Expressions 2011

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If, When, and How to Use Rifampin in Acute Staphylococcal Periprosthetic Joint Infections, a Multicentre Observational Study

Background: Rifampin is generally advised in the treatment of acute staphylococcal periprosthetic joint infections (PJI). However, if, when, and how to use rifampin remains a matter of debate. We evaluated the outcome of patients treated with and without rifampin, and analyzed the influence of timing, dose and co-antibiotic. Methods: Acute staphylococcal PJIs treated with surgical debridement between 1999 and 2017, and a minimal follow-up of 1 year were evaluated. Treatment failure was defined as the need for any further surgical procedure related to infection, PJI-related death or the need for suppressive antimicrobial treatment. Results: A total of 669 patients were analyzed. Treatment failure was 32.2% (131/407) in patients treated with rifampin and 54.2% (142/262) in whom rifampin was withheld (P < .001). The most prominent effect of rifampin was observed in knees (treatment failure 28.6% versus 63.9%, respectively, P < .001). The use of rifampin was an independent predictor of treatment success in the multi-variate analysis (OR 0.30, 95% CI 0.20 - 0.45). In the rifampin group, the use of a co-antibiotic other than a fluoroquinolone or clindamycin (OR 10.1, 95% CI 5.65 - 18.2) and the start of rifampin within 5 days after surgical debridement (OR 1.96, 95% CI 1.08 - 3.65) were predictors of treatment failure. The dosing of rifampin had no effect on outcome. Conclusions: Our data supports the use of rifampin in acute staphylococcal PJIs treated with surgical debridement, particularly in knees. Immediate start of rifampin after surgical debridement should probably be discouraged, but requires further investigation

Debridement, antibiotics and implant retention is a viable treatment option for early periprosthetic joint infection presenting more than four weeks after index arthroplasty

Background. The success of debridement, antibiotics, and implant retention (DAIR) in early periprosthetic joint infection (PJI) largely depends on the presence of a mature biofilm. At what time point DAIR should be disrecommended is unknown. This multicenter study evaluated the outcome of DAIR in relation to the time after index arthroplasty. Methods. We retrospectively evaluated PJIs occurring within 90 days after surgery and treated with DAIR. Patients with bacteremia, arthroscopic debridements, and a follow-up <1 year were excluded. Treatment failure was defined as (1) any further surgical procedure related to infection; (2) PJI-related death; or (3) use of long-term suppressive antibiotics. Results. We included 769 patients. Treatment failure occurred in 294 patients (38%) and was similar between time intervals from index arthroplasty to DAIR: The failure rate for Week 1-2 was 42% (95/226), the rate for Week 3-4 was 38% (143/378), the rate for Week 5-6 was 29% (29/100), and the rate for Week 7-12 was 42% (27/65). An exchange of modular components was performed to a lesser extent in the early post-surgical course compared with the late course (41% vs 63%, respectively; P < .001). The causative microorganisms, comorbidities, and durations of symptoms were comparable between time intervals. Conclusions. DAIR is a viable option in patients with early PJI presenting more than 4 weeks after index surgery, as long as DAIR is performed within at least 1 week after the onset of symptoms and modular components can be exchanged

Pharmacologic Ascorbic Acid as Early Therapy for Hospitalized Patients with COVID-19: A Randomized Clinical Trial

Despite the widespread availability of effective vaccines, new cases of infection with severe acute respiratory syndrome coronavirus-2, the cause of coronavirus disease 2019 (COVID-19), remain a concern in the settings of vaccine hesitancy and vaccine breakthrough. In this randomized, controlled, phase 2 trial, we hypothesized that high-dose ascorbic acid delivered intravenously to achieve pharmacologic concentrations may target the high viral phase of COVID-19 and thus improve early clinical outcomes. Sixty-six patients admitted with COVID-19 and requiring supplemental oxygen were randomized to receive either escalating doses of intravenous ascorbic acid plus standard of care or standard of care alone. The demographic and clinical characteristics were well-balanced between the two study arms. The primary outcome evaluated in this study was clinical improvement at 72 h after randomization. While the primary outcome was not achieved, point estimates for the composite outcome and its individual components of decreased use of supplemental oxygen, decreased use of bronchodilators, and the time to discharge were all favorable for the treatment arm. Possible favorable effects of ascorbic acid were most apparent during the first 72 h of hospitalization, although these effects disappeared over the course of the entire hospitalization. Future larger trials of intravenous ascorbic acid should be based on our current understanding of COVID-19 with a focus on the potential early benefits of ascorbic in hospitalized patients

