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Byrd TF, Phelan TA, Ingraham NE, Langworthy BW, Bhasin A, Kc A, Melton-Meaux GB, Tignanelli CJ. Beyond Unplanned ICU Transfers: Linking a Revised Definition of Deterioration to Patient Outcomes. Crit Care Med 2024:00003246-990000000-00339. [PMID: 38832836 DOI: 10.1097/ccm.0000000000006333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
OBJECTIVES To develop an electronic descriptor of clinical deterioration for hospitalized patients that predicts short-term mortality and identifies patient deterioration earlier than current standard definitions. DESIGN A retrospective study using exploratory record review, quantitative analysis, and regression analyses. SETTING Twelve-hospital community-academic health system. PATIENTS All adult patients with an acute hospital encounter between January 1, 2018, and December 31, 2022. INTERVENTIONS Not applicable. MEASUREMENTS AND MAIN RESULTS Clinical trigger events were selected and used to create a revised electronic definition of deterioration, encompassing signals of respiratory failure, bleeding, and hypotension occurring in proximity to ICU transfer. Patients meeting the revised definition were 12.5 times more likely to die within 7 days (adjusted odds ratio 12.5; 95% CI, 8.9-17.4) and had a 95.3% longer length of stay (95% CI, 88.6-102.3%) compared with those who were transferred to the ICU or died regardless of meeting the revised definition. Among the 1812 patients who met the revised definition of deterioration before ICU transfer (52.4%), the median detection time was 157.0 min earlier (interquartile range 64.0-363.5 min). CONCLUSIONS The revised definition of deterioration establishes an electronic descriptor of clinical deterioration that is strongly associated with short-term mortality and length of stay and identifies deterioration over 2.5 hours earlier than ICU transfer. Incorporating the revised definition of deterioration into the training and validation of early warning system algorithms may enhance their timeliness and clinical accuracy.
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Sangji NF, Dougherty JM, Tignanelli CJ, Maqsood HA, Cain-Nielsen AH, Oliphant BW, Hemmila MR. Calculation and Feedback of Risk-Adjusted Antibiotic Days as a Process Measure in a Statewide Trauma Collaborative. Am Surg 2024:31348241256070. [PMID: 38770751 DOI: 10.1177/00031348241256070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
BACKGROUND Optimization of antibiotic stewardship requires determining appropriate antibiotic treatment and duration of use. Our current method of identifying infectious complications alone does not attempt to measure the resources actually utilized to treat infections in patients. We sought to develop a method accounting for treatment of infections and length of antibiotic administration to allow benchmarking of trauma hospitals with regard to days of antibiotic use. METHODS Using trauma quality collaborative data from 35 American College of Surgeons (ACS)-verified level I and level II trauma centers between November 1, 2020, and January 31, 2023, a two-part model was created to account for (1) the odds of any antibiotic use, using logistic regression; and (2) the duration of usage, using negative binomial distribution. We adjusted for injury severity, presence/type of infection (eg, ventilator-acquired pneumonia), infectious complications, and comorbid conditions. We performed observed-to-expected adjustments to calculate each center's risk-adjusted antibiotic days, bootstrapped Observed/Expected (O/E) ratios to create confidence intervals, and flagged potential high or low outliers as hospitals whose confidence intervals lay above or below the overall mean. RESULTS The mean antibiotic treatment days was 1.98°days with a total of 88,403 treatment days. A wide variation existed in risk-adjusted antibiotic treatment days (.76°days to 2.69°days). Several hospitals were identified as low (9 centers) or high (6 centers) outliers. CONCLUSION There exists a wide variation in the duration of risk-adjusted antibiotic use amongst trauma centers. Further study is needed to address the underlying cause of variation and for improved antibiotic stewardship.
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Morris R, Al Tannir AH, Chipman J, Charles A, Ingraham NE, Kalinoski M, Bolden L, Siegel L, Tignanelli CJ. Deriving a definition of chronic critical illness: ICU stay of 10 days. Am J Surg 2024:S0002-9610(24)00276-9. [PMID: 38782686 DOI: 10.1016/j.amjsurg.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 04/29/2024] [Accepted: 05/17/2024] [Indexed: 05/25/2024]
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Biesboer EA, Pokrzywa CJ, Karam BS, Chen B, Szabo A, Teng BQ, Bernard MD, Bernard A, Chowdhury S, Hayudini AHE, Radomski MA, Doris S, Yorkgitis BK, Mull J, Weston BW, Hemmila MR, Tignanelli CJ, de Moya MA, Morris RS. Prospective validation of a hospital triage predictive model to decrease undertriage: an EAST multicenter study. Trauma Surg Acute Care Open 2024; 9:e001280. [PMID: 38737811 PMCID: PMC11086287 DOI: 10.1136/tsaco-2023-001280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 03/23/2024] [Indexed: 05/14/2024] Open
Abstract
Background Tiered trauma team activation (TTA) allows systems to optimally allocate resources to an injured patient. Target undertriage and overtriage rates of <5% and <35% are difficult for centers to achieve, and performance variability exists. The objective of this study was to optimize and externally validate a previously developed hospital trauma triage prediction model to predict the need for emergent intervention in 6 hours (NEI-6), an indicator of need for a full TTA. Methods The model was previously developed and internally validated using data from 31 US trauma centers. Data were collected prospectively at five sites using a mobile application which hosted the NEI-6 model. A weighted multiple logistic regression model was used to retrain and optimize the model using the original data set and a portion of data from one of the prospective sites. The remaining data from the five sites were designated for external validation. The area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC) were used to assess the validation cohort. Subanalyses were performed for age, race, and mechanism of injury. Results 14 421 patients were included in the training data set and 2476 patients in the external validation data set across five sites. On validation, the model had an overall undertriage rate of 9.1% and overtriage rate of 53.7%, with an AUROC of 0.80 and an AUPRC of 0.63. Blunt injury had an undertriage rate of 8.8%, whereas penetrating injury had 31.2%. For those aged ≥65, the undertriage rate was 8.4%, and for Black or African American patients the undertriage rate was 7.7%. Conclusion The optimized and externally validated NEI-6 model approaches the recommended undertriage and overtriage rates while significantly reducing variability of TTA across centers for blunt trauma patients. The model performs well for populations that traditionally have high rates of undertriage. Level of evidence 2.
