Casey Morrell, Kristina McClanahan, Lauren Daniel, James Burks, Argentina Charles, Ashley Marin, Jeanne Negley, Melanie Roderick, Carolyn Stover
Background: Carbapenem-resistant Acinetobacter (CRA) bacteria are an urgent public health threat. Accurate and timely testing of CRA is important for proper infection control practices to minimize spread. In 2017, the CDC estimated 8,500 CRA cases among hospitalized patients, 700 deaths, and $281 million in attributable healthcare costs. Treatment options are extremely limited for carbapenem-resistant Acinetobacter baumannii (CRAB) infections, making CRAB a unique concern. Colonization screening is a valuable tool for containment but requires sampling of 4 body sites. Identifying a reliable specimen collection site for CRAB is important to inform public health recommendations as screening can cost healthcare facilities valuable time and resources. Methods: Results of all screening specimens of patients with at least 1 site positive for CRAB on a unique collection date were extracted from the Southeast Regional data of Antimicrobial Resistance Lab Network (SEARLN) data. Non-CRAB screening and screenings that did not yield at least 1 positive result on a single collection date were excluded. We also limited our data to include only the following screening sites, which have been validated by the Tennessee Department of Health’s State Public Health Laboratory: axilla and groin, rectal, sputum, and wound. For each specimen source, we calculated the percentage of positive specimen among CRAB-colonized patients. Data were extracted and analyzed using SAS version 9.4 software. Results: The SEARLN data contained 594 CRAB screening specimens collected over 4 years, 2018 through 2021, and 486 of those specimens yielded CRAB. For CRAB-colonized patients screened in this study, wound specimens had the highest positivity rate at 93.4% (95% CI, 89.9%–96.9%) of samples culturing CRAB. Sputum followed at 87.7%, then axilla and groin at 77.6% and rectal at 59.7%. Conclusions: Wound specimens produced the highest proportion of positive cultures among CRAB-positive patients, making them the sample type with the highest prevalence in our study. For healthcare facilities with limited time and resources seeking to optimize their CRAB screening process, wound specimens may be the most reliable single site for detecting CRAB colonization in patients with an open wound. When a wound is not present, sputum may be a good alternative single-source collection site. More research should be conducted before CRAB screening recommendations are updated. Disclosures: None
{"title":"Assessment of carbapenem-resistant <i>Acinetobacter baumannii</i>–colonized patients: Which specimens produce the highest yield?","authors":"Casey Morrell, Kristina McClanahan, Lauren Daniel, James Burks, Argentina Charles, Ashley Marin, Jeanne Negley, Melanie Roderick, Carolyn Stover","doi":"10.1017/ash.2023.370","DOIUrl":"https://doi.org/10.1017/ash.2023.370","url":null,"abstract":"Background: Carbapenem-resistant Acinetobacter (CRA) bacteria are an urgent public health threat. Accurate and timely testing of CRA is important for proper infection control practices to minimize spread. In 2017, the CDC estimated 8,500 CRA cases among hospitalized patients, 700 deaths, and $281 million in attributable healthcare costs. Treatment options are extremely limited for carbapenem-resistant Acinetobacter baumannii (CRAB) infections, making CRAB a unique concern. Colonization screening is a valuable tool for containment but requires sampling of 4 body sites. Identifying a reliable specimen collection site for CRAB is important to inform public health recommendations as screening can cost healthcare facilities valuable time and resources. Methods: Results of all screening specimens of patients with at least 1 site positive for CRAB on a unique collection date were extracted from the Southeast Regional data of Antimicrobial Resistance Lab Network (SEARLN) data. Non-CRAB screening and screenings that did not yield at least 1 positive result on a single collection date were excluded. We also limited our data to include only the following screening sites, which have been validated by the Tennessee Department of Health’s State Public Health Laboratory: axilla and groin, rectal, sputum, and wound. For each specimen source, we calculated the percentage of positive specimen among CRAB-colonized patients. Data were extracted and analyzed using SAS version 9.4 software. Results: The SEARLN data contained 594 CRAB screening specimens collected over 4 years, 2018 through 2021, and 486 of those specimens yielded