Comparative-Effectiveness of Oral Beta-Lactams and Fluoroquinolones for Stepdown Therapy in Patients with Enterobacterales Bloodstream Infections: A Retrospective Cohort Study.

Background: This study compares treatment failure for patients who received oral beta-lactams (BLs) and fluoroquinolones (FQs) for stepdown treatment of Enterobacterales bloodstream infections (BSIs). Methods: We conducted a single-center, retrospective, age- and sex-matched, cohort study, at a Veterans Affairs (VA) hospital in South Texas. Eligible patients were at least 18 years of age with a monomicrobial BSI treated with a single oral BL or FQ antibiotic. Treatment failure was defined as recurrence or all-cause mortality within 90 days of documented BSI. Bivariate (chi-square, Fisher's Exact, and Wilcoxon Rank Sum) and multivariate (logistic regression) statistical tests were used to compare groups. Results: A total of 130 patients were included in this study, with 65 patients per group. Groups were well balanced with respect to exact age, sex assigned at birth, Caucasian race, source control, intensive care unit admission, and Charlson Comorbidity Index. Importantly, 60% of patients in the BL group had cultures that were resistant to FQs and 71% were prescribed cefpodoxime. Patients in the BL group had higher median (interquartile range [IQR]) Pitt bacteremia scores than those in the FQ group: 2 (1-4) vs. 1 (1-2), p=0.04. Patients in the BL group also had a higher median (IQR) duration of intravenous (IV) antibiotics than those in the FQ group: 5 (3-7) vs. 4 (3-5), p=0.02. Treatment failure was statistically comparable for patients in the BL and FQ groups: 15% vs. 12%, p=0.61. This finding was consistent in a multivariate logistic regression model with group (BL vs. FQ) as the independent variable, treatment failure as the dependent variable, and Pitt bacteremia score and duration of IV antibiotics as covariates (OR: 0.76, 95% CI: 0.27-2.18). One patient in the FQ group experienced Clostridioides difficile infection. Conclusion: This study suggests that BLs may be as effective as FQs for oral stepdown treatment of Enterobacterales BSI without the potential associated risks. Furthermore, in the setting of FQ-resistant Enterobacterales BSI secondary to urinary source, third generation oral cephalosporins (i.e., cefpodoxime) may be reasonable alternatives.

Immunologic resilience and COVID-19 survival advantage.

BACKGROUND: The risk of severe coronavirus disease 2019 (COVID-19) varies significantly among persons of similar age and is higher in males. Age-independent, sex-biased differences in susceptibility to severe COVID-19 may be ascribable to deficits in a sexually dimorphic protective attribute that we termed immunologic resilience (IR). OBJECTIVE: We sought to examine whether deficits in IR that antedate or are induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection independently predict COVID-19 mortality. METHODS: IR levels were quantified with 2 novel metrics: immune health grades (IHG-I [best] to IHG-IV) to gauge CD8+ and CD4+ T-cell count equilibrium, and blood gene expression signatures. IR metrics were examined in a prospective COVID-19 cohort (n = 522); primary outcome was 30-day mortality. Associations of IR metrics with outcomes in non-COVID-19 cohorts (n = 13,461) provided the framework for linking pre-COVID-19 IR status to IR during COVID-19, as well as to COVID-19 outcomes. RESULTS: IHG-I, tracking high-grade equilibrium between CD8+ and CD4+ T-cell counts, was the most common grade (73%) among healthy adults, particularly in females. SARS-CoV-2 infection was associated with underrepresentation of IHG-I (21%) versus overrepresentation (77%) of IHG-II or IHG-IV, especially in males versus females (P < .01). Presentation with IHG-I was associated with 88% lower mortality, after controlling for age and sex; reduced risk of hospitalization and respiratory failure; lower plasma IL-6 levels; rapid clearance of nasopharyngeal SARS-CoV-2 burden; and gene expression signatures correlating with survival that signify immunocompetence and controlled inflammation. In non-COVID-19 cohorts, IR-preserving metrics were associated with resistance to progressive influenza or HIV infection, as well as lower 9-year mortality in the Framingham Heart Study, especially in females. CONCLUSIONS: Preservation of immunocompetence with controlled inflammation during antigenic challenges is a hallmark of IR and associates with longevity and AIDS resistance. Independent of age, a male-biased proclivity to degrade IR before and/or during SARS-CoV-2 infection predisposes to severe COVID-19.

