Ceftaroline Fosamil for the Treatment of Methicillin-Resistant Staphylococcus Aureus Bacteremia: A Real-World Comparative Clinical Outcomes Study.

BACKGROUND AND OBJECTIVE: Methicillin-resistant Staphylococcus aureus (MRSA) bacteremia results in substantial morbidity and mortality. As current treatments often lead to unsatisfactory outcomes, evidence guiding alternative treatment options is needed. This study evaluated real-world clinical outcomes of ceftaroline fosamil for the treatment of MRSA bacteremia. METHODS: This retrospective study included adults hospitalized with MRSA bacteremia between 2011 and 2019. Patients were classified according to treatment with ceftaroline fosamil (ceftaroline), vancomycin, or daptomycin: Group 1, ceftaroline; Group 2, vancomycin or daptomycin (without ceftaroline); Group 3, combination therapy with ≥ 2 of these three agents. Clinical outcomes were compared using propensity-score-adjusted odds ratios (ORs) from logistic regression models. RESULTS: Overall, 24,479 patients were included (Group 1, n = 532; Group 2, n = 21,555; Group 3, n = 2392). Mean age was 59.6, 60.8, and 57.4 years in Groups 1, 2, and 3, respectively. Mean post-index treatment length of stay was 8.8, 8.8, and 8.0 days, respectively. The most frequent line of therapy was ceftaroline first-line (42.1%), vancomycin or daptomycin first-line (95.4%), and combination therapy third-line or later (67.8%) in Groups 1, 2, and 3, respectively. Compared with Group 2, Groups 1 and 3 had similar favorable clinical responses {odds ratio [OR] = 1.18 [95% confidence interval (CI) 0.98-1.44], p = 0.08; OR = 1.20 [95% CI 0.97-1.47], p = 0.09, respectively} and were less likely to switch treatment (both p < 0.001). Compared with Group 2, Group 1 was more likely to undergo 30-day all-cause readmission [OR = 1.38 (95% CI 1.06-1.80), p = 0.02], whereas this was less likely for Group 3 [OR = 0.77 (95% CI 0.58-1.00), p = 0.05]. CONCLUSIONS: Patients receiving ceftaroline more often had favorable clinical responses than those receiving vancomycin or daptomycin monotherapy. In the absence of large-scale randomized controlled trials, these real-world data provide insights into the potential role of ceftaroline for treating MRSA bacteremia.

Subphenotypes of self-reported symptoms and outcomes in long COVID: a prospective cohort study with latent class analysis.

OBJECTIVE: To characterise subphenotypes of self-reported symptoms and outcomes (SRSOs) in postacute sequelae of COVID-19 (PASC). DESIGN: Prospective, observational cohort study of subjects with PASC. SETTING: Academic tertiary centre from five clinical referral sources. PARTICIPANTS: Adults with COVID-19 ≥20 days before enrolment and presence of any new self-reported symptoms following COVID-19. EXPOSURES: We collected data on clinical variables and SRSOs via structured telephone interviews and performed standardised assessments with validated clinical numerical scales to capture psychological symptoms, neurocognitive functioning and cardiopulmonary function. We collected saliva and stool samples for quantification of SARS-CoV-2 RNA via quantitative PCR. OUTCOMES MEASURES: Description of PASC SRSOs burden and duration, derivation of distinct PASC subphenotypes via latent class analysis (LCA) and relationship with viral load. RESULTS: We analysed baseline data for 214 individuals with a study visit at a median of 197.5 days after COVID-19 diagnosis. Participants reported ever having a median of 9/16 symptoms (IQR 6-11) after acute COVID-19, with muscle-aches, dyspnoea and headache being the most common. Fatigue, cognitive impairment and dyspnoea were experienced for a longer time. Participants had a lower burden of active symptoms (median 3 (1-6)) than those ever experienced (p<0.001). Unsupervised LCA of symptoms revealed three clinically active PASC subphenotypes: a high burden constitutional symptoms (21.9%), a persistent loss/change of smell and taste (20.6%) and a minimal residual symptoms subphenotype (57.5%). Subphenotype assignments were strongly associated with self-assessments of global health, recovery and PASC impact on employment (p<0.001) as well as referral source for enrolment. Viral persistence (5.6% saliva and 1% stool samples positive) did not explain SRSOs or subphenotypes. CONCLUSIONS: We identified three distinct PASC subphenotypes. We highlight that although most symptoms progressively resolve, specific PASC subpopulations are impacted by either high burden of constitutional symptoms or persistent olfactory/gustatory dysfunction, requiring prospective identification and targeted preventive or therapeutic interventions.

