Dysphagia Is an Underrecognized Risk Factor for Viral Pneumonia Severity.

The aim of this study was to examine the role of pre-existing dysphagia as a risk factor for COVID-19 severity among adults ≥50 years of age presenting to the emergency department (ED). This was a retrospective cohort study that used electronic health record data from two Midwestern EDs in the same health care system. The sample included patients ≥50 years of age who tested positive for SARS-COV-2 during an ED visit between March 15, 2020 and November 19, 2020. Patients were dichotomized based on documented history of dysphagia. The primary outcome was the highest World Health Organization COVID-19 clinical severity score within 30-days of ED arrival. Patients with a score of <4 were classified as non-severe whereas a score ≥4 was considered severe. Chi-square tests were used to assess differences in clinical severity scores between patients with and without dysphagia. A logistic regression model was created to estimate the odds of a severe COVID-19 clinical score. The sample included 126 patients without dysphagia and 40 patients with dysphagia. Patients with a history of dysphagia were more likely to develop severe COVID-19 disease compared to patients without (65.0% vs. 41.3%, p = 0.015). In multivariable analysis, patients with preexisting dysphagia (OR 2.38, 95% CI: 1.05-5.42; p = 0.038) and diabetes (OR 2.42 95% CI: 1.15-5.30; p = 0.021) had significantly increased odds of developing severe COVID-19. This study showed that a pre-existing diagnosis of dysphagia was independently associated with COVID-19 severity in adults ≥50 years of age.

Risk Factors for Dysphagia in Patients Hospitalized with COVID-19.

Patients hospitalized with COVID-19 may be at risk for dysphagia and vulnerable to associated consequences. We investigated predictors for dysphagia and its severity in a cohort of patients hospitalized with COVID-19 at a single hospital center. A large level I trauma center database was queried for all patients hospitalized with COVID-19. Demographics, medical information associated with COVID-19, specific to dysphagia, and interventions were collected. 947 patients with confirmed COVID-19 met the criteria. 118 (12%) were seen for a swallow evaluation. Individuals referred for evaluation were significantly older, had a lower BMI, more severe COVID-19, and higher rates of intubation, pneumonia, mechanical ventilation, tracheostomy placements, prone positioning, and ARDS. Pneumonia (OR 3.57, p = 0.004), ARDS (OR 3.57, p = 0.029), prone positioning (OR 3.99, p = 0.036), ventilation (OR 4.01, p = 0.006), and intubation (OR 4.75, p = 0.007) were significant risk factors for dysphagia. Older patients were more likely to have more severe dysphagia such that for every 1-year increase in age, the odds of severe dysphagia were 1.04 times greater (OR 1.04, p = 0.028). Patients hospitalized with COVID-19 are at risk for dysphagia. We show predictive variables that should be considered when referring COVID-19 patients for dysphagia services to reduce time to intervention/evaluation.

Satisfaction of Older Patients With Emergency Department Care: Psychometric Properties and Construct Validity of the Consumer Emergency Care Satisfaction Scale.

BACKGROUND: Patient satisfaction is an important indicator of quality of care, but its measurement remains challenging. The Consumer Emergency Care Satisfaction Scale (CECSS) was developed to measure patient satisfaction in the emergency department (ED). Although this is a valid and reliable tool, several aspects of the CECSS need to be improved, including the definition, dimension, and scoring of scales. PURPOSE: The purpose of this study was to examine the construct validity of the CECSS and make suggestions on how to improve the tool to measure overall satisfaction with ED care. METHODS: We administered 2 surveys to older adults who presented with a fall to the ED and used electronic health record data to examine construct validity of the CECSS and ceiling effects. RESULTS: Using several criteria, we improved construct validity of the CECSS, reduced ceiling effects, and standardized scoring. CONCLUSION: We addressed several methodological issues with the CECSS and provided recommendations for improvement.

Uncertainty as a critical determinant of antibiotic prescribing in patients with an asthma exacerbation: a qualitative study.