Validation of Available Extended-Spectrum-Beta-Lactamase Clinical Scoring Models in Predicting Drug Resistance in Patients with Enteric Gram-Negative Bacteremia Treated at South Texas Veterans Health Care System.

Extended-spectrum-beta-lactamase (ESBL)-producing Enterobacteriaceae are increasingly common; however, predicting which patients are likely to be infected with an ESBL pathogen is challenging, leading to increased use of carbapenems. To date, five prediction models have been developed to distinguish between patients infected with ESBL pathogens. The aim of this study was to validate and compare each of these models to better inform antimicrobial stewardship. This was a retrospective cohort study of patients with Gram-negative bacteremia treated at the South Texas Veterans Health Care System over 3 months from 2018 to 2019. We evaluated isolate, clinical syndrome, and score variables for the five published prediction models/scores: Italian "Tumbarello," Duke, University of South Carolina (USC), Hopkins clinical decision tree, and modified Hopkins. Each model was assessed using the area under the receiver operating characteristic curve (AUROC) and Pearson correlation. One hundred forty-five patients were included for analysis, of which 20 (13.8%) were infected with an ESBL Escherichiacoli or Klebsiella spp. The most common sources of infection were genitourinary (55.8%) and gastrointestinal/intraabdominal (24.1%), and the most common pathogen was E. coli (75.2%). The prediction model with the strongest discriminatory ability (AUROC) was Tumbarello (0.7556). The correlation between prediction model score and percent ESBL was strongest with the modified Hopkins model (R2 = 0.74). In this veteran population, the modified Hopkins and Duke prediction models were most accurate in discriminating between Gram-negative bacteremia patients when considering both AUROC and correlation. However, given the moderate discriminatory ability, many patients with ESBL Enterobacteriaceae (at least 25%) may still be missed empirically.

Modeling the temporal network dynamics of neuronal cultures.

Neurons form complex networks that evolve over multiple time scales. In order to thoroughly characterize these networks, time dependencies must be explicitly modeled. Here, we present a statistical model that captures both the underlying structural and temporal dynamics of neuronal networks. Our model combines the class of Stochastic Block Models for community formation with Gaussian processes to model changes in the community structure as a smooth function of time. We validate our model on synthetic data and demonstrate its utility on three different studies using in vitro cultures of dissociated neurons.

Cases and etiologies of suspected COVID-19 reactivation.

Our article outlines a perspective on COVID-19 reactivation with considerations of implored commentary on behalf of the medical community regarding open discourse about this subject. Such a topic is paramount in elucidating parameters that pertain to testing, and subsequent public health population dynamics once uneventful cases pass. We argue that what some may refer to as a reinfection or reactivation of the virus, is actually a result of prolonged shedding of the virus complemented with occasional false positives/negatives and lab errors. This article was written with the perspective of informing in addition to engage discussions that distill salient, evidence-based characterization of COVID-19. We hope to recruit fellow academics in medicine who see trends in their own respective communities about people who re-test, and to explore their clinical outcomes.

Discovery of under immunized spatial clusters using network scan statistics.

BACKGROUND: Clusters of under-vaccinated children are emerging in a number of states in the United States due to rising rates of vaccine hesitancy and refusal. As the measles outbreaks in California and other states in 2015 and in Minnesota in 2017 showed, such clusters can pose a significant public health risk. Prior methods have used publicly-available school immunization data for analysis (except for a few, which use private healthcare patient records). School immunization data has limited demographic information-as a result, such analyses are not able to provide demographic characteristics of significant clusters. Further, the resolution of the clusters identified by prior methods is limited since they are typically restricted to disks or well-rounded shapes. METHODS: We use realistic population models for Minnesota (MN) and Washington (WA) state, which provide a model of activities for all individuals in the population. We combine this with school level immunization data for these two states, to estimate vaccine coverage at the level of census block groups. A scan statistic method defined on networks is used for finding significant clusters of under-immunized block groups, without any restrictions on shape. Further we provide the demographic characteristics of these clusters. RESULTS: We find 2 significant under-vaccinated clusters in MN and 3 in WA. These are very irregular in shape, in contrast to the circular disks reported in prior work, which rely on the SatScan approach. Some of the clusters found by our method are not contained in those computed using SatScan, a state-of-the-art software tool used in similar studies in other states. CONCLUSIONS: The emergence of under-immunized clusters is a growing concern for public health agencies because they can act as reservoirs of infection and increase the risk of infection into the wider population. Higher resolution clusters computed using our network based approach and population models provide new insights on the structure and characteristics of such clusters and enable targeted interventions.