Substantial health and economic burden of COVID-19 during the year after acute illness among US adults at high risk of severe COVID-19.

BACKGROUND: Post-COVID conditions encompass a range of long-term symptoms after SARS-CoV-2 infection. The potential clinical and economic burden in the United States is unclear. We evaluated diagnoses, medications, healthcare use, and medical costs before and after acute COVID-19 illness in US patients at high risk of severe COVID-19. METHODS: Eligible adults were diagnosed with COVID-19 from April 1 to May 31, 2020, had ≥ 1 condition placing them at risk of severe COVID-19, and were enrolled in Optum's de-identified Clinformatics® Data Mart Database for ≥ 12 months before and ≥ 13 months after COVID-19 diagnosis. Percentages of diagnoses, medications, resource use, and costs were calculated during baseline (12 months preceding diagnosis) and the post-acute phase (12 months after the 30-day acute phase of COVID-19). Data were stratified by age and COVID-19 severity. RESULTS: The cohort included 19,558 patients (aged 18-64 y, n = 9381; aged ≥ 65 y, n = 10,177). Compared with baseline, patients during the post-acute phase had increased percentages of blood disorders (16.3%), nervous system disorders (11.1%), and mental and behavioral disorders (7.7%), along with increases in related prescriptions. Overall, there were substantial increases in inpatient and outpatient healthcare utilization, along with a 23.0% increase in medical costs. Changes were greatest among older patients and those admitted to the intensive care unit for acute COVID-19 but were also observed in younger patients and those who did not require COVID-19 hospitalization. CONCLUSIONS: There is a significant clinical and economic burden of post-COVID conditions among US individuals at high risk for severe COVID-19.

Substantial health and economic burden of COVID-19 during the year after acute illness among US adults not at high risk of severe COVID-19.

BACKGROUND: Patients recovering from SARS-CoV-2 infection and acute COVID-19 illness can experience a range of long-term post-acute effects. The potential clinical and economic burden of these outcomes in the USA is unclear. We evaluated diagnoses, medications, healthcare utilization, and medical costs before and after acute COVID-19 illness in US patients who were not at high risk of severe COVID-19. METHODS: This study included eligible adults who were diagnosed with COVID-19 from April 1 to May 31, 2020, who were 18 - 64 years of age, and enrolled within Optum's de-identified Clinformatics® Data Mart Database for 12 months before and 13 months after COVID-19 diagnosis. Patients with any condition or risk factor placing them at high risk of progression to severe COVID-19 were excluded. Percentages of diagnoses, medications, healthcare utilization, and costs were calculated during baseline (12 months preceding diagnosis) and the post-acute phase (12 months after the 30-day acute phase of COVID-19). Data were stratified into 3 cohorts according to disposition during acute COVID-19 illness (i.e., not hospitalized, hospitalized without intensive care unit [ICU] admission, or admitted to the ICU). RESULTS: The study included 3792 patients; 56.5% of patients were men, 44% were White, and 94% did not require hospitalization. Compared with baseline, patients during the post-acute phase had percentage increases in the diagnosis of the following disorders: blood (166%), endocrine and metabolic (123%), nervous system (115%), digestive system (76%), and mental and behavioral (75%), along with increases in related prescriptions. Substantial increases in all measures of healthcare utilization were observed among all 3 cohorts. Total medical costs increased by 178% during the post-acute phase. Those who were hospitalized with or without ICU admission during the acute phase had the greatest increases in comorbidities and healthcare resource utilization. However, the burden was apparent across all cohorts. CONCLUSIONS: As evidenced by resource use in the post-acute phase, COVID-19 places a significant long-term clinical and economic burden among US individuals, even among patients whose acute infection did not merit hospitalization.

Real-World Evidence of the Top 100 Prescribed Drugs in the USA and Their Potential for Drug Interactions with Nirmatrelvir; Ritonavir.