OBJECTIVE: To identify factors that influence providers' decisions to prescribe antibiotics in patients presenting to the hospital with an asthma exacerbation. METHODS: We performed semi-structured interviews with a purposive sample of providers including sixteen hospitalists, emergency room providers, or pulmonologists, and one focus group with internal medicine residents recruited from one large, urban, teaching hospital and one small, rural, community hospital. Questions were informed by the Theoretical Domains Framework to determine factors that may influence behaviors. Directed content analysis was used to code and analyze transcripts of the interviews. RESULTS: Uncertainty regarding the diagnostic (asthma vs. COPD) and the cause of exacerbation (bacterial vs. viral infection) emerged as the main driver for prescribing behavior. Provider response to uncertainty included: "watchful waiting" or immediate antibiotic prescribing. The following factors played important roles in providers' prescribing decision: 1) awareness/agreement with existing guidelines 2) confidence in their ability to apply the guidelines in challenging cases; 3) perceived risk of patient deterioration without antibiotics; 4) fear of litigation; 5) habit and clinical inertia 6) prescribing within the group 7) lack of information of antibiotic prescribing rates and 8) lack of time and/or resources. CONCLUSIONS: We identified diagnostic uncertainty as the primary determinant of antibiotic prescribing in asthma exacerbations and developed a conceptual model to explain provider responses and factors that influenced their responses. These results enhance our understanding of the factors that can contribute to low-value and wasteful practices like superfluous antibiotic prescribing and will support the development of interventions to de-implement such practices.

Older Adult Patients and Care Partners as Knowledge Brokers in Fragmented Health Care.

OBJECTIVE: To describe older adult patients' and care partners' knowledge broker roles during emergency department (ED) visits. BACKGROUND: Older adult patients are vulnerable to communication and coordination challenges during an ED visit, which can be exacerbated by the time and resource constrained ED environment. Yet, as a constant throughout the patient journey, patients and care partners can act as an information conduit, or knowledge broker, between fragmented care systems to attain high-quality, safe care. METHODS: Participants included 14 older adult patients (≥ 65 years old) and their care partners (e.g., spouse, adult child) who presented to the ED after having experienced a fall. Human factors researchers collected observation data from patients, care partners and clinician interactions during the patient's ED visit. We used an inductive content analysis to determine the role of patients and care partners as knowledge brokers. RESULTS: We found that patients and care partners act as knowledge brokers by providing information about diagnostic testing, medications, the patient's health history, and care accommodations at the disposition location. Patients and care partners filled the role of knowledge broker proactively (i.e. offer information) and reactively (i.e. are asked to provide information by clinicians or staff), within-ED work system and across work systems (e.g., between the ED and hospital), and in anticipation of future knowledge brokering. CONCLUSION: Patients and care partners, acting as knowledge brokers, often fill gaps in communication and participate in care coordination that assists in mitigating health care fragmentation.

Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits.

BACKGROUND: Machine learning is increasingly used for risk stratification in health care. Achieving accurate predictive models do not improve outcomes if they cannot be translated into efficacious intervention. Here we examine the potential utility of automated risk stratification and referral intervention to screen older adults for fall risk after emergency department (ED) visits. OBJECTIVE: This study evaluated several machine learning methodologies for the creation of a risk stratification algorithm using electronic health record data and estimated the effects of a resultant intervention based on algorithm performance in test data. METHODS: Data available at the time of ED discharge were retrospectively collected and separated into training and test datasets. Algorithms were developed to predict the outcome of a return visit for fall within 6 months of an ED index visit. Models included random forests, AdaBoost, and regression-based methods. We evaluated models both by the area under the receiver operating characteristic (ROC) curve, also referred to as area under the curve (AUC), and by projected clinical impact, estimating number needed to treat (NNT) and referrals per week for a fall risk intervention. RESULTS: The random forest model achieved an AUC of 0.78, with slightly lower performance in regression-based models. Algorithms with similar performance, when evaluated by AUC, differed when placed into a clinical context with the defined task of estimated NNT in a real-world scenario. CONCLUSION: The ability to translate the results of our analysis to the potential tradeoff between referral numbers and NNT offers decisionmakers the ability to envision the effects of a proposed intervention before implementation.

Scope and Influence of Electronic Health Record-Integrated Clinical Decision Support in the Emergency Department: A Systematic Review.

STUDY OBJECTIVE: As electronic health records evolve, integration of computerized clinical decision support offers the promise of sorting, collecting, and presenting this information to improve patient care. We conducted a systematic review to examine the scope and influence of electronic health record-integrated clinical decision support technologies implemented in the emergency department (ED). METHODS: A literature search was conducted in 4 databases from their inception through January 18, 2018: PubMed, Scopus, the Cumulative Index of Nursing and Allied Health, and Cochrane Central. Studies were included if they examined the effect of a decision support intervention that was implemented in a comprehensive electronic health record in the ED setting. Standardized data collection forms were developed and used to abstract study information and assess risk of bias. RESULTS: A total of 2,558 potential studies were identified after removal of duplicates. Of these, 42 met inclusion criteria. Common targets for clinical decision support intervention included medication and radiology ordering practices, as well as more comprehensive systems supporting diagnosis and treatment for specific disease entities. The majority of studies (83%) reported positive effects on outcomes studied. Most studies (76%) used a pre-post experimental design, with only 3 (7%) randomized controlled trials. CONCLUSION: Numerous studies suggest that clinical decision support interventions are effective in changing physician practice with respect to process outcomes such as guideline adherence; however, many studies are small and poorly controlled. Future studies should consider the inclusion of more specific information in regard to design choices, attempt to improve on uncontrolled before-after designs, and focus on clinically relevant outcomes wherever possible.

Effectiveness of Outpatient Antibiotics After Surgical Drainage of Abscesses in Reducing Treatment Failure.

BACKGROUND: The optimal approach to outpatient antibiotic use after surgical drainage of abscesses is unclear given conflicting clinical trial results. OBJECTIVE: Our primary objective was to evaluate the real-world effectiveness of outpatient antibiotic prescribing after surgical drainage of cutaneous abscesses on reducing treatment failure. METHODS: We performed a retrospective observational study using data extracted from the electronic health record of a single academic health care system. All emergency department (ED) visits that resulted in discharge with a surgical drainage of a cutaneous abscess procedure code were included in the sample. All visits were categorized into having received or not having received an antibiotic prescription at the index visit. Outcome frequencies were compared using Pearson's chi-squared test. A multivariable logistic regression model was used to estimate the odds of treatment failure among those who did and did not receive an antibiotic prescription at their index ED visit. RESULTS: The final sample consisted of 421 index ED visits, of which 303 (72%) received an antibiotic prescription. Treatment with antibiotics after drainage did not significantly reduce the odds of composite treatment failure within 30 days when controlling for sociodemographic and clinical encounter variables (odds ratio 0.52, 95% confidence interval 0.23-1.21). CONCLUSIONS: This real-world, comparative effectiveness analysis did not demonstrate any significant reduction in treatment failure with the use of antibiotics after drainage of abscesses in the ED. It is unclear if the clinical benefit observed under controlled trial conditions will carry over to routine clinical practice where varied antibiotic regimens are the norm and local bacterial resistance patterns vary.

Negative D-dimer testing excludes pulmonary embolism in non-high risk patients in the emergency department.

PURPOSE: The purpose of this study was to assess the ability of d-dimer testing to obviate the need for cross-sectional imaging for patients at "non-high risk" for pulmonary embolism (PE). METHODS: This is a retrospective study of emergency department patients at an academic medical center who underwent cross-sectional imaging (MRA or CTA) to evaluate for PE from 2008 to 2013. The primary outcome was the NPV of d-dimer testing when used in conjunction with clinical decision instruments (CDIs = Wells', Revised Geneva, and Simplified Revised Geneva Scores). The reference standard for PE status included image test results and a 6-month chart review follow-up for venous thromboembolism as a proxy for false negative imaging. Secondary analyses included ROC curves for each CDI and calculation of PE prevalence in each risk stratum. RESULTS: Of 459 patients, 41 (8.9%) had PE. None of the 76 patients (16.6%) with negative d-dimer results had PE. Thus, d-dimer testing had 100% sensitivity and NPV, and there were no differences in CDI performance. Similarly, when evaluated independently of d-dimer results, no CDI outperformed the others (areas under the ROC curves ranged 0.53-0.55). There was a significantly higher PE prevalence in the high versus "non-high risk" groups when stratified by the Wells' Score (p = 0.03). CONCLUSIONS: Negative d-dimer testing excluded PE in our retrospective cohort. Each CDI had similar NPVs, whether analyzed in conjunction with or independently of d-dimer results. Our results confirm that PE can be safely excluded in patients with "non-high risk" CDI scores and a negative d-dimer.