Adjunctive Corticosteroid Therapy in the Treatment of Coccidioidal Meningitis.

Coccidioidal meningitis (CM) has high morbidity, and adjunctive measures to improve outcomes are needed. Using an established multicenter retrospective cohort study of CM (N = 221), we found that patients receiving adjunctive corticosteroids had a significant reduction in secondary cerebrovascular events (P = .0049). Those with CM-associated cerebrovascular events (8%) may benefit from short-term corticosteroids.

Comparison of cefazolin versus oxacillin for treatment of complicated bacteremia caused by methicillin-susceptible Staphylococcus aureus.

Contrary to prior case reports that described occasional clinical failures with cefazolin for methicillin-susceptible Staphylococcus aureus (MSSA) infections, recent studies have demonstrated no difference in outcomes between cefazolin and antistaphylococcal penicillins for the treatment of MSSA bacteremia. While promising, these studies described low frequencies of high-inoculum infections, such as endocarditis. This retrospective study compares clinical outcomes of cefazolin versus oxacillin for complicated MSSA bacteremia at two tertiary care hospitals between January 2008 and June 2012. Fifty-nine patients treated with cefazolin and 34 patients treated with oxacillin were included. Osteoarticular (41%) and endovascular (20%) sources were the predominant sites of infection. The rates of clinical cure at the end of therapy were similar between cefazolin and oxacillin (95% versus 88%; P=0.25), but overall failure at 90 days was higher in the oxacillin arm (47% versus 24%; P=0.04). Failures were more likely to have received surgical interventions (63% versus 40%; P=0.05) and to have an osteoarticular source (57% versus 33%; P=0.04). Failures also had a longer duration of bacteremia (7 versus 3 days; P=0.0002), which was the only predictor of failure. Antibiotic selection was not predictive of failure. Rates of adverse drug events were higher in the oxacillin arm (30% versus 3%; P=0.0006), and oxacillin was more frequently discontinued due to adverse drug events (21% versus 3%; P=0.01). Cefazolin appears similar to oxacillin for the treatment of complicated MSSA bacteremia but with significantly improved safety. The higher rates of failure with oxacillin may have been confounded by other patient factors and warrant further investigation.

Effects of COVID-19 hospitalization rates on the incidence of hospital-acquired Candida central line-associated bloodstream infection.

BACKGROUND: An increase in central line-associated bloodstream infections (CLABSIs) has been reported during the Coronavirus (COVID-19) pandemic; however, few studies have documented causative pathogens, particularly Candida species associated with candidemia. METHODS: This was a retrospective study based on the National Health Care Safety Network surveillance definitions of CLABSI caused by Candida species during pre-COVID-19 (October 2017 to February 2020) and COVID-19 (March 2020 to December 2021) periods within a local community hospital. Candida CLABSI incidence per 1,000 central line days was compared between periods using the χ2 test and correlated with COVID-19 inpatient hospitalization rates using Pearson correlation. RESULTS: Overall CLABSI (0.68 vs 1.98 per 1,000, P = .004) and Candida CLABSI incidence (0.06 vs 0.77 per 1,000, P = .003) significantly increased from pre-COVID-19 to COVID-19 periods. There was a significant correlation between COVID-19 ICU hospitalizations and CLABSIs (R = 0.18, P = .048), but not acute care hospitalizations and CLABSIs (R = 0.065, P = .250). Conversely, there was a significant association between COVID-19 acute care hospitalizations and Candida CLABSIs (R = 0.50, P < .001), but not COVID-19 ICU hospitalizations and Candida CLABSIs (R = 0.01, P = .631). CONCLUSIONS: During the COVID-19 pandemic, our facility experienced a significant increase in Candida CLABSI and a significant correlation of Candida CLABSIs with acute care COVID-19 hospitalizations.

A Case of New Delhi Metallo-ß-Lactamase-Producing Enterobacter and a Review of Cases in the United States From January 2009 to September 2022.

Antimicrobial resistance is a growing problem. Novel resistance mechanisms continue to emerge, and the pipeline of antimicrobial development struggles to keep up. Antimicrobial stewardship and proper infection control are key in preventing the spread of these infections. A case of a carbapenem-resistant Enterobacter cloacae complex urinary isolate was identified in an 81-year-old male patient at the San Antonio Veterans Affairs hospital, Texas, USA. The patient was placed on isolation, and further testing of the isolate to other antibiotics requested. The purpose of this study is to analyze the details of reports of such cases and to review at-risk populations and appropriate treatment for resistant organisms.

Flea-Borne Typhus as a COVID-19 Mimic: A Report of Four Cases.

Flea-borne typhus (FBT), due to Rickettsia typhi and R. felis, is an infection causing fever, headache, rash, hepatitis, thrombocytopenia, and diverse organ manifestations. Cough occurs in about 30% of patients with FBT, and chest X-ray abnormalities are seen in 17%. Severe pulmonary manifestations have also been reported in FBT, including adult respiratory distress syndrome and pulmonary embolism. Because of these pulmonary manifestations, FBT can mimic Coronavirus Illness 2019 (COVID-19), a febrile illness with prominent respiratory involvement. Flea-borne typhus and COVID-19 may also have similar laboratory abnormalities, including elevated ferritin, C-reactive protein, and D-dimer. However, elevated transaminase levels, rash, and thrombocytopenia are more common in FBT. Herein, we present four cases of patients with FBT who were initially suspected to have COVID-19. These cases illustrate the problem of availability bias, in which the clinician thinks a particular common condition (COVID-19 in this case) is more prevalent than it actually is.

Eczema Monkeypoxicum in a Female Patient With Atopic Dermatitis.

A female patient with atopic dermatitis who had recently received a tattoo presented with severe right ear pain and several vesiculopustular lesions. Over 1 week, she developed approximately 80 widely distributed lesions. Laboratory testing confirmed mpox (previously monkeypox) virus, and no further lesions developed after initiation of oral tecovirimat.

An electronic health record cohort of Veterans with amyotrophic lateral sclerosis.

Objective: To assemble and characterize an electronic health record (EHR) dataset for a large cohort of US military Veterans diagnosed with ALS (Amyotrophic Lateral Sclerosis). Methods: An EHR dataset for 19,662 Veterans diagnosed with ALS between January 1, 2000 to December 31, 2020 was compiled from the Veterans Health Administration (VHA) EHR database by a query for ICD9 diagnosis (335.20) or ICD10 diagnosis (G12.21) for Amyotrophic Lateral Sclerosis. Results: The cohort is predominantly male (98.94%) and white (72.37%) with a median age at disease onset of 68 years and median survival from the date of diagnosis of 590 days. With the designation of ALS as a compensable illness in 2009, there was a subsequent increase in the number of Veterans diagnosed per year in the VHA, but no change in median survival. The cohort included a greater-than-expected proportion of individuals whose branch of service at the time of separation was the Army. Conclusions: The composition of the cohort reflects the VHA population who are at greatest risk for ALS. The greater than expected proportion of individuals whose branch of service at the time of separation was the Army suggests the possibility of a branch-specific risk factor for ALS.

Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array.

While there is a growing appreciation of three-dimensional (3D) neural tissues (i.e., hydrogel-based, organoids, and spheroids), shown to improve cellular health and network activity to mirror brain-like activity in vivo, functional assessment using current electrophysiology techniques (e.g., planar multi-electrode arrays or patch clamp) has been technically challenging and limited to surface measurements at the bottom or top of the 3D tissue. As next-generation MEAs, specifically 3D MEAs, are being developed to increase the spatial precision across all three dimensions (X, Y, Z), development of improved computational analytical tools to discern region-specific changes within the Z dimension of the 3D tissue is needed. In the present study, we introduce a novel computational analytical pipeline to analyze 3D neural network activity recorded from a "bottom-up" 3D MEA integrated with a 3D hydrogel-based tissue containing human iPSC-derived neurons and primary astrocytes. Over a period of ~6.5 weeks, we describe the development and maturation of 3D neural activity (i.e., features of spiking and bursting activity) within cross sections of the 3D tissue, based on the vertical position of the electrode on the 3D MEA probe, in addition to network activity (identified using synchrony analysis) within and between cross sections. Then, using the sequential addition of postsynaptic receptor antagonists, bicuculline (BIC), 2-amino-5-phosphonovaleric acid (AP-5), and 6-cyano-5-nitroquinoxaline-2,3-dione (CNQX), we demonstrate that networks within and between cross sections of the 3D hydrogel-based tissue show a preference for GABA and/or glutamate synaptic transmission, suggesting differences in the network composition throughout the neural tissue. The ability to monitor the functional dynamics of the entire 3D reconstructed neural tissue is a critical bottleneck; here we demonstrate a computational pipeline that can be implemented in studies to better interpret network activity within an engineered 3D neural tissue and have a better understanding of the modeled organ tissue.

Corrigendum: Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array.

[This corrects the article DOI: 10.3389/fncel.2023.1287089.].

Methicillin-resistant Staphylococcus aureus bacteraemia and endocarditis treated with ceftaroline salvage therapy.

BACKGROUND: One of the newest methicillin-resistant Staphylococcus aureus (MRSA) antibiotics to receive FDA approval is ceftaroline fosamil, a member of a new subclass of cephalosporins with unique activity against MRSA. However, ceftaroline is currently only FDA approved for complicated skin/soft tissue infections and community-acquired pneumonia; there are currently no clinical data regarding its use in MRSA bacteraemia and endocarditis. We report a series of six patients in which ceftaroline was utilized as salvage monotherapy in persistent MRSA bacteraemia or endocarditis. METHODS: Using pharmacy records, 11 ceftaroline-treated patients were identified between January 2011 and November 2011 at University Health System and the South Texas Veterans Health Care System in San Antonio, TX, USA. All cases were reviewed and six patients received ceftaroline therapy for MRSA bacteraemia or endocarditis due to persistent or recurrent bacteraemia while on standard antibiotics (vancomycin or daptomycin). RESULTS: All six patients experienced rapid clearance of their bacteraemia after starting ceftaroline. In the case of endocarditis for which the patient subsequently developed heart failure and required valve replacement, there was no evidence of growth from cultures taken from the excised valve, suggesting sterilization within 13 days of starting ceftaroline. CONCLUSIONS: Ceftaroline exhibits potent anti-MRSA activity in both in vitro and animal studies, including rabbit endocarditis models; however, the lack of clinical data has limited its use in bacteraemia and endovascular infections in humans. We hope that this series serves as an initial stepping stone for further evaluation of this compound for more invasive infections due to MRSA.

COVID-19 outcomes in patients with cancer: Findings from the University of California health system database.

BACKGROUND: The interaction between cancer diagnoses and COVID-19 infection and outcomes is unclear. We leveraged a state-wide, multi-institutional database to assess cancer-related risk factors for poor COVID-19 outcomes. METHODS: We conducted a retrospective cohort study using the University of California Health COVID Research Dataset, which includes electronic health data of patients tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at 17 California medical centers. We identified adults tested for SARS-CoV-2 from 2/1/2020-12/31/2020 and selected a cohort of patients with cancer. We obtained demographic, clinical, cancer type, and antineoplastic therapy data. The primary outcome was hospitalization within 30d after the first positive SARS-CoV-2 test. Secondary outcomes were SARS-CoV-2 positivity and severe COVID-19 (intensive care, mechanical ventilation, or death within 30d after the first positive test). We used multivariable logistic regression to identify cancer-related factors associated with outcomes. RESULTS: We identified 409,462 patients undergoing SARS-CoV-2 testing. Of 49,918 patients with cancer, 1781 (3.6%) tested positive. Patients with cancer were less likely to test positive (RR 0.70, 95% CI: 0.67-0.74, p < 0.001). Among the 1781 SARS-CoV-2-positive patients with cancer, BCR/ABL-negative myeloproliferative neoplasms (RR 2.15, 95% CI: 1.25-3.41, p = 0.007), venetoclax (RR 2.96, 95% CI: 1.14-5.66, p = 0.028), and methotrexate (RR 2.72, 95% CI: 1.10-5.19, p = 0.032) were associated with greater hospitalization risk. Cancer and therapy types were not associated with severe COVID-19. CONCLUSIONS: In this large, diverse cohort, cancer was associated with a decreased risk of SARS-CoV-2 positivity. Patients with BCR/ABL-negative myeloproliferative neoplasm or receiving methotrexate or venetoclax may be at increased risk of hospitalization following SARS-CoV-2 infection. Mechanistic and comparative studies are needed to validate findings.

Dynamic modeling of hospitalized COVID-19 patients reveals disease state-dependent risk factors.