Should We Use Rifampicin in Periprosthetic Joint Infections Caused by Staphylococci When the Implant Has Been Exchanged? A Multicenter Observational Cohort Study

BACKGROUND: Previous studies demonstrated the efficacy of a rifampicin-based regimen in the treatment of acute staphylococcal periprosthetic joint infections (PJIs) treated with surgical debridement. However, evidence is lacking to support the use of rifampicin in cases where the implant is exchanged during revision. METHODS: We included all consecutive cases of staphylococcal PJIs treated from January 2013 to December 2018 with revision surgery in this international, retrospective, multicenter observational cohort study. PJI was defined according to the European Bone and Joint Infection Society diagnostic criteria. A relapse or reinfection during follow-up, the need for antibiotic suppressive therapy, the need for implant removal, and PJI-related death were defined as clinical failure. Cases without reimplantation or with follow-upexcluded. RESULTS: A total of 375 cases were included in the final analysis, including 124 1-stage exchanges (33.1%) and 251 2-stage exchanges (66.9%). Of those, 101 cases failed (26.9%). There was no statistically significant difference in failure of patients receiving rifampicin (22.5%, 42/187) and those not receiving rifampicin (31.4%, 59/188; CONCLUSIONS: Combination treatment with rifampicin increases treatment success in patients with chronic staphylococcal PJI treated with 2-stage exchange arthroplasty

Validation of Automated Data Abstraction for SCCM Discovery VIRUS COVID-19 Registry: Practical EHR Export Pathways (VIRUS-PEEP)

BACKGROUND: The gold standard for gathering data from electronic health records (EHR) has been manual data extraction; however, this requires vast resources and personnel. Automation of this process reduces resource burdens and expands research opportunities. OBJECTIVE: This study aimed to determine the feasibility and reliability of automated data extraction in a large registry of adult COVID-19 patients. MATERIALS AND METHODS: This observational study included data from sites participating in the SCCM Discovery VIRUS COVID-19 registry. Important demographic, comorbidity, and outcome variables were chosen for manual and automated extraction for the feasibility dataset. We quantified the degree of agreement with Cohen\u27s kappa statistics for categorical variables. The sensitivity and specificity were also assessed. Correlations for continuous variables were assessed with Pearson\u27s correlation coefficient and Bland-Altman plots. The strength of agreement was defined as almost perfect (0.81-1.00), substantial (0.61-0.80), and moderate (0.41-0.60) based on kappa statistics. Pearson correlations were classified as trivial (0.00-0.30), low (0.30-0.50), moderate (0.50-0.70), high (0.70-0.90), and extremely high (0.90-1.00). MEASUREMENTS AND MAIN RESULTS: The cohort included 652 patients from 11 sites. The agreement between manual and automated extraction for categorical variables was almost perfect in 13 (72.2%) variables (Race, Ethnicity, Sex, Coronary Artery Disease, Hypertension, Congestive Heart Failure, Asthma, Diabetes Mellitus, ICU admission rate, IMV rate, HFNC rate, ICU and Hospital Discharge Status), and substantial in five (27.8%) (COPD, CKD, Dyslipidemia/Hyperlipidemia, NIMV, and ECMO rate). The correlations were extremely high in three (42.9%) variables (age, weight, and hospital LOS) and high in four (57.1%) of the continuous variables (Height, Days to ICU admission, ICU LOS, and IMV days). The average sensitivity and specificity for the categorical data were 90.7 and 96.9%. CONCLUSION AND RELEVANCE: Our study confirms the feasibility and validity of an automated process to gather data from the EHR

Validation of automated data abstraction for SCCM discovery VIRUS COVID-19 registry: practical EHR export pathways (VIRUS-PEEP)