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Bramante CT, Beckman KB, Mehta T, Karger AB, Odde DJ, Tignanelli CJ, Buse JB, Johnson DM, Watson RHB, Daniel JJ, Liebovitz DM, Nicklas JM, Cohen K, Puskarich MA, Belani HK, Siegel LK, Klatt NR, Anderson B, Hartman KM, Rao V, Hagen AA, Patel B, Fenno SL, Avula N, Reddy NV, Erickson SM, Fricton RD, Lee S, Griffiths G, Pullen MF, Thompson JL, Sherwood NE, Murray TA, Rose MR, Boulware DR, Huling JD. Favorable Antiviral Effect of Metformin on Severe Acute Respiratory Syndrome Coronavirus 2 Viral Load in a Randomized, Placebo-Controlled Clinical Trial of Coronavirus Disease 2019. Clin Infect Dis 2024:ciae159. [PMID: 38690892 DOI: 10.1093/cid/ciae159] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Indexed: 05/03/2024] Open
Abstract
BACKGROUND Metformin has antiviral activity against RNA viruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The mechanism appears to be suppression of protein translation via targeting the host mechanistic target of rapamycin pathway. In the COVID-OUT randomized trial for outpatient coronavirus disease 2019 (COVID-19), metformin reduced the odds of hospitalizations/death through 28 days by 58%, of emergency department visits/hospitalizations/death through 14 days by 42%, and of long COVID through 10 months by 42%. METHODS COVID-OUT was a 2 × 3 randomized, placebo-controlled, double-blind trial that assessed metformin, fluvoxamine, and ivermectin; 999 participants self-collected anterior nasal swabs on day 1 (n = 945), day 5 (n = 871), and day 10 (n = 775). Viral load was quantified using reverse-transcription quantitative polymerase chain reaction. RESULTS The mean SARS-CoV-2 viral load was reduced 3.6-fold with metformin relative to placebo (-0.56 log10 copies/mL; 95% confidence interval [CI], -1.05 to -.06; P = .027). Those who received metformin were less likely to have a detectable viral load than placebo at day 5 or day 10 (odds ratio [OR], 0.72; 95% CI, .55 to .94). Viral rebound, defined as a higher viral load at day 10 than day 5, was less frequent with metformin (3.28%) than placebo (5.95%; OR, 0.68; 95% CI, .36 to 1.29). The metformin effect was consistent across subgroups and increased over time. Neither ivermectin nor fluvoxamine showed effect over placebo. CONCLUSIONS In this randomized, placebo-controlled trial of outpatient treatment of SARS-CoV-2, metformin significantly reduced SARS-CoV-2 viral load, which may explain the clinical benefits in this trial. Metformin is pleiotropic with other actions that are relevant to COVID-19 pathophysiology. CLINICAL TRIALS REGISTRATION NCT04510194.
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An SJ, Smith C, Davis D, Gallaher J, Tignanelli CJ, Charles A. Predictors of Functional Decline Among Critically Ill Surgical Patients: A National Analysis. J Surg Res 2024; 296:209-216. [PMID: 38281356 DOI: 10.1016/j.jss.2023.12.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 12/07/2023] [Accepted: 12/29/2023] [Indexed: 01/30/2024]
Abstract
INTRODUCTION Functional decline is associated with critical illness, though this relationship in surgical patients is unclear. This study aims to characterize functional decline after intensive care unit (ICU) admission among surgical patients. METHODS We performed a retrospective analysis of surgical patients admitted to the ICU in the Cerner Acute Physiology and Chronic Health Evaluation database, which includes 236 hospitals, from 2007 to 2017. Patients with and without functional decline were compared. Predictors of decline were modeled. RESULTS A total of 52,838 patients were included; 19,310 (36.5%) experienced a functional decline. Median ages of the decline and nondecline groups were 69 (interquartile range 59-78) and 63 (interquartile range 52-72) years, respectively (P < 0.01). The nondecline group had a larger proportion of males (59.1% versus 55.3% in the decline group, P < 0.01). After controlling for sociodemographic covariates, comorbidities, and disease severity upon ICU admission, patients undergoing pulmonary (odds ratio [OR] 6.54, 95% confidence interval [CI] 2.67-16.02), musculoskeletal (OR 4.13, CI 3.51-4.87), neurological (OR 2.67, CI 2.39-2.98), gastrointestinal (OR 1.61, CI 1.38-1.88), and skin and soft tissue (OR 1.35, CI 1.08-1.68) compared to cardiovascular surgeries had increased odds of decline. CONCLUSIONS More than one in three critically ill surgical patients experienced a functional decline. Pulmonary, musculoskeletal, and neurological procedures conferred the greatest risk. Additional resources should be targeted toward the rehabilitation of these patients.
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King S, Proper J, Siegel LK, Ingraham NE, Tignanelli CJ, Chipman JG, Ho J. Acute Appendicitis Treatment Strategies and Mortality Based on Critical Illness on Admission: An Observational Study. Surg Infect (Larchmt) 2024; 25:56-62. [PMID: 38285892 PMCID: PMC10825276 DOI: 10.1089/sur.2023.249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024] Open
Abstract
Background: Trials have shown non-inferiority of non-operative management (NOM) for appendicitis, although critically ill patients have been often excluded. The purpose of this study is to evaluate surgical versus NOM outcomes in critically ill patients with appendicitis by measuring mortality and hospital length of stay (LOS). Patients and Methods: The Healthcare Cost and Utilization Project's (HCUP) Database was utilized to analyze data from 10 states between 2008 and 2015. All patients with acute appendicitis by International Classification of Diseases, Ninth Revision (ICD-9) codes over the age of 18 were included. Negative binomial and logistic regression were used to determine the association of acute renal failure (ARF), cardiovascular failure (CVF), pulmonary failure (PF), and sepsis by treatment strategy (laparoscopic, open, both, or no surgery) on mortality and hospital LOS. Results: Among 464,123 patients, 67.5%, 23.3%, 8.2%, and 0.8% underwent laparoscopic, open, NOM, or both laparoscopic and open surgery, respectively. Patients who underwent surgery had 58% lower odds of mortality and 34% shorter hospital LOS compared with NOM patients. Patients with ARF, CVF, PF, and sepsis had 102%, 383%, 475%, and 666% higher odds of mortality and a 47%, 46%, 71%, and 163% longer hospital LOS, respectively, compared with patients without these diagnoses on admission. Conclusions: Critical illness on admission increases mortality and hospital LOS. Patients who underwent laparoscopic, and to a lesser extent, open appendectomy had improved mortality compared with those who did not undergo surgery regardless of critical illness status.