Nirmatrelvir (coadministered with ritonavir as PAXLOVIDTM) reduces the risk of COVID-19-related hospitalizations and all-cause death in individuals with mild-to-moderate COVID-19 at high risk of progression to severe disease. Ritonavir is coadministered as a pharmacokinetic enhancer. However, ritonavir may cause drug-drug interactions (DDIs) due to its interactions with various drug-metabolizing enzymes and transporters, including cytochrome P450 (CYP) 3A, CYP2D6, and P-glycoprotein transporters. To better understand the extent of DDIs (or lack thereof) of nirmatrelvir; ritonavir in a clinical setting, this study used real-world evidence (RWE) from the Optum Clinformatics Data Mart database to identify the top 100 drugs most commonly prescribed to US patients at high risk of progression to severe COVID-19 disease. The top 100 drugs were identified based on total counts associated with drugs prescribed to high-risk patients (i.e., ≥ 1 medical condition associated with an increased risk of severe COVID-19) who were continuously enrolled in the database throughout 2019 and had ≥ 1 prescription claim. Each of the 100 drugs was then assessed for DDI risk based on their metabolism, excretion, and transport pathways identified from available US prescribing and medical literature sources. Seventy drugs identified were not expected to have DDIs with nirmatrelvir; ritonavir, including many cardiovascular agents, anti-infectives, antidiabetic agents, and antidepressants. Conversely, 30 drugs, including corticosteroids, narcotic analgesics, anticoagulants, statins, and sedatives/hypnotics, were expected to cause DDIs with nirmatrelvir; ritonavir. This RWE analysis is complementary to the prescribing information and other DDI management tools for guiding healthcare providers in managing DDIs.

Use of the Postacute Sequelae of COVID-19 Diagnosis Code in Routine Clinical Practice in the US.

Importance: A new International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis code (U09.9 Post COVID-19 condition, unspecified) was introduced by the Centers for Disease Control and Prevention on October 1, 2021. Objective: To examine the use of the U09.9 code and describe concurrently diagnosed conditions to understand physician use of this code in clinical practice. Design, Setting, and Participants: This cohort study of US patients with an ICD-10-CM code for post-COVID-19 condition used deidentified patient-level claims data aggregated by HealthVerity. Children and adolescents (aged 0-17 years) and adults (aged 18-64 and ≥65 years) with a post-COVID-19 condition code were identified between October 1, 2021, and January 31, 2022. To identify a prior COVID-19 diagnosis, 3 months of continuous enrollment (CE) before the post-COVID-19 diagnosis date was required. Main Outcomes and Measures: Presence of the ICD-10-CM U09.9 code. Results: There were 56 143 patients (7723 female patients [61.2%]; mean [SD] age, 47.6 [19.2] years) with a post-COVID-19 diagnosis code, with cases increasing in mid-December 2021 following the trajectory of the Omicron case wave by 3 to 4 weeks. The analysis cohort included 12 622 patients after the 3-month preindex CE criteria was applied. Among this cohort, the median (IQR) age was 49 (35-61) years; however, 1080 (8.6%) were pediatric patients. The U09.9 code was used most often in the outpatient setting, although 305 older adults (14.0%) were inpatients. Only 698 patients (5.5%) had at least 1 of the 5 codes listed as possible concurrent conditions in the coding guidance. Only 8879 patients (70.4%) had a documented acute COVID-19 diagnosis code (569 [52.7%] among children), and the median (IQR) time between acute COVID-19 and post-COVID-19 diagnosis codes was 56 (21-200) days. The most common concurrently coded conditions varied by age; children experienced COVID-19-like symptoms (eg, 207 [19.2%] had cough and 115 [10.6%] had breathing abnormalities), while 459 older adults aged 65 years or older (21.1%) experienced respiratory failure and 189 (8.7%) experienced viral pneumonia. Conclusions and Relevance: This retrospective cohort study found patients with a post-COVID-19 ICD-10-CM diagnosis code following the acute phase of COVID-19 disease among patients of all ages in clinical practice in the US. The use of the U09.9 code encompassed a wide range of conditions. It will be important to monitor how the use of this code changes as the pandemic continues to evolve.

Risk factors in people with mold infections that have spread to different parts of the body: a plain language summary.

WHAT IS THIS SUMMARY ABOUT?: This is a summary of a study originally published in ClinicoEconomics and Outcomes Research. Mold infections spread from one to other parts of the body and can infect other body parts. We need to understand what makes people more likely to get this type of mold infection (called invasive mold infection). This summary may help doctors to understand the risks that can relate to invasive mold infections. WHAT WERE THE RESULTS?: The main risks in people with invasive aspergillosis (shortened to IA) and invasive mucormycosis (shortened to IM) were: ○diabetes (high blood sugar and associated conditions), ○lung disease (such as tuberculosis, chronic obstructive pulmonary disorder), ○blood-related cancers (such as leukemia, lymphoma), and ○solid organ transplant (removing an organ from one person and placing in another person). WHAT DO THE RESULTS OF THE STUDY MEAN?: People with the risks listed above may be more likely to get invasive mold infections. People with these risks should talk to their doctor about invasive mold infections. Being aware of these risks may help doctors to be aware of which people are at risk of invasive mold infections.

Characterizing patients with rare mucormycosis infections using real-world data.