BackgroundThe gold standard for gathering data from electronic health records (EHR) has been manual data extraction; however, this requires vast resources and personnel. Automation of this process reduces resource burdens and expands research opportunities.ObjectiveThis study aimed to determine the feasibility and reliability of automated data extraction in a large registry of adult COVID-19 patients.Materials and methodsThis observational study included data from sites participating in the SCCM Discovery VIRUS COVID-19 registry. Important demographic, comorbidity, and outcome variables were chosen for manual and automated extraction for the feasibility dataset. We quantified the degree of agreement with Cohen’s kappa statistics for categorical variables. The sensitivity and specificity were also assessed. Correlations for continuous variables were assessed with Pearson’s correlation coefficient and Bland–Altman plots. The strength of agreement was defined as almost perfect (0.81–1.00), substantial (0.61–0.80), and moderate (0.41–0.60) based on kappa statistics. Pearson correlations were classified as trivial (0.00–0.30), low (0.30–0.50), moderate (0.50–0.70), high (0.70–0.90), and extremely high (0.90–1.00).Measurements and main resultsThe cohort included 652 patients from 11 sites. The agreement between manual and automated extraction for categorical variables was almost perfect in 13 (72.2%) variables (Race, Ethnicity, Sex, Coronary Artery Disease, Hypertension, Congestive Heart Failure, Asthma, Diabetes Mellitus, ICU admission rate, IMV rate, HFNC rate, ICU and Hospital Discharge Status), and substantial in five (27.8%) (COPD, CKD, Dyslipidemia/Hyperlipidemia, NIMV, and ECMO rate). The correlations were extremely high in three (42.9%) variables (age, weight, and hospital LOS) and high in four (57.1%) of the continuous variables (Height, Days to ICU admission, ICU LOS, and IMV days). The average sensitivity and specificity for the categorical data were 90.7 and 96.9%.Conclusion and relevanceOur study confirms the feasibility and validity of an automated process to gather data from the EHR

Metabolic Syndrome and Acute Respiratory Distress Syndrome in Hospitalized Patients With COVID-19

Importance: Obesity, diabetes, and hypertension are common comorbidities in patients with severe COVID-19, yet little is known about the risk of acute respiratory distress syndrome (ARDS) or death in patients with COVID-19 and metabolic syndrome. Objective: To determine whether metabolic syndrome is associated with an increased risk of ARDS and death from COVID-19. Design, setting, and participants: This multicenter cohort study used data from the Society of Critical Care Medicine Discovery Viral Respiratory Illness Universal Study collected from 181 hospitals across 26 countries from February 15, 2020, to February 18, 2021. Outcomes were compared between patients with metabolic syndrome (defined as ≥3 of the following criteria: obesity, prediabetes or diabetes, hypertension, and dyslipidemia) and a control population without metabolic syndrome. Participants included adult patients hospitalized for COVID-19 during the study period who had a completed discharge status. Data were analyzed from February 22 to October 5, 2021. Exposures: Exposures were SARS-CoV-2 infection, metabolic syndrome, obesity, prediabetes or diabetes, hypertension, and/or dyslipidemia. Main outcomes and measures: The primary outcome was in-hospital mortality. Secondary outcomes included ARDS, intensive care unit (ICU) admission, need for invasive mechanical ventilation, and length of stay (LOS). Results: Among 46 441 patients hospitalized with COVID-19, 29 040 patients (mean [SD] age, 61.2 [17.8] years; 13 059 [45.0%] women and 15713 [54.1%] men; 6797 Black patients [23.4%], 5325 Hispanic patients [18.3%], and 16 507 White patients [57.8%]) met inclusion criteria. A total of 5069 patients (17.5%) with metabolic syndrome were compared with 23 971 control patients (82.5%) without metabolic syndrome. In adjusted analyses, metabolic syndrome was associated with increased risk of ICU admission (adjusted odds ratio [aOR], 1.32 [95% CI, 1.14-1.53]), invasive mechanical ventilation (aOR, 1.45 [95% CI, 1.28-1.65]), ARDS (aOR, 1.36 [95% CI, 1.12-1.66]), and mortality (aOR, 1.19 [95% CI, 1.08-1.31]) and prolonged hospital LOS (median [IQR], 8.0 [4.2-15.8] days vs 6.8 [3.4-13.0] days; P \u3c .001) and ICU LOS (median [IQR], 7.0 [2.8-15.0] days vs 6.4 [2.7-13.0] days; P \u3c .001). Each additional metabolic syndrome criterion was associated with increased risk of ARDS in an additive fashion (1 criterion: 1147 patients with ARDS [10.4%]; P = .83; 2 criteria: 1191 patients with ARDS [15.3%]; P \u3c .001; 3 criteria: 817 patients with ARDS [19.3%]; P \u3c .001; 4 criteria: 203 patients with ARDS [24.3%]; P \u3c .001). Conclusions and relevance: These findings suggest that metabolic syndrome was associated with increased risks of ARDS and death in patients hospitalized with COVID-19. The association with ARDS was cumulative for each metabolic syndrome criteria present

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder