publication year, participant mean age, or when comparing earlier (3 months) versus each later follow-up time point (6, 12, or 24 months).

Conclusions: Participant retention was generally high but varied greatly across individual studies and time points, with 24% of studies reporting inadequate data to calculate retention rate. High participant retention is possible, but resources for optimizing retention may help studies retain participants. Improved reporting guidelines with greater adherence would be beneficial.
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http://dx.doi.org/10.4187/respcare.07461DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906609PMC
September 2020

Identifying Clinical Research Priorities in Adult Pulmonary and Critical Care: NHLBI Working Group Report.

Am J Respir Crit Care Med 2020 Mar 9. Epub 2020 Mar 9.

NHLBI, 35035, Division of Lung Diseases, Bethesda, Maryland, United States;

Preventing, treating, and promoting recovery from critical illness due to pulmonary disease are foundational goals of the critical care community and the National Heart, Lung, and Blood Institute. Decades of clinical research in acute respiratory distress syndrome, acute respiratory failure, pneumonia, and sepsis have yielded improvements in supportive care, which have translated into improved patient outcomes. Novel therapeutics have largely failed to translate from promising pre-clinical findings into improved patient outcomes in late-phase clinical trials. Recent advances in personalized medicine, "big data", causal inference using observational data, novel clinical trial designs, pre-clinical disease modeling, and understanding recovery from acute illness promise to transform the methods of pulmonary and critical care clinical research. To assess the current state, research priorities, and future directions for adult pulmonary and critical care research, the NHLBI assembled a multidisciplinary working group of investigators. This working group identified recommendations for future research, including: (1) focusing on understanding the clinical, physiological, and biological underpinnings of heterogeneity in syndromes, diseases, and treatment-response with the goal of developing targeted, personalized interventions; (2) optimizing pre-clinical models by incorporating comorbidities, co-interventions, and organ support; (3) developing and applying novel clinical trial designs; and (4) advancing mechanistic understanding of injury and recovery in order to develop and test interventions targeted at achieving long-term improvements in the lives of patients and families. Specific areas of research are highlighted as especially promising for making advances in pneumonia, acute hypoxemic respiratory failure, and acute respiratory distress syndrome.
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http://dx.doi.org/10.1164/rccm.201908-1595WSDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427373PMC
March 2020

Use of actigraphy to characterize inactivity and activity in patients in a medical ICU.

Heart Lung 2020 Jul - Aug;49(4):398-406. Epub 2020 Feb 24.

Division of Pulmonary, Critical Care and Sleep Medicine, UC San Diego School of Medicine, 9300 Campus Point Dr. #7381, La Jolla, CA 92037, USA; VA San Diego Healthcare System, 3350 La Jolla Village Dr., San Diego, CA 92161. Electronic address:

Background: In the intensive care unit (ICU), inactivity is common, contributing to ICU-acquired weakness and poor outcomes. Actigraphy may be useful for measuring activity in the ICU.

Objectives: To use actigraphy to characterize inactivity and activity in critically ill patients.

Methods: This prospective observational study involved 48-h wrist actigraphy in medical ICU (MICU) patients, with activity data captured across 30-s epochs. Inactivity (zero-activity epochs) and activity (levels of non-zero activity) were summarized across key patient (e.g., age) and clinical (e.g., mechanical ventilation status) variables, and compared using multivariable regression.

Results: Overall, 189,595 30-s epochs were collected in 34 MICU patients. Zero-activity (inactivity) comprised 122,865 (65%) of epochs; these epochs were 24% and 13% more prevalent, respectively, in patients receiving mechanical ventilation (versus none, p < 0.001) and in the highest (versus lowest) organ failure score tertile (p = 0.03). Ambulatory (versus non-ambulatory) patients exhibited more non-zero activity (35 more movements per epoch, p < 0.001), while those in the highest (versus lowest) organ failure score tertile exhibited less activity (22 fewer movements per epoch, p = 0.03). Significant inactivity/activity differences were not observed when evaluated based on age, sedation, or restraint status.