BACKGROUND: Invasive mucormycosis (IM) is a rare and often life-threatening fungal infection, for which clinical and epidemiological understanding is lacking. Electronic health record (EHR) data can be utilized to elucidate large populations of patients with IM to address this unmet need. This study aimed to descriptively assess data on patients with IM using the Optum® EHR dataset. METHODS: US patient data from the Optum® deidentified EHR dataset (2007-2019) were analyzed to identify patients with IM. Patients with hematologic malignancies (HM), at high risk of IM, were selected and sorted by IM diagnosis (ICD9 117.7; ICD10 B46). Demographics, comorbidities/other diagnoses, and treatments were analyzed in patients with IM. RESULTS: In total, 1133 patients with HM and IM were identified. Most were between 40 and 64 years of age, Caucasian, and from the Midwest. Essential primary hypertension (50.31%) was the most common comorbidity. Of the 1133 patients, only 33.72% were prescribed an antifungal treatment. The most common antifungal treatments were fluconazole (24.27%) and posaconazole (16.33%), which may have been prophylactic, and any AmB (15.62%). CONCLUSIONS: A large population of patients with IM were identified, highlighting the potential of analyzing EHR data to investigate epidemiology, diagnosis, and the treatment of apparently rare diseases.

Clinical and Pregnancy Outcomes of Coronavirus Disease 2019 Among Hospitalized Pregnant Women in the United States.

BACKGROUND: Pregnant women with coronavirus disease 2019 (COVID-19) may be at greater risk of poor maternal and pregnancy outcomes. This retrospective analysis reports clinical and pregnancy outcomes among hospitalized pregnant women with COVID-19 in the United States. METHODS: The Premier Healthcare Database-Special Release was used to examine the impact of COVID-19 among pregnant women aged 15-44 years who were hospitalized and who delivered compared with pregnant women without COVID-19. Outcomes evaluated were COVID-19 clinical progression, including the use of supplemental oxygen therapy, intensive care unit admission, critical illness, receipt of invasive mechanical ventilation/extracorporeal membrane oxygenation, maternal death, and pregnancy outcomes, including preterm delivery and stillbirth. RESULTS: Overall, 473 902 hospitalized pregnant women were included, 8584 (1.8%) of whom had a COVID-19 diagnosis (mean age = 28.4 [standard deviation = 6.1] years; 40% Hispanic). The risk of poor clinical and pregnancy outcomes was greater among pregnant women with COVID-19 compared with pregnant women without a COVID-19 diagnosis in 2020; the risk of poor clinical and pregnancy outcomes increased with increasing age. Hispanic and Black non-Hispanic women were consistently observed to have the highest relative risk of experiencing poor clinical or pregnancy outcomes across all age groups. CONCLUSIONS: Overall, COVID-19 had a significant negative impact on maternal health and pregnancy outcomes. These data help inform clinical practice and counseling to pregnant women regarding the risks of COVID-19. Clinical studies evaluating the safety and efficacy of vaccines against severe acute respiratory syndrome coronavirus 2 in pregnant women are urgently needed.

Pandemic-related declines in hospitalization for non-COVID-19-related illness in the United States from January through July 2020.

BACKGROUND: The COVID-19 pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has substantially impacted healthcare utilization worldwide. The objective of this retrospective analysis of a large hospital discharge database was to compare all-cause and cause-specific hospitalizations during the first six months of the pandemic in the United States with the same months in the previous four years. METHODS: Data were collected from all hospitals in the Premier Healthcare Database (PHD) and PHD Special Release reporting hospitalizations from January through July for each year from 2016 through 2020. Hospitalization trends were analyzed stratified by age group, major diagnostic categories (MDCs), and geographic region. RESULTS: The analysis included 286 hospitals from all 9 US Census divisions. The number of all-cause hospitalizations per month was relatively stable from 2016 through 2019 and then fell by 21% (57,281 fewer hospitalizations) between March and April 2020, particularly in hospitalizations for non-respiratory illnesses. From April onward there was a rise in the number of monthly hospitalizations per month. Hospitalizations per month, nationally and in each Census division, decreased for 20 of 25 MDCs between March and April 2020. There was also a decrease in hospitalizations per month for all age groups between March and April 2020 with the greatest decreases in hospitalizations observed for patients 50-64 and ≥65 years of age. CONCLUSIONS: Rates of hospitalization declined substantially during the first months of the COVID-19 pandemic, suggesting delayed routine, elective, and emergency care in the United States. These lapses in care for illnesses not related to COVID-19 may lead to increases in morbidity and mortality for other conditions. Thus, in the current stage of the pandemic, clinicians and public-health officials should work, not only to prevent SARS-CoV-2 transmission, but also to ensure that care for non-COVID-19 conditions is not delayed.