CRAB. For CRAB-colonized patients screened in this study, wound specimens had the highest positivity rate at 93.4% (95% CI, 89.9%–96.9%) of samples culturing CRAB. Sputum followed at 87.7%, then axilla and groin at 77.6% and rectal at 59.7%. Conclusions: Wound specimens produced the highest proportion of positive cultures among CRAB-positive patients, making them the sample type with the highest prevalence in our study. For healthcare facilities with limited time and resources seeking to optimize their CRAB screening process, wound specimens may be the most reliable single site for detecting CRAB colonization in patients with an open wound. When a wound is not present, sputum may be a good alternative single-source collection site. More research should be conducted before CRAB screening recommendations are updated. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Katryna Gouin, Stephen Creasy, Mary Beckerson, Marti Wdowicki, Lauri Hicks, Sarah Kabbani
Background: Antibiotic use (AU) data are needed to improve prescribing in long-term care facilities (LTCFs). CMS requires AU tracking in LTCFs (effective 2017). Although most LTCFs have limited resources for AU tracking, LTCFs contract with LTCF pharmacies to dispense, monitor, and review medications. The objective of our analysis was to report LTCF antibiotic prescribing and characterize temporal changes from 2013 to 2021. Methods: We estimated annual systemic AU rates using prescription dispenses and resident census data from PharMerica, a LTCF-pharmacy services provider that covers ~20% of LTCFs nationwide, although the number of LTCFs and residents serviced by PharMerica varied over time (Fig. 1). We included LTCFs with ≥4 months of antibiotic dispensing and 12 months of census data. We identified courses by collapsing the same drug dispensed to the same resident within 3 days of the preceding end date. Course duration was calculated as the difference between the end and dispense dates. We reported yearly AU rates as courses per 1,000 residents and days of therapy (DOT) per 1,000 resident days from 2013 to 2021. We compared AU rates (percentage change) and antibiotic courses by class and agent (absolute percent difference) between 2013 and 2021. Results: From 2013 to 2021, AU course rates reported as antibiotic courses per 1,000 residents decreased (percentage change, −28%), with a notable increase in 2020 (Fig. 1). However, the median course duration remained the same (Table 1). The AU decline was mostly driven by decreases in fluoroquinolone courses (absolute difference, −10%, most commonly levofloxacin) and macrolide courses (−2%, most commonly azithromycin) (Figs. 2 and 3). Increases in cephalosporin courses (absolute difference, +7%, most commonly cephalexin) and tetracycline courses (+5%, most commonly doxycycline) were also observed (Figs. 2 and 3). During this period, AU DOT rates reported as DOT per 1,000 resident days decreased (percentage change, −13%) (Table 1). Conclusions: The LTCF AU rates, especially for fluoroquinolones, have decreased in recent years with associated shifts in the distribution of antibiotic classes. This finding may be due to CMS stewardship requirements and increased awareness of adverse events, including the FDA fluoroquinolone warnings. The observed increase in 2020 could be secondary to changes in prescribing practices and resident population during the COVID-19 pandemic. Opportunities to improve prescribing in LTCFs include optimizing treatment duration and leveraging LTCF-pharmacy resources to provide stewardship expertise and support AU tracking and reporting. Disclosures: None
{"title":"Changes in US long-term care facility antibiotic prescribing, 2013–2021","authors":"Katryna Gouin, Stephen Creasy, Mary Beckerson, Marti Wdowicki, Lauri Hicks, Sarah Kabbani","doi":"10.1017/ash.2023.385","DOIUrl":"https://doi.org/10.1017/ash.2023.385","url":null,"abstract":"Background: Antibiotic use (AU) data are needed to improve prescribing in long-term care facilities (LTCFs). CMS requires AU tracking in LTCFs (effective 2017). Although most LTCFs have limited resources for AU tracking, LTCFs contract with LTCF pharmacies to dispense, monitor, and review medications. The objective of our analysis was to report LTCF antibiotic prescribing and characterize temporal changes from 2013 to 2021. Methods: We estimated annual systemic AU rates using prescription dispenses and resident census data from PharMerica, a LTCF-pharmacy services provider that covers ~20% of LTCFs nationwide, although the number of LTCFs and residents serviced by PharMerica varied over time (Fig. 1). We included LTCFs with ≥4 