Optimizing Antimicrobial Stewardship in the Emergency Department.

Antibiotic stewardship is a core component of emergency department (ED) practice and impacts patient safety, clinical outcomes, and public health. The unique characteristics of ED practice, including crowding, time pressure, and diagnostic uncertainty, need to be considered when implementing antibiotic stewardship interventions in this setting. Rapid advances in pathogen detection and host response biomarkers promise to revolutionize the diagnosis of infectious diseases in the ED, but such tests are not yet considered standard of care. Presently, clinical decision support embedded in the electronic health record and pharmacist-led interventions are the most effective ways to improve antibiotic prescribing in the ED.

A scoping review of bacterial resistance among inpatients amidst the COVID-19 pandemic.

OBJECTIVES: The COVID-19 pandemic disrupted antimicrobial stewardship and infection prevention operations worldwide, raising concerns for an acceleration of antimicrobial resistance (AMR). Therefore, we aimed to define the scope of peer reviewed research comparing AMR in inpatient bacterial clinical cultures before and after the start of the COVID-19 pandemic. METHODS: We conducted a scoping review and searched PubMed, Scopus, and Web of Science through 15 June 2023. Our inclusion criteria were: (1) English language, (2) primary evidence, (3) peer-reviewed, (4) clinical culture data from humans, (5) AMR data for at least one bacterial order/species, (6) inpatient setting, (7) use of statistical testing to evaluate AMR data before and during the COVID-19 pandemic. Reviewers extracted country, study design, type of analysis, study period, setting and population, number of positive cultures or isolates, culture type(s), method of AMR analysis, organisms, and AMR results. Study results were organised by organism and antibiotic class or resistance mechanism. AMR results are also summarised by individual study and across all studies. RESULTS: In total, 4805 articles were identified with 55 papers meeting inclusion criteria. Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Staphylococcus aureus were the most commonly studied organisms. There were 464 bacterial AMR results across all studies with 82 (18%) increase, 71 (15%) decrease, and 311 (67%) no change results. CONCLUSIONS: The literature examining the impact of COVID-19 on AMR among inpatients is diverse with most results reflecting no change pre/post pandemic. Ongoing inquiry is needed into evolving patterns in AMR post COVID-19.

Validation of Thermal Imaging and the ALT-70 Prediction Model to Differentiate Cellulitis From Pseudocellulitis.

Importance: Cellulitis is misdiagnosed in up to 30% of cases due to mimic conditions termed pseudocellulitis. The resulting overuse of antibiotics is a threat to patient safety and public health. Surface thermal imaging and the ALT-70 (asymmetry, leukocytosis, tachycardia, and age ≥70 years) prediction model have been proposed as tools to help differentiate cellulitis from pseudocellulitis. Objectives: To validate differences in skin surface temperatures between patients with cellulitis and patients with pseudocellulitis, assess the optimal temperature measure and cut point for differentiating cellulitis from pseudocellulitis, and compare the performance of skin surface temperature and the ALT-70 prediction model in differentiating cellulitis from pseudocellulitis. Design, Setting, and Participants: This prospective diagnostic validation study was conducted among patients who presented to the emergency department with acute dermatologic lower extremity symptoms from October 11, 2018, through March 11, 2020. Statistical analysis was performed from July 2020 to March 2021 with additional work conducted in September 2023. Main Outcomes and Measures: Temperature measures for affected and unaffected skin were obtained. Cellulitis vs pseudocellulitis was assessed by a 6-physician, independent consensus review. Differences in temperature measures were compared using the t test. Logistic regression was used to identify the temperature measure and associated cut point with the optimal performance for discriminating between cellulitis and pseudocellulitis. Diagnostic performance characteristics for the ALT-70 prediction model, surface skin temperature, and both combined were also assessed. Results: The final sample included 204 participants (mean [SD] age, 56.6 [16.5] years; 121 men [59.3%]), 92 (45.1%) of whom had a consensus diagnosis of cellulitis. There were statistically significant differences in all skin surface temperature measures (mean temperature, maximum temperature, and gradients) between cellulitis and pseudocellulitis. The maximum temperature of the affected limb for patients with cellulitis was 33.2 °C compared with 31.2 °C for those with pseudocellulitis (difference, 2.0 °C [95% CI, 1.3-2.7 °C]; P < .001). The maximum temperature was the optimal temperature measure with a cut point of 31.2 °C in the affected skin, yielding a mean (SD) negative predictive value of 93.5% (4.7%) and a sensitivity of 96.8% (2.3%). The sensitivity of all 3 measures remained above 90%, while specificity varied considerably (ALT-70, 22.0% [95% CI, 15.8%-28.1%]; maximum temperature of the affected limb, 38.4% [95% CI, 31.7%-45.1%]; combination measure, 53.9% [95% CI, 46.5%-61.2%]). Conclusions and Relevance: In this large diagnostic validation study, significant differences in skin surface temperature measures were observed between cases of cellulitis and cases of pseudocellulitis. Thermal imaging and the ALT-70 both demonstrated high sensitivity, but specificity was improved by combining the 2 measures. These findings support the potential of thermal imaging, alone or in combination with the ALT-70 prediction model, as a diagnostic adjunct that may reduce overdiagnosis of cellulitis.