Conclusions: Actigraphy demonstrated that MICU patients are profoundly inactive, including those who are young, non-sedated and non-restrained. Hence, ICU-specific, non-patient-related factors may contribute to inactivity, an issue requiring further investigation.
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http://dx.doi.org/10.1016/j.hrtlng.2020.02.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305977PMC
December 2020

Effect of Treating Parents Colonized With Staphylococcus aureus on Transmission to Neonates in the Intensive Care Unit: A Randomized Clinical Trial.

JAMA 2020 01;323(4):319-328

Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

Importance: Staphylococcus aureus is a leading cause of health care-associated infections in the neonatal intensive care unit (NICU). Parents may expose neonates to S aureus colonization, a well-established predisposing factor to invasive S aureus disease.

Objective: To test whether treating parents with intranasal mupirocin and topical chlorhexidine compared with placebo would reduce transmission of S aureus from parents to neonates.

Design, Setting, And Participants: Double-blinded randomized clinical trial in 2 tertiary NICUs in Baltimore, Maryland. Neonates (n = 236) with S aureus-colonized parent(s) were enrolled. The study period was November 7, 2014, through December 13, 2018.

Interventions: Parents were assigned to intranasal mupirocin and 2% chlorhexidine-impregnated cloths (active treatment, n = 117) or petrolatum intranasal ointment and nonmedicated soap cloths (placebo, n = 119) for 5 days.

Main Outcomes And Measures: The primary end point was concordant S aureus colonization by 90 days, defined as neonatal acquisition of an S aureus strain that was the same strain as a parental strain at time of screening. Secondary outcomes included neonatal acquisition of any S aureus strain and neonatal S aureus infections.

Results: Among 236 randomized neonates, 208 were included in the analytic sample (55% male; 76% singleton births; mean birth weight, 1985 g [SD, 958 g]; 76% vaginal birth; mean parent age, 31 [SD, 7] years), of whom 18 were lost to follow-up. Among 190 neonates included in the analysis, 74 (38.9%) acquired S aureus colonization by 90 days, of which 42 (56.8%) had a strain concordant with a parental baseline strain. In the intervention and placebo groups, 13 of 89 neonates (14.6%) and 29 of 101 neonates (28.7%), respectively, acquired concordant S aureus colonization (risk difference, -14.1% [95% CI, -30.8% to -3.9%]; hazard ratio [HR], 0.43 [95.2% CI, 0.16 to 0.79]). A total of 28 of 89 neonates (31.4%) in the intervention group and 46 of 101 (45.5%) in the control group acquired any S aureus strain (HR, 0.57 [95% CI, 0.31 to 0.88]), and 1 neonate (1.1%) in the intervention group and 1 neonate (1.0%) in the control group developed an S aureus infection before colonization. Skin reactions in parents were common (4.8% intervention, 6.2% placebo).

Conclusions And Relevance: In this preliminary trial of parents colonized with S aureus, treatment with intranasal mupirocin and chlorhexidine-impregnated cloths compared with placebo significantly reduced neonatal colonization with an S aureus strain concordant with a parental baseline strain. However, further research is needed to replicate these findings and to assess their generalizability.

Trial Registration: ClinicalTrials.gov Identifier: NCT02223520.
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http://dx.doi.org/10.1001/jama.2019.20785DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6990934PMC
January 2020

Prediction of Disposition Within 48 Hours of Hospital Admission Using Patient Mobility Scores.

J Hosp Med 2020 09;15(9):540-543

Department of Physical Medicine and Rehabilitation, Johns Hopkins University, Baltimore, Maryland.

Delayed hospital discharges for patients needing rehabilitation in a postacute setting can exacerbate hospital-acquired mobility loss, prolong functional recovery, and increase costs. Systematic measurement of patient mobility by nurses early during hospitalization has the potential to help identify which patients are likely to be discharged to a postacute care facility versus home. To test the predictive ability of this approach, a machine learning classification tree method was applied retrospectively to a diverse sample of hospitalized patients (N = 761) using training and validation sets. Compared with patients discharged to home, patients discharged to a postacute facility were older (median, 64 vs 56 years old) and had lower mobility scores at hospital admission (median, 32 vs 41). The final decision tree accurately classified the discharge location for 73% (95% CI, 67%-78%) of patients. This study emphasizes the value of systematically measuring mobility in the hospital and provides a simple decision tree to facilitate early discharge planning.
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http://dx.doi.org/10.12788/jhm.3332DOI Listing
September 2020

Return to work after critical illness: a systematic review and meta-analysis.