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Silverman GM, Rajamani G, Ingraham NE, Glover JK, Sahoo HS, Usher M, Zhang R, Ikramuddin F, Melnik TE, Melton GB, Tignanelli CJ. A Symptom-Based Natural Language Processing Surveillance Pipeline for Post-COVID-19 Patients. Stud Health Technol Inform 2024; 310:860-864. [PMID: 38269931 DOI: 10.3233/shti231087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
Post-acute sequelae of SARS CoV-2 (PASC) are a group of conditions in which patients previously infected with COVID-19 experience symptoms weeks/months post-infection. PASC has substantial societal burden, including increased healthcare costs and disabilities. This study presents a natural language processing (NLP) based pipeline for identification of PASC symptoms and demonstrates its ability to estimate the proportion of suspected PASC cases. A manual case review to obtain this estimate indicated our sample incidence of PASC (13%) was representative of the estimated population proportion (95% CI: 19±6.22%). However, the high number of cases classified as indeterminate demonstrates the challenges in classifying PASC even among experienced clinicians. Lastly, this study developed a dashboard to display views of aggregated PASC symptoms and measured its utility using the System Usability Scale. Overall comments related to the dashboard's potential were positive. This pipeline is crucial for monitoring post-COVID-19 patients with potential for use in clinical settings.
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Loftus TJ, Balch JA, Marquard JL, Ray JM, Alper BS, Ojha N, Bihorac A, Melton-Meaux G, Khanna G, Tignanelli CJ. Longitudinal clinical decision support for assessing decisions over time: State-of-the-art and future directions. Digit Health 2024; 10:20552076241249925. [PMID: 38708184 PMCID: PMC11067677 DOI: 10.1177/20552076241249925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 04/10/2024] [Indexed: 05/07/2024] Open
Abstract
Objective Patients and clinicians rarely experience healthcare decisions as snapshots in time, but clinical decision support (CDS) systems often represent decisions as snapshots. This scoping review systematically maps challenges and facilitators to longitudinal CDS that are applied at two or more timepoints for the same decision made by the same patient or clinician. Methods We searched Embase, PubMed, and Medline databases for articles describing development, validation, or implementation of patient- or clinician-facing longitudinal CDS. Validated quality assessment tools were used for article selection. Challenges and facilitators to longitudinal CDS are reported according to PRISMA-ScR guidelines. Results Eight articles met inclusion criteria; each article described a unique CDS. None used entirely automated data entry, none used living guidelines for updating the evidence base or knowledge engine as new evidence emerged during the longitudinal study, and one included formal readiness for change assessments. Seven of eight CDS were implemented and evaluated prospectively. Challenges were primarily related to suboptimal study design (with unique challenges for each study) or user interface. Facilitators included use of randomized trial designs for prospective enrollment, increased CDS uptake during longitudinal exposure, and machine-learning applications that are tailored to the CDS use case. Conclusions Despite the intuitive advantages of representing healthcare decisions longitudinally, peer-reviewed literature on longitudinal CDS is sparse. Existing reports suggest opportunities to incorporate longitudinal CDS frameworks, automated data entry, living guidelines, and user readiness assessments. Generating best practice guidelines for longitudinal CDS would require a greater depth and breadth of published work and expert opinion.
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Castro-Pearson S, Samorodnitsky S, Yang K, Lotfi-Emran S, Ingraham NE, Bramante C, Jones EK, Greising S, Yu M, Steffen B, Svensson J, Åhlberg E, Österberg B, Wacker D, Guan W, Puskarich M, Smed-Sörensen A, Lusczek E, Safo SE, Tignanelli CJ. Development of a proteomic signature associated with severe disease for patients with COVID-19 using data from 5 multicenter, randomized, controlled, and prospective studies. Sci Rep 2023; 13:20315. [PMID: 37985892 PMCID: PMC10661735 DOI: 10.1038/s41598-023-46343-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 10/31/2023] [Indexed: 11/22/2023] Open
Abstract
Significant progress has been made in preventing severe COVID-19 disease through the development of vaccines. However, we still lack a validated baseline predictive biologic signature for the development of more severe disease in both outpatients and inpatients infected with SARS-CoV-2. The objective of this study was to develop and externally validate, via 5 international outpatient and inpatient trials and/or prospective cohort studies, a novel baseline proteomic signature, which predicts the development of moderate or severe (vs mild) disease in patients with COVID-19 from a proteomic analysis of 7000 + proteins. The secondary objective was exploratory, to identify (1) individual baseline protein levels and/or (2) protein level changes within the first 2 weeks of acute infection that are associated with the development of moderate/severe (vs mild) disease. For model development, samples collected from 2 randomized controlled trials were used. Plasma was isolated and the SomaLogic SomaScan platform was used to characterize protein levels for 7301 proteins of interest for all studies. We dichotomized 113 patients as having mild or moderate/severe COVID-19 disease. An elastic net approach was used to develop a predictive proteomic signature. For validation, we applied our signature to data from three independent prospective biomarker studies. We found 4110 proteins measured at baseline that significantly differed between patients with mild COVID-19 and those with moderate/severe COVID-19 after adjusting for multiple hypothesis testing. Baseline protein expression was associated with predicted disease severity with an error rate of 4.7% (AUC = 0.964). We also found that five proteins (Afamin, I-309, NKG2A, PRS57, LIPK) and patient age serve as a signature that separates patients with mild COVID-19 and patients with moderate/severe COVID-19 with an error rate of 1.77% (AUC = 0.9804). This panel was validated using data from 3 external studies with AUCs of 0.764 (Harvard University), 0.696 (University of Colorado), and 0.893 (Karolinska Institutet). In this study we developed and externally validated a baseline COVID-19 proteomic signature associated with disease severity for potential use in both outpatients and inpatients with COVID-19.