Inappropriate Diagnosis of Pneumonia Among Hospitalized Adults.

Importance: Little is known about incidence of, risk factors for, and harms associated with inappropriate diagnosis of community-acquired pneumonia (CAP). Objective: To characterize inappropriate diagnosis of CAP in hospitalized patients. Design, Setting, and Participants: This prospective cohort study, including medical record review and patient telephone calls, took place across 48 Michigan hospitals. Trained abstractors retrospectively assessed hospitalized patients treated for CAP between July 1, 2017, and March 31, 2020. Patients were eligible for inclusion if they were adults admitted to general care with a discharge diagnostic code of pneumonia who received antibiotics on day 1 or 2 of hospitalization. Data were analyzed from February to December 2023. Main Outcomes and Measures: Inappropriate diagnosis of CAP was defined using a National Quality Forum-endorsed metric as CAP-directed antibiotic therapy in patients with fewer than 2 signs or symptoms of CAP or negative chest imaging. Risk factors for inappropriate diagnosis were assessed and, for those inappropriately diagnosed, 30-day composite outcomes (mortality, readmission, emergency department visit, Clostridioides difficile infection, and antibiotic-associated adverse events) were documented and stratified by full course (>3 days) vs brief (≤3 days) antibiotic treatment using generalized estimating equation models adjusting for confounders and propensity for treatment. Results: Of the 17 290 hospitalized patients treated for CAP, 2079 (12.0%) met criteria for inappropriate diagnosis (median [IQR] age, 71.8 [60.1-82.8] years; 1045 [50.3%] female), of whom 1821 (87.6%) received full antibiotic courses. Compared with patients with CAP, patients inappropriately diagnosed were older (adjusted odds ratio [AOR], 1.08; 95% CI, 1.05-1.11 per decade) and more likely to have dementia (AOR, 1.79; 95% CI, 1.55-2.08) or altered mental status on presentation (AOR, 1.75; 95% CI, 1.39-2.19). Among those inappropriately diagnosed, 30-day composite outcomes for full vs brief treatment did not differ (25.8% vs 25.6%; AOR, 0.98; 95% CI, 0.79-1.23). Full vs brief duration of antibiotic treatment among patients was associated with antibiotic-associated adverse events (31 of 1821 [2.1%] vs 1 of 258 [0.4%]; P = .03). Conclusions and Relevance: In this cohort study, inappropriate diagnosis of CAP among hospitalized adults was common, particularly among older adults, those with dementia, and those presenting with altered mental status. Full-course antibiotic treatment of those inappropriately diagnosed with CAP may be harmful.

Diagnostic testing and antibiotic utilization among inpatients evaluated for coronavirus disease 2019 (COVID-19) pneumonia.

We evaluated diagnostic test and antibiotic utilization among 252 patients from 11 US hospitals who were evaluated for coronavirus disease 2019 (COVID-19) pneumonia during the severe acute respiratory coronavirus virus 2 (SARS-CoV-2) omicron variant pandemic wave. In our cohort, antibiotic use remained high (62%) among SARS-CoV-2-positive patients and even higher among those who underwent procalcitonin testing (68%).

Multisite evaluation of prediction models for emergency department crowding before and during the COVID-19 pandemic.

OBJECTIVE: To develop a machine learning framework to forecast emergency department (ED) crowding and to evaluate model performance under spatial and temporal data drift. MATERIALS AND METHODS: We obtained 4 datasets, identified by the location: 1-large academic hospital and 2-rural hospital, and time period: pre-coronavirus disease (COVID) (January 1, 2019-February 1, 2020) and COVID-era (May 15, 2020-February 1, 2021). Our primary target was a binary outcome that is equal to 1 if the number of patients with acute respiratory illness that were ED boarding for more than 4 h was above a prescribed historical percentile. We trained a random forest and used the area under the curve (AUC) to evaluate out-of-sample performance for 2 experiments: (1) we evaluated the impact of sudden temporal drift by training models using pre-COVID data and testing them during the COVID-era, (2) we evaluated the impact of spatial drift by testing models trained at location 1 on data from location 2, and vice versa. RESULTS: The baseline AUC values for ED boarding ranged from 0.54 (pre-COVID at location 2) to 0.81 (COVID-era at location 1). Models trained with pre-COVID data performed similarly to COVID-era models (0.82 vs 0.78 at location 1). Models that were transferred from location 2 to location 1 performed worse than models trained at location 1 (0.51 vs 0.78). DISCUSSION AND CONCLUSION: Our results demonstrate that ED boarding is a predictable metric for ED crowding, models were not significantly impacted by temporal data drift, and any attempts at implementation must consider spatial data drift.

Patient-centered care outcomes for patients in the emergency department with a non-English language preference: A scoping review.

OBJECTIVE: This review highlights what is known about patient-centered care outcomes (PCCOs) for emergency department (ED) patients with non-English language preferences (NELP). METHODS: Four databases were searched and included article were written in English, presented primary evidence, published in a peer-reviewed journal, and reported PCCOs from the perspective of ED patients with NELP. PCCOs were defined using the Institute of Medicine definition, outcomes that evaluate respect and responsiveness to patient preferences, needs and values. Two reviewers assessed all articles, extracted data, and resolved discrepancies. PCCOs were grouped in categories (needs, preferences, and values) based on the definition's domains. RESULTS: Of the 6524 potentially eligible studies, 20 met inclusion criteria. Of these, 16 focused on needs; 4 on preferences and 8 on values. Within patient need, five studies found a large unmet need for language services. Within patient value, three found that language discordance negatively influenced perceptions of care. CONCLUSIONS: Most studies in this review found that not speaking English negatively influenced perceptions of care and highlighted a large unmet need for language services in the ED. PRACTICE IMPLICATIONS: More work needs to be done to characterize PCCOs in ED patients with NELP and develop interventions to improve care.

Lopinavir/ritonavir for treatment of non-hospitalized patients with COVID-19: a randomized clinical trial.

OBJECTIVES: Effective and widely available therapies are still needed for outpatients with COVID-19. We aimed to evaluate the efficacy and safety of lopinavir/ritonavir (LPV/r) for early treatment of non-hospitalized individuals diagnosed with COVID-19. METHODS: This randomized, placebo (Plb)-controlled, double-blind, multi-site decentralized clinical trial enrolled non-hospitalized adults with confirmed SARS-CoV-2 infection and six or fewer days of acute respiratory infection symptoms who were randomized to either twice-daily oral LPV/r (400 mg/100 mg) or Plb for 14 days. Daily surveys on study days 1 through 16 and again on study day 28 evaluated symptoms, daily activities, and hospitalization status. The primary outcome was longitudinal change in an ordinal scale based on a combination of symptoms, activity, and hospitalization status through day 15 and was analyzed by use of a Bayesian longitudinal proportional odds logistic regression model for estimating the probability of a superior recovery for LPV/r over Plb (odds ratio >1). RESULTS: Between June 2020 and December 2021, 448 participants were randomized to receive either LPV/r (n = 216) or Plb (n = 221). The mean symptom duration before randomization was 4.3 days (SD 1.3). There were no differences between treatment groups through the first 15 days for the ordinal primary outcome (odds ratio 0.96; 95% credible interval: 0.66 to 1.41). There were 3.2% (n = 7) of LPV/r and 2.7% (n = 6) of Plb participants hospitalized by day 28. Serious adverse events did not differ between groups. CONCLUSION: LPV/r did not significantly improve symptom resolution or reduce hospitalization in non-hospitalized participants with COVID-19. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04372628.