Thorax 2020 01 8;75(1):17-27. Epub 2019 Nov 8.

Center for Humanizing Critical Care, Intermountain Health Care, Murray, Utah, USA.

Background: Survivors of critical illness often experience poor outcomes after hospitalisation, including delayed return to work, which carries substantial economic consequences.

Objective: To conduct a systematic review and meta-analysis of return to work after critical illness.

Methods: We searched PubMed, Embase, PsycINFO, CINAHL and Cochrane Library from 1970 to February 2018. Data were extracted, in duplicate, and random-effects meta-regression used to obtain pooled estimates.

Results: Fifty-two studies evaluated return to work in 10 015 previously employed survivors of critical illness, over a median (IQR) follow-up of 12 (6.25-38.5) months. By 1-3, 12 and 42-60 months' follow-up, pooled return to work prevalence (95% CI) was 36% (23% to 49%), 60% (50% to 69%) and 68% (51% to 85%), respectively ( =0.55, I=87%, p=0.03). No significant difference was observed based on diagnosis (acute respiratory distress syndrome (ARDS) vs non-ARDS) or region (Europe vs North America vs Australia/New Zealand), but was observed when comparing mode of employment evaluation (in-person vs telephone vs mail). Following return to work, 20%-36% of survivors experienced job loss, 17%-66% occupation change and 5%-84% worsening employment status (eg, fewer work hours). Potential risk factors for delayed return to work include pre-existing comorbidities and post-hospital impairments (eg, mental health).

Conclusion: Approximately two-thirds, two-fifths and one-third of previously employed intensive care unit survivors are jobless up to 3, 12 and 60 months following hospital discharge. Survivors returning to work often experience job loss, occupation change or worse employment status. Interventions should be designed and evaluated to reduce the burden of this common and important problem for survivors of critical illness.

Trial Registration Number: PROSPERO CRD42018093135.
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http://dx.doi.org/10.1136/thoraxjnl-2019-213803DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7418481PMC
January 2020

Practices, Perceptions, and Attitudes in the Evaluation of Critically Ill Children for Bacteremia: A National Survey.

Pediatr Crit Care Med 2020 01;21(1):e23-e29

Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD.

Objectives: Sending blood cultures in children at low risk of bacteremia can contribute to a cascade of unnecessary antibiotic exposure, adverse effects, and increased costs. We aimed to describe practice variation, clinician beliefs, and attitudes about blood culture testing in critically ill children.

Design: Cross-sectional electronic survey.

Setting: Fifteen PICUs enrolled in the Blood Culture Improvement Guidelines and Diagnostic Stewardship for Antibiotic Reduction in Critically Ill Children collaborative, an investigation of blood culture use in critically ill children in the United States.

Subjects: PICU clinicians (bedside nurses, resident physicians, fellow physicians, nurse practitioners, physician assistants, and attending physicians).

Interventions: None.

Measurement And Main Results: Survey items explored typical blood culture practices, attitudes and beliefs about cultures, and potential barriers to changing culture use in a PICU setting. Fifteen of 15 sites participated, with 347 total responses, 15-45 responses per site, and an overall median response rate of 57%. We summarized median proportions and interquartile ranges of respondents who reported certain practices or beliefs: 86% (73-91%) report that cultures are ordered reflexively; 71% (61-77%) do not examine patients before ordering cultures; 90% (86-94%) obtain cultures for any new fever in PICU patients; 33% (19-61%) do not obtain peripheral cultures when an indwelling catheter is in place; and 64% (36-81%) sample multiple (vs single) lumens of central venous catheters for new fever. When asked about barriers to reducing unnecessary cultures, 80% (73-90%) noted fear of missing sepsis. Certain practices (culture source and indication) varied by clinician type. Obtaining surveillance cultures and routinely culturing all possible sources (each lumen of indwelling catheters and peripheral specimens) are positively correlated with baseline blood culture rates.

Conclusions: There is variation in blood culture practices in the PICU. Fear and reflexive habits are common drivers of cultures. These practices may contribute to over-testing for bacteremia. Further investigation of how to optimize blood culture use is warranted.
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http://dx.doi.org/10.1097/PCC.0000000000002176DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6942229PMC
January 2020
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