OBJECTIVE: The study sought to investigate the disease state-dependent risk profiles of patient demographics and medical comorbidities associated with adverse outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. MATERIALS AND METHODS: A covariate-dependent, continuous-time hidden Markov model with 4 states (moderate, severe, discharged, and deceased) was used to model the dynamic progression of COVID-19 during the course of hospitalization. All model parameters were estimated using the electronic health records of 1362 patients from ProMedica Health System admitted between March 20, 2020 and December 29, 2020 with a positive nasopharyngeal PCR test for SARS-CoV-2. Demographic characteristics, comorbidities, vital signs, and laboratory test results were retrospectively evaluated to infer a patient's clinical progression. RESULTS: The association between patient-level covariates and risk of progression was found to be disease state dependent. Specifically, while being male, being Black or having a medical comorbidity were all associated with an increased risk of progressing from the moderate disease state to the severe disease state, these same factors were associated with a decreased risk of progressing from the severe disease state to the deceased state. DISCUSSION: Recent studies have not included analyses of the temporal progression of COVID-19, making the current study a unique modeling-based approach to understand the dynamics of COVID-19 in hospitalized patients. CONCLUSION: Dynamic risk stratification models have the potential to improve clinical outcomes not only in COVID-19, but also in a myriad of other acute and chronic diseases that, to date, have largely been assessed only by static modeling techniques.

Dose-dependent consequences of sub-chronic fentanyl exposure on neuron and glial co-cultures.

Fentanyl is one of the most common opioid analgesics administered to patients undergoing surgery or for chronic pain management. While the side effects of chronic fentanyl abuse are recognized (e.g., addiction, tolerance, impairment of cognitive functions, and inhibit nociception, arousal, and respiration), it remains poorly understood what and how changes in brain activity from chronic fentanyl use influences the respective behavioral outcome. Here, we examined the functional and molecular changes to cortical neural network activity following sub-chronic exposure to two fentanyl concentrations, a low (0.01 µM) and high (10 µM) dose. Primary rat co-cultures, containing cortical neurons, astrocytes, and oligodendrocyte precursor cells, were seeded in wells on either a 6-well multi-electrode array (MEA, for electrophysiology) or a 96-well tissue culture plate (for serial endpoint bulk RNA sequencing analysis). Once networks matured (at 28 days in vitro), co-cultures were treated with 0.01 or 10 µM of fentanyl for 4 days and monitored daily. Only high dose exposure to fentanyl resulted in a decline in features of spiking and bursting activity as early as 30 min post-exposure and sustained for 4 days in cultures. Transcriptomic analysis of the complex cultures after 4 days of fentanyl exposure revealed that both the low and high dose induced gene expression changes involved in synaptic transmission, inflammation, and organization of the extracellular matrix. Collectively, the findings of this in vitro study suggest that while neuroadaptive changes to neural network activity at a systems level was detected only at the high dose of fentanyl, transcriptomic changes were also detected at the low dose conditions, suggesting that fentanyl rapidly elicits changes in plasticity.

Dose of trimethoprim-sulfamethoxazole to treat skin and skin structure infections caused by methicillin-resistant Staphylococcus aureus.

We undertook this study to investigate whether treatment with a higher dose of trimethoprim-sulfamethoxazole (TMP/SMX) led to greater clinical resolution in patients with skin and soft tissue infections (SSTIs) caused by methicillin-resistant Staphylococcus aureus (MRSA). A prospective, observational cohort with nested case-control study was performed at a public tertiary health system. Among patients with MRSA SSTIs during the period from May 2008 to September 2008 who received oral monotherapy with TMP/SMX and whose clinical outcome was known, the clinical characteristics and outcomes were compared between patients treated with a high dose of TMP/SMX (320 mg/1,600 mg twice daily) for 7 to 15 days and patients treated with the standard dose of TMP/SMX (160 mg/800 mg twice daily) for 7 to 15 days. In patients with MRSA SSTIs, those treated with the high dose of TMP/SMX (n = 121) had clinical characteristics similar to those of patients treated with the standard dose of TMP/SMX (n = 170). The only exception was a higher proportion of patients with a history of trauma upon admission among the patients treated with the higher dose. The proportion of patients with clinical resolution of infection was not different in the two groups (88/121 [73%] versus 127/170 [75%]; P = 0.79). The lack of significance remained in patients with abscess upon stratified analysis by whether surgical drainage was performed. The study found that patients with MRSA SSTIs treated with the higher dose of TMP/SMX (320/1,600 mg twice daily) for 7 to 15 days had a similar rate of clinical resolution as patients treated with the standard dose of TMP/SMX (160/800 mg twice daily) for 7 to 15 days.