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Avula N, Kakach D, Tignanelli CJ, Liebovitz DM, Nicklas JM, Cohen K, Puskarich MA, Belani HK, Buse JB, Klatt NR, Anderson B, Karger AB, Hartman KM, Patel B, Fenno SL, Reddy NV, Erickson SM, Boulware DR, Murray TA, Bramante CT. Strategies used for the COVID-OUT decentralized trial of outpatient treatment of SARS-CoV-2. J Clin Transl Sci 2023; 7:e242. [PMID: 38033705 PMCID: PMC10685265 DOI: 10.1017/cts.2023.668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 09/20/2023] [Accepted: 10/24/2023] [Indexed: 12/02/2023] Open
Abstract
The COVID-19 pandemic accelerated the development of decentralized clinical trials (DCT). DCT's are an important and pragmatic method for assessing health outcomes yet comprise only a minority of clinical trials, and few published methodologies exist. In this report, we detail the operational components of COVID-OUT, a decentralized, multicenter, quadruple-blinded, randomized trial that rapidly delivered study drugs nation-wide. The trial examined three medications (metformin, ivermectin, and fluvoxamine) as outpatient treatment of SARS-CoV-2 for their effectiveness in preventing severe or long COVID-19. Decentralized strategies included HIPAA-compliant electronic screening and consenting, prepacking investigational product to accelerate delivery after randomization, and remotely confirming participant-reported outcomes. Of the 1417 individuals with the intention-to-treat sample, the remote nature of the study caused an additional 94 participants to not take any doses of study drug. Therefore, 1323 participants were in the modified intention-to-treat sample, which was the a priori primary study sample. Only 1.4% of participants were lost to follow-up. Decentralized strategies facilitated the successful completion of the COVID-OUT trial without any in-person contact by expediting intervention delivery, expanding trial access geographically, limiting contagion exposure, and making it easy for participants to complete follow-up visits. Remotely completed consent and follow-up facilitated enrollment.
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An SJ, Davis D, Peiffer S, Gallaher J, Tignanelli CJ, Charles A. Arrhythmias in Critically Ill Surgical and Non-surgical Patients: A National Propensity-Matched Study. World J Surg 2023; 47:2668-2675. [PMID: 37524957 DOI: 10.1007/s00268-023-07129-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/17/2023] [Indexed: 08/02/2023]
Abstract
BACKGROUND Arrhythmias are common in critically ill patients, though the impact of arrhythmias on surgical patients is not well delineated. We aimed to characterize mortality following arrhythmias in critically ill patients. METHODS We performed a propensity-matched retrospective analysis of intensive care unit (ICU) patients from 2007 to 2017 in the Cerner Acute Physiology and Chronic Health Evaluation database. We compared outcomes between patients with and without arrhythmias and those with and without surgical indications for ICU admission. We also modeled predictors of arrhythmias in surgical patients. RESULTS 467,951 patients were included; 97,958 (20.9%) were surgical patients. Arrhythmias occurred in 1.4% of the study cohorts. Predictors of arrhythmias in surgical patients included a history of cardiovascular disease (odds ratio [OR] 1.35, 95% confidence interval [CI95] 1.11-1.63), respiratory failure (OR 1.48, CI95 1.12-1.96), pneumonia (OR 3.17, CI95 1.98-5.10), higher bicarbonate level (OR 1.03, CI95 1.01-1.05), lower albumin level (OR 0.79, CI95 0.68-0.91), and vasopressor requirement (OR 27.2, CI95 22.0-33.7). After propensity matching, surgical patients with arrhythmias had a 42% mortality risk reduction compared to non-surgical patients (risk ratio [RR] 0.58, CI 95 0.43-0.79). Predicted probabilities of mortality for surgical patients were lower at all ages. CONCLUSIONS Surgical patients with arrhythmias are at lower risk of mortality than non-surgical patients. In this propensity-matched analysis, predictors of arrhythmias in critically ill surgical patients included a history of cardiovascular disease, respiratory complications, increased bicarbonate levels, decreased albumin levels, and vasopressor requirement. These findings highlight the differential effect of arrhythmias on different cohorts of critically ill populations.
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Yang K, Kang Z, Guan W, Lotfi-Emran S, Mayer ZJ, Guerrero CR, Steffen BT, Puskarich MA, Tignanelli CJ, Lusczek E, Safo SE. Developing A Baseline Metabolomic Signature Associated with COVID-19 Severity: Insights from Prospective Trials Encompassing 13 U.S. Centers. Metabolites 2023; 13:1107. [PMID: 37999202 PMCID: PMC10672920 DOI: 10.3390/metabo13111107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 10/14/2023] [Accepted: 10/16/2023] [Indexed: 11/25/2023] Open
Abstract
Metabolic disease is a significant risk factor for severe COVID-19 infection, but the contributing pathways are not yet fully elucidated. Using data from two randomized controlled trials across 13 U.S. academic centers, our goal was to characterize metabolic features that predict severe COVID-19 and define a novel baseline metabolomic signature. Individuals (n = 133) were dichotomized as having mild or moderate/severe COVID-19 disease based on the WHO ordinal scale. Blood samples were analyzed using the Biocrates platform, providing 630 targeted metabolites for analysis. Resampling techniques and machine learning models were used to determine metabolomic features associated with severe disease. Ingenuity Pathway Analysis (IPA) was used for functional enrichment analysis. To aid in clinical decision making, we created baseline metabolomics signatures of low-correlated molecules. Multivariable logistic regression models were fit to associate these signatures with severe disease on training data. A three-metabolite signature, lysophosphatidylcholine a C17:0, dihydroceramide (d18:0/24:1), and triacylglyceride (20:4_36:4), resulted in the best discrimination performance with an average test AUROC of 0.978 and F1 score of 0.942. Pathways related to amino acids were significantly enriched from the IPA analyses, and the mitogen-activated protein kinase kinase 5 (MAP2K5) was differentially activated between groups. In conclusion, metabolites related to lipid metabolism efficiently discriminated between mild vs. moderate/severe disease. SDMA and GABA demonstrated the potential to discriminate between these two groups as well. The mitogen-activated protein kinase kinase 5 (MAP2K5) regulator is differentially activated between groups, suggesting further investigation as a potential therapeutic pathway.
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Fawley JA, Tignanelli CJ, Werner NL, Kasotakis G, Mandell SP, Glass NE, Dries DJ, Costantini TW, Napolitano LM. American Association for the Surgery of Trauma/American College of Surgeons Committee on Trauma clinical protocol for management of acute respiratory distress syndrome and severe hypoxemia. J Trauma Acute Care Surg 2023; 95:592-602. [PMID: 37314843 PMCID: PMC10545067 DOI: 10.1097/ta.0000000000004046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 04/27/2023] [Accepted: 04/28/2023] [Indexed: 06/15/2023]
Abstract
LEVEL OF EVIDENCE Therapeutic/Care Management: Level V.
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Bramante CT, Buse JB, Liebovitz DM, Nicklas JM, Puskarich MA, Cohen K, Belani HK, Anderson BJ, Huling JD, Tignanelli CJ, Thompson JL, Pullen M, Wirtz EL, Siegel LK, Proper JL, Odde DJ, Klatt NR, Sherwood NE, Lindberg SM, Karger AB, Beckman KB, Erickson SM, Fenno SL, Hartman KM, Rose MR, Mehta T, Patel B, Griffiths G, Bhat NS, Murray TA, Boulware DR. Outpatient treatment of COVID-19 and incidence of post-COVID-19 condition over 10 months (COVID-OUT): a multicentre, randomised, quadruple-blind, parallel-group, phase 3 trial. THE LANCET. INFECTIOUS DISEASES 2023; 23:1119-1129. [PMID: 37302406 DOI: 10.1016/s1473-3099(23)00299-2] [Citation(s) in RCA: 56] [Impact Index Per Article: 56.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 03/30/2023] [Accepted: 05/02/2023] [Indexed: 06/13/2023]
Abstract
BACKGROUND Post-COVID-19 condition (also known as long COVID) is an emerging chronic illness potentially affecting millions of people. We aimed to evaluate whether outpatient COVID-19 treatment with metformin, ivermectin, or fluvoxamine soon after SARS-CoV-2 infection could reduce the risk of long COVID. METHODS We conducted a decentralised, randomised, quadruple-blind, parallel-group, phase 3 trial (COVID-OUT) at six sites in the USA. We included adults aged 30-85 years with overweight or obesity who had COVID-19 symptoms for fewer than 7 days and a documented SARS-CoV-2 positive PCR or antigen test within 3 days before enrolment. Participants were randomly assigned via 2 × 3 parallel factorial randomisation (1:1:1:1:1:1) to receive metformin plus ivermectin, metformin plus fluvoxamine, metformin plus placebo, ivermectin plus placebo, fluvoxamine plus placebo, or placebo plus placebo. Participants, investigators, care providers, and outcomes assessors were masked to study group assignment. The primary outcome was severe COVID-19 by day 14, and those data have been published previously. Because the trial was delivered remotely nationwide, the a priori primary sample was a modified intention-to-treat sample, meaning that participants who did not receive any dose of study treatment were excluded. Long COVID diagnosis by a medical provider was a prespecified, long-term secondary outcome. This trial is complete and is registered with ClinicalTrials.gov, NCT04510194. FINDINGS Between Dec 30, 2020, and Jan 28, 2022, 6602 people were assessed for eligibility and 1431 were enrolled and randomly assigned. Of 1323 participants who received a dose of study treatment and were included in the modified intention-to-treat population, 1126 consented for long-term follow-up and completed at least one survey after the assessment for long COVID at day 180 (564 received metformin and 562 received matched placebo; a subset of participants in the metformin vs placebo trial were also randomly assigned to receive ivermectin or fluvoxamine). 1074 (95%) of 1126 participants completed at least 9 months of follow-up. 632 (56·1%) of 1126 participants were female and 494 (43·9%) were male; 44 (7·0%) of 632 women were pregnant. The median age was 45 years (IQR 37-54) and median BMI was 29·8 kg/m2 (IQR 27·0-34·2). Overall, 93 (8·3%) of 1126 participants reported receipt of a long COVID diagnosis by day 300. The cumulative incidence of long COVID by day 300 was 6·3% (95% CI 4·2-8·2) in participants who received metformin and 10·4% (7·8-12·9) in those who received identical metformin placebo (hazard ratio [HR] 0·59, 95% CI 0·39-0·89; p=0·012). The metformin beneficial effect was consistent across prespecified subgroups. When metformin was started within 3 days of symptom onset, the HR was 0·37 (95% CI 0·15-0·95). There was no effect on cumulative incidence of long COVID with ivermectin (HR 0·99, 95% CI 0·59-1·64) or fluvoxamine (1·36, 0·78-2·34) compared with placebo. INTERPRETATION Outpatient treatment with metformin reduced long COVID incidence by about 41%, with an absolute reduction of 4·1%, compared with placebo. Metformin has clinical benefits when used as outpatient treatment for COVID-19 and is globally available, low-cost, and safe. FUNDING Parsemus Foundation; Rainwater Charitable Foundation; Fast Grants; UnitedHealth Group Foundation; National Institute of Diabetes, Digestive and Kidney Diseases; National Institutes of Health; and National Center for Advancing Translational Sciences.
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Alper BS, Dehnbostel J, Shahin K, Ojha N, Khanna G, Tignanelli CJ. Striking a match between FHIR-based patient data and FHIR-based eligibility criteria. Learn Health Syst 2023; 7:e10368. [PMID: 37860063 PMCID: PMC10582208 DOI: 10.1002/lrh2.10368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 03/10/2023] [Accepted: 03/29/2023] [Indexed: 10/21/2023] Open
Abstract
Inputs and Outputs The Strike-a-Match Function, written in JavaScript version ES6+, accepts the input of two datasets (one dataset defining eligibility criteria for research studies or clinical decision support, and one dataset defining characteristics for an individual patient). It returns an output signaling whether the patient characteristics are a match for the eligibility criteria. Purpose Ultimately, such a system will play a "matchmaker" role in facilitating point-of-care recognition of patient-specific clinical decision support. Specifications The eligibility criteria are defined in HL7 FHIR (version R5) EvidenceVariable Resource JSON structure. The patient characteristics are provided in an FHIR Bundle Resource JSON including one Patient Resource and one or more Observation and Condition Resources which could be obtained from the patient's electronic health record. Application The Strike-a-Match Function determines whether or not the patient is a match to the eligibility criteria and an Eligibility Criteria Matching Software Demonstration interface provides a human-readable display of matching results by criteria for the clinician or patient to consider. This is the first software application, serving as proof of principle, that compares patient characteristics and eligibility criteria with all data exchanged using HL7 FHIR JSON. An Eligibility Criteria Matching Software Library at https://fevir.net/110192 provides a method for sharing functions using the same information model.
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Tignanelli CJ, Arbabi S, Iskander G, Kralovich K, Scott J, Sangji NF, Hemmila MR. Association of Discontinuing Preinjury Beta-Adrenergic Blockade Medications With Mortality in Severe Blunt Traumatic Brian Injury. ANNALS OF SURGERY OPEN 2023; 4:e324. [PMID: 37746607 PMCID: PMC10513140 DOI: 10.1097/as9.0000000000000324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 07/14/2023] [Indexed: 09/26/2023] Open
Abstract
Background Beta-adrenergic receptor blocker (BB) administration has been shown to improve survival after traumatic brain injury (TBI). However, studies to date that observe a benefit did not distinguish between continuation of preinjury BB versus de novo initiation of BB. Objectives To determine the effect of continuation of preinjury BB and de novo initiation of BB on risk-adjusted mortality and complications for patients with TBI. Methods Trauma quality collaborative data (2016-2021) were analyzed. Patients were excluded with hospitalization <48 hours, direct admission, or penetrating injury. Severe TBI was identified as a head abbreviated injury scale (AIS) value of 3 to 5. Patients were placed into 4 groups based on the preinjury BB use and administration of BB during hospitalization. Propensity score matching was used to create 1:1 matched cohorts of patients for comparisons. Odd ratios of mortality accounting for hospital clustering were calculated. A sensitivity analysis was performed excluding patients with AIS >2 injuries in all other body regions to create a cohort of isolated TBI patients. Results A total of 15,153 patients treated at 35 trauma centers were available for analysis. Patients were divided into 4 cohort groupings related to preinjury BB use and postinjury receipt of BB. The odds of mortality was significantly reduced for patients with a TBI on a preinjury BB who had the medication continued in the acute setting (as compared with patients on preinjury BB who did not) (odds ratio [OR], 0.73; 95% confidence interval [CI], 0.54-0.98; P = 0.04). Patients with a TBI who were not on preinjury BB did not benefit from de novo initiation of BB with regard to mortality (OR, 0.83; 95% CI, 0.64-1.08; P = 0.2). In the sensitivity analysis, excluding polytrauma patients, patients on preinjury BB who had BB continued had a reduction in mortality when compared with patients in which BB was stopped following a TBI (OR, 0.65; 95% CI, 0.47-0.91; P = 0.01). Conclusions Continuing BB is associated with reduced odds of mortality in patients with a TBI on preinjury BB. We were unable to demonstrate benefit from instituting beta blockade in patients who are not on a BB preinjury.
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Jones EK, Ninkovic I, Bahr M, Dodge S, Doering M, Martin D, Ottosen J, Allen T, Melton GB, Tignanelli CJ. A novel, evidence-based, comprehensive clinical decision support system improves outcomes for patients with traumatic rib fractures. J Trauma Acute Care Surg 2023; 95:161-171. [PMID: 37012630 DOI: 10.1097/ta.0000000000003866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023]
Abstract
BACKGROUND Traumatic rib fractures are associated with high morbidity and mortality. Clinical decision support systems (CDSS) have been shown to improve adherence to evidence-based (EB) practice and improve clinical outcomes. The objective of this study was to investigate if a rib fracture CDSS reduced hospital length of stay (LOS), 90-day and 1-year mortality, unplanned ICU transfer, and the need for mechanical ventilation. The independent association of two process measures, an admission EB order set and a pain-inspiratory-cough score early warning system, with LOS were investigated. METHODS The CDSS was scaled across nine US trauma centers. Following multiple imputation, multivariable regression models were fit to evaluate the association of the CDSS on primary and secondary outcomes. As a sensitivity analysis, propensity score matching was also performed to confirm regression findings. RESULTS Overall, 3,279 patients met inclusion criteria. Rates of EB practices increased following implementation. On risk-adjusted analysis, in-hospital LOS preintervention versus postintervention was unchanged (incidence rate ratio [IRR], 1.06; 95% confidence interval [CI], 0.97-1.15, p = 0.2) but unplanned transfer to the ICU was reduced (odds ratio, 0.28; 95% CI, 0.09-0.84, p = 0.024), as was 1-year mortality (hazard ratio, 0.6; 95% CI, 0.4-0.89, p = 0.01). Provider utilization of the admission order bundle was 45.3%. Utilization was associated with significantly reduced LOS (IRR, 0.87; 95% CI, 0.77-0.98; p = 0.019). The early warning system triggered on 34.4% of patients; however, was not associated with a significant reduction in hospital LOS (IRR, 0.76; 95% CI, 0.55-1.06; p = 0.1). CONCLUSION A novel, user-centered, comprehensive CDSS improves adherence to EB practice and is associated with a significant reduction in unplanned ICU admissions and possibly mortality, but not hospital LOS. LEVEL OF EVIDENCE Therapeutic/Care Management; Level III.
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Byrd TF, Southwell B, Ravishankar A, Tran T, Kc A, Phelan T, Melton-Meaux GB, Usher MG, Scheppmann D, Switzer S, Simon G, Tignanelli CJ. Validation of a Proprietary Deterioration Index Model and Performance in Hospitalized Adults. JAMA Netw Open 2023; 6:e2324176. [PMID: 37486632 PMCID: PMC10366696 DOI: 10.1001/jamanetworkopen.2023.24176] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/25/2023] Open
Abstract
Importance The Deterioration Index (DTI), used by hospitals for predicting patient deterioration, has not been extensively validated externally, raising concerns about performance and equitable predictions. Objective To locally validate DTI performance and assess its potential for bias in predicting patient clinical deterioration. Design, Setting, and Participants This retrospective prognostic study included 13 737 patients admitted to 8 heterogenous Midwestern US hospitals varying in size and type, including academic, community, urban, and rural hospitals. Patients were 18 years or older and admitted between January 1 and May 31, 2021. Exposure DTI predictions made every 15 minutes. Main Outcomes and Measures Deterioration, defined as the occurrence of any of the following while hospitalized: mechanical ventilation, intensive care unit transfer, or death. Performance of the DTI was evaluated using area under the receiver operating characteristic curve (AUROC) and area under the precision recall curve (AUPRC). Bias measures were calculated across demographic subgroups. Results A total of 5 143 513 DTI predictions were made for 13 737 patients across 14 834 hospitalizations. Among 13 918 encounters, the mean (SD) age of patients was 60.3 (19.2) years; 7636 (54.9%) were female, 11 345 (81.5%) were White, and 12 392 (89.0%) were of other ethnicity than Hispanic or Latino. The prevalence of deterioration was 10.3% (n = 1436). The DTI produced AUROCs of 0.759 (95% CI, 0.756-0.762) at the observation level and 0.685 (95% CI, 0.671-0.700) at the encounter level. Corresponding AUPRCs were 0.039 (95% CI, 0.037-0.040) at the observation level and 0.248 (95% CI, 0.227-0.273) at the encounter level. Bias measures varied across demographic subgroups and were 14.0% worse for patients identifying as American Indian or Alaska Native and 19.0% worse for those who chose not to disclose their ethnicity. Conclusions and Relevance In this prognostic study, the DTI had modest ability to predict patient deterioration, with varying degrees of performance at the observation and encounter levels and across different demographic groups. Disparate performance across subgroups suggests the need for more transparency in model training data and reinforces the need to locally validate externally developed prediction models.
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Loftus TJ, Altieri MS, Balch JA, Abbott KL, Choi J, Marwaha JS, Hashimoto DA, Brat GA, Raftopoulos Y, Evans HL, Jackson GP, Walsh DS, Tignanelli CJ. Artificial Intelligence-enabled Decision Support in Surgery: State-of-the-art and Future Directions. Ann Surg 2023; 278:51-58. [PMID: 36942574 DOI: 10.1097/sla.0000000000005853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
OBJECTIVE To summarize state-of-the-art artificial intelligence-enabled decision support in surgery and to quantify deficiencies in scientific rigor and reporting. BACKGROUND To positively affect surgical care, decision-support models must exceed current reporting guideline requirements by performing external and real-time validation, enrolling adequate sample sizes, reporting model precision, assessing performance across vulnerable populations, and achieving clinical implementation; the degree to which published models meet these criteria is unknown. METHODS Embase, PubMed, and MEDLINE databases were searched from their inception to September 21, 2022 for articles describing artificial intelligence-enabled decision support in surgery that uses preoperative or intraoperative data elements to predict complications within 90 days of surgery. Scientific rigor and reporting criteria were assessed and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. RESULTS Sample size ranged from 163-2,882,526, with 8/36 articles (22.2%) featuring sample sizes of less than 2000; 7 of these 8 articles (87.5%) had below-average (<0.83) area under the receiver operating characteristic or accuracy. Overall, 29 articles (80.6%) performed internal validation only, 5 (13.8%) performed external validation, and 2 (5.6%) performed real-time validation. Twenty-three articles (63.9%) reported precision. No articles reported performance across sociodemographic categories. Thirteen articles (36.1%) presented a framework that could be used for clinical implementation; none assessed clinical implementation efficacy. CONCLUSIONS Artificial intelligence-enabled decision support in surgery is limited by reliance on internal validation, small sample sizes that risk overfitting and sacrifice predictive performance, and failure to report confidence intervals, precision, equity analyses, and clinical implementation. Researchers should strive to improve scientific quality.
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Di Stefano L, Ram M, Scharfstein DO, Li T, Khanal P, Baksh SN, McBee N, Bengtson CD, Gadomski A, Geriak M, Puskarich MA, Salathe MA, Schutte AE, Tignanelli CJ, Victory J, Bierer BE, Hanley DF, Freilich DA. Losartan in hospitalized patients with COVID-19 in North America: An individual participant data meta-analysis. Medicine (Baltimore) 2023; 102:e33904. [PMID: 37335665 PMCID: PMC10256351 DOI: 10.1097/md.0000000000033904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 05/11/2023] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers (ARBs) have been hypothesized to benefit patients with COVID-19 via the inhibition of viral entry and other mechanisms. We conducted an individual participant data (IPD) meta-analysis assessing the effect of starting the ARB losartan in recently hospitalized COVID-19 patients. METHODS We searched ClinicalTrials.gov in January 2021 for U.S./Canada-based trials where an angiotensin-converting enzyme inhibitors/ARB was a treatment arm, targeted outcomes could be extrapolated, and data sharing was allowed. Our primary outcome was a 7-point COVID-19 ordinal score measured 13 to 16 days post-enrollment. We analyzed data by fitting multilevel Bayesian ordinal regression models and standardizing the resulting predictions. RESULTS 325 participants (156 losartan vs 169 control) from 4 studies contributed IPD. Three were randomized trials; one used non-randomized concurrent and historical controls. Baseline covariates were reasonably balanced for the randomized trials. All studies evaluated losartan. We found equivocal evidence of a difference in ordinal scores 13-16 days post-enrollment (model-standardized odds ratio [OR] 1.10, 95% credible interval [CrI] 0.76-1.71; adjusted OR 1.15, 95% CrI 0.15-3.59) and no compelling evidence of treatment effect heterogeneity among prespecified subgroups. Losartan had worse effects for those taking corticosteroids at baseline after adjusting for covariates (ratio of adjusted ORs 0.29, 95% CrI 0.08-0.99). Hypotension serious adverse event rates were numerically higher with losartan. CONCLUSIONS In this IPD meta-analysis of hospitalized COVID-19 patients, we found no convincing evidence for the benefit of losartan versus control treatment, but a higher rate of hypotension adverse events with losartan.
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Bramante CT, Beckman KB, Mehta T, Karger AB, Odde DJ, Tignanelli CJ, Buse JB, Johnson DM, Watson RHB, Daniel JJ, Liebovitz DM, Nicklas JM, Cohen K, Puskarich MA, Belani HK, Siegel LK, Klatt NR, Anderson B, Hartman KM, Rao V, Hagen AA, Patel B, Fenno SL, Avula N, Reddy NV, Erickson SM, Fricton RD, Lee S, Griffiths G, Pullen MF, Thompson JL, Sherwood N, Murray TA, Rose MR, Boulware DR, Huling JD. Metformin reduces SARS-CoV-2 in a Phase 3 Randomized Placebo Controlled Clinical Trial. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.06.23290989. [PMID: 37333243 PMCID: PMC10275003 DOI: 10.1101/2023.06.06.23290989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Current antiviral treatment options for SARS-CoV-2 infections are not available globally, cannot be used with many medications, and are limited to virus-specific targets.1-3 Biophysical modeling of SARS-CoV-2 replication predicted that protein translation is an especially attractive target for antiviral therapy.4 Literature review identified metformin, widely known as a treatment for diabetes, as a potential suppressor of protein translation via targeting of the host mTor pathway.5 In vitro, metformin has antiviral activity against RNA viruses including SARS-CoV-2.6,7 In the COVID-OUT phase 3, randomized, placebo-controlled trial of outpatient treatment of COVID-19, metformin had a 42% reduction in ER visits/hospitalizations/death through 14 days; a 58% reduction in hospitalizations/death through 28 days, and a 42% reduction in Long COVID through 10 months.8,9 Here we show viral load analysis of specimens collected in the COVID-OUT trial that the mean SARS-CoV-2 viral load was reduced 3.6-fold with metformin relative to placebo (-0.56 log10 copies/mL; 95%CI, -1.05 to -0.06, p=0.027) while there was no virologic effect for ivermectin or fluvoxamine vs placebo. The metformin effect was consistent across subgroups and with emerging data.10,11 Our results demonstrate, consistent with model predictions, that a safe, widely available,12 well-tolerated, and inexpensive oral medication, metformin, can be repurposed to significantly reduce SARS-CoV-2 viral load.
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Samorodnitsky S, Castro-Pearson S, Yang K, Lotfi-Emran S, Ingraham NE, Bramante C, Geising S, Jones EK, Wacker D, Puskarich M, Lusczek E, Safo S, Tignanelli CJ. Proteomic pathways associated with developing severe disease for patients with COVID-19: A biologic analysis of data from two multicenter randomized controlled trials encompassing 13 U.S. hospitals. J Crit Care 2023. [PMCID: PMC9930204 DOI: 10.1016/j.jcrc.2022.154203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
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Ingraham NE, Jones EK, King S, Dries J, Phillips M, Loftus T, Evans HL, Melton GB, Tignanelli CJ. Re-Aiming Equity Evaluation in Clinical Decision Support: A Scoping Review of Equity Assessments in Surgical Decision Support Systems. Ann Surg 2023; 277:359-364. [PMID: 35943199 PMCID: PMC9905217 DOI: 10.1097/sla.0000000000005661] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
OBJECTIVE We critically evaluated the surgical literature to explore the prevalence and describe how equity assessments occur when using clinical decision support systems. BACKGROUND Clinical decision support (CDS) systems are increasingly used to facilitate surgical care delivery. Despite formal recommendations to do so, equity evaluations are not routinely performed on CDS systems and underrepresented populations are at risk of harm and further health disparities. We explored surgical literature to determine frequency and rigor of CDS equity assessments and offer recommendations to improve CDS equity by appending existing frameworks. METHODS We performed a scoping review up to Augus 25, 2021 using PubMed and Google Scholar for the following search terms: clinical decision support, implementation, RE-AIM, Proctor, Proctor's framework, equity, trauma, surgery, surgical. We identified 1415 citations and 229 abstracts met criteria for review. A total of 84 underwent full review after 145 were excluded if they did not assess outcomes of an electronic CDS tool or have a surgical use case. RESULTS Only 6% (5/84) of surgical CDS systems reported equity analyses, suggesting that current methods for optimizing equity in surgical CDS are inadequate. We propose revising the RE-AIM framework to include an Equity element (RE 2 -AIM) specifying that CDS foundational analyses and algorithms are performed or trained on balanced datasets with sociodemographic characteristics that accurately represent the CDS target population and are assessed by sensitivity analyses focused on vulnerable subpopulations. CONCLUSION Current surgical CDS literature reports little with respect to equity. Revising the RE-AIM framework to include an Equity element (RE 2 -AIM) promotes the development and implementation of CDS systems that, at minimum, do not worsen healthcare disparities and possibly improve their generalizability.
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Johnson RA, Eaton A, Tignanelli CJ, Carrabre KJ, Gerges C, Yang GL, Hemmila MR, Ngwenya LB, Wright JM, Parr AM. Changes in patterns of traumatic brain injury in the Michigan Trauma Quality Improvement Program database early in the COVID-19 pandemic. J Neurosurg 2023; 138:465-475. [PMID: 35901671 DOI: 10.3171/2022.5.jns22244] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 05/17/2022] [Indexed: 02/04/2023]
Abstract
OBJECTIVE The authors' objective was to investigate the impact of the global COVID-19 pandemic on hospital presentation and process of care for the treatment of traumatic brain injuries (TBIs). Improved understanding of these effects will inform sociopolitical and hospital policies in response to future pandemics. METHODS The Michigan Trauma Quality Improvement Program (MTQIP) database, which contains data from 36 level I and II trauma centers in Michigan and Minnesota, was queried to identify patients who sustained TBI on the basis of head/neck Abbreviated Injury Scale (AIS) codes during the periods of March 13 through July 2 of 2017-2019 (pre-COVID-19 period) and March 13, 2020, through July 2, 2020 (COVID-19 period). Analyses were performed to detect differences in incidence, patient characteristics, injury severity, and outcomes. RESULTS There was an 18% decrease in the rate of encounters with TBI in the first 8 weeks (March 13 through May 7), followed by a 16% increase during the last 8 weeks (May 8 through July 2), of our COVID-19 period compared with the pre-COVID-19 period. Cumulatively, there was no difference in the rates of encounters with TBI between the COVID-19 and pre-COVID-19 periods. Severity of TBI, as measured with maximum AIS score for the head/neck region and Glasgow Coma Scale score, was also similar between periods. During the COVID-19 period, a greater proportion of patients with TBI presented more than a day after sustaining their injuries (p = 0.046). COVID-19 was also associated with a doubling in the decubitus ulcer rate from 1.0% to 2.1% (p = 0.002) and change in the distribution of discharge status (p = 0.01). Multivariable analysis showed no differences in odds of death/hospice discharge, intensive care unit stay of at least a day, or need for a ventilator for at least a day between the COVID-19 and pre-COVID-19 periods. CONCLUSIONS During the early months of the COVID-19 pandemic, the number of patients who presented with TBI was initially lower than in the years 2017-2019 prior to the pandemic. However, there was a subsequent increase in the rate of encounters with TBI, resulting in overall similar rates of TBI between March 13 through July 2 during the COVID-19 period and during the pre-COVID-19 period. The COVID-19 cohort was also associated with negative impacts on time to presentation, rate of decubitus ulcers, and discharge with supervision. Policies in response to future pandemics must consider the resources necessary to care for patients with TBI.
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