months of antibiotic dispensing and 12 months of census data. We identified courses by collapsing the same drug dispensed to the same resident within 3 days of the preceding end date. Course duration was calculated as the difference between the end and dispense dates. We reported yearly AU rates as courses per 1,000 residents and days of therapy (DOT) per 1,000 resident days from 2013 to 2021. We compared AU rates (percentage change) and antibiotic courses by class and agent (absolute percent difference) between 2013 and 2021. Results: From 2013 to 2021, AU course rates reported as antibiotic courses per 1,000 residents decreased (percentage change, −28%), with a notable increase in 2020 (Fig. 1). However, the median course duration remained the same (Table 1). The AU decline was mostly driven by decreases in fluoroquinolone courses (absolute difference, −10%, most commonly levofloxacin) and macrolide courses (−2%, most commonly azithromycin) (Figs. 2 and 3). Increases in cephalosporin courses (absolute difference, +7%, most commonly cephalexin) and tetracycline courses (+5%, most commonly doxycycline) were also observed (Figs. 2 and 3). During this period, AU DOT rates reported as DOT per 1,000 resident days decreased (percentage change, −13%) (Table 1). Conclusions: The LTCF AU rates, especially for fluoroquinolones, have decreased in recent years with associated shifts in the distribution of antibiotic classes. This finding may be due to CMS stewardship requirements and increased awareness of adverse events, including the FDA fluoroquinolone warnings. The observed increase in 2020 could be secondary to changes in prescribing practices and resident population during the COVID-19 pandemic. Opportunities to improve prescribing in LTCFs include optimizing treatment duration and leveraging LTCF-pharmacy resources to provide stewardship expertise and support AU tracking and reporting. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: In the United States, pneumonia causes >100,000 pediatric hospitalizations annually. On November 4, 2022, the CDC issued a Heath Advisory concerning an upcoming surge of respiratory illnesses including SARS-CoV-2, influenza, and respiratory syncytial virus (RSV). Differentiating between viral and bacterial causes is challenging and can lead to antimicrobial overuse. Currently, tools are being developed to distinguish between viral and bacterial pneumonia. The VALS-DANCE Pneumonia Etiology Predictor (PEP) provides clinical scoring criteria (Fig. 1) to determine probable cause of pneumonia with 93.1% sensitivity for bacterial pneumonia. Scores >11 have a >25% likelihood of having bacterial etiology. Given that antimicrobial exposure increases resistance rates, disrupts natural flora, and increases the risk of side effects, a core goal of researchers is to develop ways to promote stewardship and reduce inappropriate use. We assessed the patterns of use for antimicrobials in pediatric patients admitted with pneumonia at our institution. Methods: This retrospective review included pediatric cases admitted to an urban safety-net community hospital from July 22, 2022, to December 16, 2022. A daily list of all patients receiving antimicrobials was reviewed, and pediatric patients with diagnosis of a respiratory infection were included. Patients with additional indications for antimicrobial therapy, diagnosis of bronchitis, incomplete records, or without complete information were excluded from the scoring criteria. The primary objective was to assess the appropriateness of antimicrobial use for pneumonia, defined as use consistent with PEP scoring recommendations. Results: Of 53 patients reviewed, 37 met inclusion criteria. Of 37 patients, 22 (59.5%) met study criteria for appropriate therapy. The 15 patients (40.5%) who were inappropriate for treatment received an average of 4.67 ± 1.91 days of antibiotics. Of these 15 patients, 11 (73.3%) also had a positive viral test, further increasing the likelihood of a viral etiology. This subgroup had an average antibiotic exposure of 4.27 ± 1.79 days. Documented rationale for therapy included severity of illness (4 of 11), radiograph consolidation (4 of 11), and provider disagreement with radiograph interpretation (3 of 11). Conclusions: Pediatric respiratory infections represent a significant opportunity for antimicrobial stewardship. In this study, as many as 40% of pediatric patients may have received unnecessary antibiotic exposure. Use of the VALS-DANCE criteria may help clinicians identify patients with low likelihood of bacterial infection and reduce antimicrobial use. The national surge of viral infections serves to highlight the vital importance of appropriate diagnostic stewardship. Disclosure: None
{"title":"Inpatient pediatric antimicrobial use for respiratory infections during the RSV surge","authors":"Aaron Hunt, Rodrigo Burgos, Alfredo Mena Lora","doi":"10.1017/ash.2023.213","DOIUrl":"https://doi.org/10.1017/ash.2023.213","url":null,"abstract":"Background: In the United States, pneumonia causes >100,000 pediatric hospitalizations annually. On November 4, 2022, the CDC issued a Heath Advisory concerning an upcoming surge of respiratory illnesses including SARS-CoV-2, influenza, and respiratory syncytial virus (RSV). Differentiating between viral and bacterial causes is challenging and can lead to antimicrobial overuse. Currently, tools are being developed to distinguish between viral and bacterial pneumonia. The VALS-DANCE Pneumonia Etiology Predictor (PEP) provides clinical scoring criteria (Fig. 1) to determine probable cause of pneumonia with 93.1% sensitivity for bacterial pneumonia. Scores >11 have a >25% likelihood of having bacterial etiology. Given that antimicrobial exposure increases resistance rates, disrupts natural flora, and increases the risk of side effects, a core goal of researchers is to develop ways to promote stewardship and reduce inappropriate use. We assessed the patterns of use for antimicrobials in pediatric patients admitted with pneumonia at our institution. Methods: This retrospective review included pediatric cases admitted to an urban safety-net community hospital from July 22, 2022, to December 16, 2022. A daily list of all patients receiving antimicrobials was reviewed, and pediatric patients with diagnosis of a respiratory infection were included. Patients with additional indications for antimicrobial therapy, diagnosis of bronchitis, incomplete records, or without complete information were excluded from the scoring criteria. The primary objective was to assess the appropriateness of antimicrobial use for pneumonia, defined as use consistent with PEP scoring recommendations. Results: Of 53 patients reviewed, 37 met inclusion criteria. Of 37 patients, 22 (59.5%) met study criteria for appropriate therapy. The 15 patients (40.5%) who were inappropriate for treatment received an average of 4.67 ± 1.91 days of antibiotics. Of these 15 patients, 11 (73.3%) also had a positive viral test, further increasing the likelihood of a viral etiology. This subgroup had an average antibiotic exposure of 4.27 ± 1.79 days. Documented rationale for therapy included severity of illness (4 of 11), radiograph consolidation (4 of 11), and provider disagreement with radiograph interpretation (3 of 11). Conclusions: Pediatric respiratory infections represent a significant opportunity for antimicrobial stewardship. In this study, as many as 40% of pediatric patients may have received unnecessary antibiotic exposure. Use of the VALS-DANCE criteria may help clinicians identify patients with low likelihood of bacterial infection and reduce antimicrobial use. The national surge of viral infections serves to highlight the vital importance of appropriate diagnostic stewardship. Disclosure: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xuping Yan, Christopher McCoy, Ryan Chapin, Matthew Lee, Howard Gold, Kendall Donohoe
Background: The off-target effects linezolid have the potential to cause serotonin syndrome when given in conjunction with serotonergic agents. Despite package insert labeling as a contraindication, several postmarketing studies have demonstrated a low incidence of serotonin syndrome with the concomitant use of linezolid and other serotonergic agents. Linezolid provides a convenient oral option for gram-positive infections. However, due to concerns for serotonin syndrome, the use of linezolid is sometimes avoided. Methods: We performed a single-center, retrospective, medical record review of all adult inpatients from September 2021 to September 2022. Patients included had 1 administration of linezolid and 1 inpatient administration of a selective serotonin reuptake inhibitor (SSRI) or serotonin and norepinephrine reuptake inhibitor (SNRI) within 14 days. The primary outcome was the incidence of serotonin syndrome as defined by the Hunter serotonin toxicity criteria, which were retrospectively applied to each patient based on medical-record documentation. We compared patients receiving 1 versus multiple serotonergic agents. Secondary outcomes included duration of hospitalization and adverse outcomes based on concerns for serotonin syndrome such as need for rescue, ICU admission, or change in medication. Results: Of the 50 included patients from a convenience sample, 27 (54%) were on linezolid and >1 serotonergic agent. Patients had similar baseline characteristics (Table 1). The most common concomitant agent used was an SSRI. Other agents that predispose patients to serotonin syndrome included opioid analgesics and other classes of antidepressants (Fig. 1). Serotonin syndrome occurred within 48 hours in 1 patient on an SNRI and a continuous fentanyl drip. There was no need for rescue or ICU admission due to serotonin syndrome. No patients were readmitted due to serotonin syndrome, and no differences were observed in hospital lengths of stay. Conclusions: Exposure to a single serotonergic agent combined with receipt of linezolid was not associated with any cases of serotonin syndrome. Exposure to multiple serotonergic agents was not associated with a high incidence of serotonin syndrome. This small series supports previous reports demonstrating relative safety of linezolid given with serotonergic agents and encourages review of interruptive drug–drug interaction alerts for linezolid within the electronic ordering system. Disclosures: None
{"title":"Serotonergic agents and linezolid: Impact of exposure to more than one agent concomitantly on risk of adverse effects","authors":"Xuping Yan, Christopher McCoy, Ryan Chapin, Matthew Lee, Howard Gold, Kendall Donohoe","doi":"10.1017/ash.2023.260","DOIUrl":"https://doi.org/10.1017/ash.2023.260","url":null,"abstract":"Background: The off-target effects linezolid have the potential to cause serotonin syndrome when given in conjunction with serotonergic agents. Despite package insert labeling as a contraindication, several postmarketing studies have demonstrated a low incidence of serotonin syndrome with the concomitant use of linezolid and other serotonergic agents. Linezolid provides a convenient oral option for gram-positive infections. However, due to concerns for serotonin syndrome, the use of linezolid is sometimes avoided. Methods: We performed a single-center, retrospective, medical record review of all adult inpatients from September 2021 to September 2022. Patients included had 1 administration of linezolid and 1 inpatient administration of a selective serotonin reuptake inhibitor (SSRI) or serotonin and norepinephrine reuptake inhibitor (SNRI) within 14 days. The primary outcome was the incidence of serotonin syndrome as defined by the Hunter serotonin toxicity criteria, which were retrospectively applied to each patient based on medical-record documentation. We compared patients receiving 1 versus multiple serotonergic agents. Secondary outcomes included duration of hospitalization and adverse outcomes based on concerns for serotonin syndrome such as need for rescue, ICU admission, or change in medication. Results: Of the 50 included patients from a convenience sample, 27 (54%) were on linezolid and >1 serotonergic agent. Patients had similar baseline characteristics (Table 1). The most common concomitant agent used was an SSRI. Other agents that predispose patients to serotonin syndrome included opioid analgesics and other classes of antidepressants (Fig. 1). Serotonin syndrome occurred within 48 hours in 1 patient on an SNRI and a continuous fentanyl drip. There was no need for rescue or ICU admission due to serotonin syndrome. No patients were readmitted due to serotonin syndrome, and no differences were observed in hospital lengths of stay. Conclusions: Exposure to a single serotonergic agent combined with receipt of linezolid was not associated with any cases of serotonin syndrome. Exposure to multiple serotonergic agents was not associated with a high incidence of serotonin syndrome. This small series supports previous reports demonstrating relative safety of linezolid given with serotonergic agents and encourages review of interruptive drug–drug interaction alerts for linezolid within the electronic ordering system. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kelly Jackson, Sydney Resler, Joelle Nadle, Susan Petit, Susan Ray, Lee Harrison, Ruth Lynfield, Kathryn Como-Sabetti, Carmen Bernu, Ghinwa Dumyati, Marissa Tracy, William Schaffner, Holly Biggs, Isaac See
Background: Previous analyses describing the relationship between SARS-CoV-2 infection and Staphylococcus aureus have focused on hospital-onset S. aureus infections occurring during COVID-19 hospitalizations. Because most invasive S. aureus (iSA) infections are community-onset (CO), we characterized CO iSA cases with a recent positive SARS-CoV-2 test (coinfection). Methods: We analyzed CDC Emerging Infections Program active, population- and laboratory-based iSA surveillance data among adults during March 1–December 31, 2020, from 11 counties in 7 states. The iSA cases ( S. aureus isolation from a normally sterile site in a surveillance area resident) were considered CO if culture was obtained <3 days after hospital admission. Coinfection was defined as first positive SARS-CoV-2 test ≤14 days before the initial iSA culture. We explored factors independently associated with SARS-CoV-2 coinfection versus no prior positive SARS-CoV-2 test among CO iSA cases through a multivariable logistic regression model (using demographic, healthcare exposure, and underlying condition variables with P<0.25 in univariate analysis) and examined differences in outcomes through descriptive analysis. Results: Overall, 3,908 CO iSA cases were reported, including 138 SARS-CoV-2 coinfections (3.5%); 58.0% of coinfections had iSA culture and the first positive SARS-CoV-2 test on the same day (Fig. 1). In univariate analysis, neither methicillin resistance (44.2% with coinfection vs 36.5% without; P = .06) nor race and ethnicity differed significantly between iSA cases with and without SARS-CoV-2 coinfection ( P = .93 for any association between race and ethnicity and coinfection), although iSA cases with coinfection were older (median age, 72 vs 60 years , P<0.01) and more often female (46.7% vs 36.3%, P=0.01). In multivariable analysis, significant associations with SARS-CoV-2 coinfection included older age, female sex, previous location in a long-term care facility (LTCF) or hospital, presence of a central venous catheter (CVC), and diabetes (Figure 2). Two-thirds of co-infection cases had ≥1 of the following characteristics: age > 73 years, LTCF residence 3 days before iSA culture, and/or CVC present any time during the 2 days before iSA culture. More often, iSA cases with SARS-CoV-2 coinfection were admitted to the intensive care unit ≤2 days after iSA culture (37.7% vs 23.3%, P<0.01) and died (33.3% vs 11.3%, P<0.01). Conclusions: CO iSA patients with SARS-CoV-2 coinfection represent a small proportion of CO iSA cases and mostly involve a limited number of factors related to likelihood of acquiring SARS-CoV-2 and iSA. Although CO iSA patients with SARS-CoV-2 coinfection had more severe outcomes, additional research is needed to understand how much of this difference is related to differences in patient characteristics. Disclosures: None
背景:先前描述SARS-CoV-2感染与金黄色葡萄球菌之间关系的分析主要集中在COVID-19住院期间发生的住院性金黄色葡萄球菌感染。由于大多数侵袭性金黄色葡萄球菌(iSA)感染是社区发病的(CO)，我们将CO iSA病例描述为近期SARS-CoV-2检测阳性(合并感染)。方法:我们分析了美国7个州11个县2020年3月1日至12月31日期间CDC新兴感染项目活跃的、基于人群和实验室的成人iSA监测数据。如果住院3天后进行培养，则iSA病例(从监测区居民的正常无菌地点分离出金黄色葡萄球菌)被认为是CO。合并感染定义为首次SARS-CoV-2检测阳性≤首次iSA培养前14天。我们通过多变量logistic回归模型(使用人口统计学、医疗保健暴露和潜在条件变量，单变量分析采用P<0.25)，探索与CO - iSA病例中SARS-CoV-2合并感染与先前未进行SARS-CoV-2阳性检测独立相关的因素，并通过描述性分析检查结果的差异。结果:共报告coisa病例3908例，其中SARS-CoV-2合并感染138例(3.5%);58.0%的合并感染患者在同一天进行了iSA培养和首次SARS-CoV-2检测阳性(图1)。在单因素分析中，合并感染患者的甲氧西林耐药性(44.2% vs 36.5%;合并SARS-CoV-2感染的iSA病例与未合并SARS-CoV-2感染的iSA病例之间没有种族和民族差异(种族和民族与合并感染之间的任何关联P= 0.93)，尽管合并感染的iSA病例年龄较大(中位年龄，72岁vs 60岁，P<0.01)，并且更多为女性(46.7% vs 36.3%， P=0.01)。在多变量分析中，与SARS-CoV-2合并感染相关的显著因素包括年龄较大、女性、以前在长期护理机构(LTCF)或医院的位置、是否存在中心静脉导管(CVC)和糖尿病(图2)。三分之二的合并感染病例具有以下特征中的≥1项:年龄>73岁，LTCF居住在iSA培养前3天，和/或CVC出现在iSA培养前2天的任何时间。iSA合并SARS-CoV-2感染的病例在iSA培养后≤2天入院重症监护(37.7% vs 23.3%， P<0.01)并死亡(33.3% vs 11.3%， P<0.01)。结论:CO - iSA合并SARS-CoV-2感染的患者占CO - iSA病例的一小部分，主要涉及与获得SARS-CoV-2和iSA可能性相关的有限因素。虽然合并SARS-CoV-2感染的CO iSA患者有更严重的结果，但需要进一步的研究来了解这种差异在多大程度上与患者特征的差异有关。披露:没有
{"title":"Factors associated with SARS-CoV-2 and community-onset invasive <i>Staphylococcus aureus</i> coinfection, 2020","authors":"Kelly Jackson, Sydney Resler, Joelle Nadle, Susan Petit, Susan Ray, Lee Harrison, Ruth Lynfield, Kathryn Como-Sabetti, Carmen Bernu, Ghinwa Dumyati, Marissa Tracy, William Schaffner, Holly Biggs, Isaac See","doi":"10.1017/ash.2023.342","DOIUrl":"https://doi.org/10.1017/ash.2023.342","url":null,"abstract":"Background: Previous analyses describing the relationship between SARS-CoV-2 infection and Staphylococcus aureus have focused on hospital-onset S. aureus infections occurring during COVID-19 hospitalizations. Because most invasive S. aureus (iSA) infections are community-onset (CO), we characterized CO iSA cases with a recent positive SARS-CoV-2 test (coinfection). Methods: We analyzed CDC Emerging Infections Program active, population- and laboratory-based iSA surveillance data among adults during March 1–December 31, 2020, from 11 counties in 7 states. The iSA cases ( S. aureus isolation from a normally sterile site in a surveillance area resident) were considered CO if culture was obtained <3 days after hospital admission. Coinfection was defined as first positive SARS-CoV-2 test ≤14 days before the initial iSA culture. We explored factors independently associated with SARS-CoV-2 coinfection versus no prior positive SARS-CoV-2 test among CO iSA cases through a multivariable logistic regression model (using demographic, healthcare exposure, and underlying condition variables with P<0.25 in univariate analysis) and examined differences in outcomes through descriptive analysis. Results: Overall, 3,908 CO iSA cases were reported, including 138 SARS-CoV-2 coinfections (3.5%); 58.0% of coinfections had iSA culture and the first positive SARS-CoV-2 test on the same day (Fig. 1). In univariate analysis, neither methicillin resistance (44.2% with coinfection vs 36.5% without; P = .06) nor race and ethnicity differed significantly between iSA cases with and without SARS-CoV-2 coinfection ( P = .93 for any association between race and ethnicity and coinfection), although iSA cases with coinfection were older (median age, 72 vs 60 years , P<0.01) and more often female (46.7% vs 36.3%, P=0.01). In multivariable analysis, significant associations with SARS-CoV-2 coinfection included older age, female sex, previous location in a long-term care facility (LTCF) or hospital, presence of a central venous catheter (CVC), and diabetes (Figure 2). Two-thirds of co-infection cases had ≥1 of the following characteristics: age > 73 years, LTCF residence 3 days before iSA culture, and/or CVC present any time during the 2 days before iSA culture. More often, iSA cases with SARS-CoV-2 coinfection were admitted to the intensive care unit ≤2 days after iSA culture (37.7% vs 23.3%, P<0.01) and died (33.3% vs 11.3%, P<0.01). Conclusions: CO iSA patients with SARS-CoV-2 coinfection represent a small proportion of CO iSA cases and mostly involve a limited number of factors related to likelihood of acquiring SARS-CoV-2 and iSA. Although CO iSA patients with SARS-CoV-2 coinfection had more severe outcomes, additional research is needed to understand how much of this difference is related to differences in patient characteristics. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Hand-hygiene technology (HHT) intends to monitor and promote hand washing by healthcare workers, a critical measure of infection control. Healthcare worker noncompliance with HHT is a major limitation to its implementation and utility in clinical settings. We assessed perspectives on HHT in an academic hospital system. Methods: Hand-hygiene team members created an anonymous, 37-question, Likert-scale survey to assess healthcare worker attitudes toward HHT. Surveys targeted nursing staff, advanced practice providers, care partners, and internal medicine physicians. Clinical coordinators from 5 distinct nursing units and 1 physician department emailed surveys to eligible employees. Research coordinators and clinical coordinators also posted a QR code for survey fliers at nursing stations. Results: Overall, 120 surveys were completed. Most surveys were completed by nurses and physicians (66.4% and 14.0%). Most respondents (67.5%) do not find HHT useful. Additionally, 78.3% of respondents believe that HHT does not accurately record hand-washing events. Most (78.3%) do not like using HHT, and 75.8% find it annoying. Only 10.8% believe that patient care suffers because of HHT. Conclusions: Most healthcare workers dislike the HHT badges, primarily due to perceived inaccuracies, lack of utility, burden of use, and pressure to comply. Distrust and effect on patient care do not appear to be substantial factors contributing to negative perceptions of HHT. Weaknesses of the study include overrepresentation of nursing staff and potential bias because respondents may have provided exceptionally negative responses believing it could lead to the removal of HHT. Disclosures: None
{"title":"Addressing frontline healthcare worker perspectives on hand-hygiene monitoring badges","authors":"Tucker Smith, Olivia Hess, Rachel Pryor, Michelle Doll, Gonzalo Bearman","doi":"10.1017/ash.2023.321","DOIUrl":"https://doi.org/10.1017/ash.2023.321","url":null,"abstract":"Background: Hand-hygiene technology (HHT) intends to monitor and promote hand washing by healthcare workers, a critical measure of infection control. Healthcare worker noncompliance with HHT is a major limitation to its implementation and utility in clinical settings. We assessed perspectives on HHT in an academic hospital system. Methods: Hand-hygiene team members created an anonymous, 37-question, Likert-scale survey to assess healthcare worker attitudes toward HHT. Surveys targeted nursing staff, advanced practice providers, care partners, and internal medicine physicians. Clinical coordinators from 5 distinct nursing units and 1 physician department emailed surveys to eligible employees. Research coordinators and clinical coordinators also posted a QR code for survey fliers at nursing stations. Results: Overall, 120 surveys were completed. Most surveys were completed by nurses and physicians (66.4% and 14.0%). Most respondents (67.5%) do not find HHT useful. Additionally, 78.3% of respondents believe that HHT does not accurately record hand-washing events. Most (78.3%) do not like using HHT, and 75.8% find it annoying. Only 10.8% believe that patient care suffers because of HHT. Conclusions: Most healthcare workers dislike the HHT badges, primarily due to perceived inaccuracies, lack of utility, burden of use, and pressure to comply. Distrust and effect on patient care do not appear to be substantial factors contributing to negative perceptions of HHT. Weaknesses of the study include overrepresentation of nursing staff and potential bias because respondents may have provided exceptionally negative responses believing it could lead to the removal of HHT. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135219822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Yang, Leigh Cressman, Keith Hamilton, Lauren Dutcher
Background: Inappropriate antibiotic use for community-acquired pneumonia (CAP) is common. Although antibiotic stewardship activities require real-time, accurate identification of patients being treated for CAP, there are few reliable methods to identify such patients using the electronic health record (EHR). We conducted a retrospective study to assess the performance of provider-selected antibiotic indication in identifying patients being treated for CAP among a cohort of hospitalized adults. Methods: We randomly selected 440 patients from a cohort of patients who received at least 1 systemic antibiotic within 48 hours of admission between January 1, 2019, and December 31, 2021, at 3 acute-care hospitals. The reference standard for treatment of CAP was defined as intention to treat for pneumonia by inpatient provider(s) within 48 hours of admission, as assessed by chart review of provider notes. Treatment for pneumonia using any terminology except with “hospital-acquired pneumonia” (HAP) or “ventilator-associated pneumonia” (VAP) were counted. Provider-selected indication of CAP (in an antibiotic order) was compared against this reference standard; sensitivity, specificity, and positive and negative predictive values were calculated. Performance characteristics of International Classification of Disease, Tenth Revision (ICD-10) codes for pneumonia in identifying CAP patients were assessed against the same reference standard. A secondary analysis including terms HAP and VAP in the reference standard was performed. Results: Provider-selected antibiotic indication for CAP had a sensitivity of 64.4%, specificity of 96.3%, positive predictive value (PPV) of 73.1%, and negative predictive value (NPV) of 96.1%, giving comparable performance to ICD-10 codes (Table 1). Of those with 21 false-negative results, 13 (61.9%) had a healthcare-associated lower respiratory tract infection and 14 (66.7%) had sepsis indicated in at least 1 antibiotic order. Conclusions: Provider-selected antibiotic indication showed moderate sensitivity and high specificity for identifying CAP-treated cases. Importantly, use of this method can be deployed for real-time antibiotic stewardship interventions for CAP. Disclosures: None
{"title":"Electronic health record–based identification of inpatients receiving antibiotic treatment for community-acquired pneumonia","authors":"David Yang, Leigh Cressman, Keith Hamilton, Lauren Dutcher","doi":"10.1017/ash.2023.253","DOIUrl":"https://doi.org/10.1017/ash.2023.253","url":null,"abstract":"Background: Inappropriate antibiotic use for community-acquired pneumonia (CAP) is common. Although antibiotic stewardship activities require real-time, accurate identification of patients being treated for CAP, there are few reliable methods to identify such patients using the electronic health record (EHR). We conducted a retrospective study to assess the performance of provider-selected antibiotic indication in identifying patients being treated for CAP among a cohort of hospitalized adults. Methods: We randomly selected 440 patients from a cohort of patients who received at least 1 systemic antibiotic within 48 hours of admission between January 1, 2019, and December 31, 2021, at 3 acute-care hospitals. The reference standard for treatment of CAP was defined as intention to treat for pneumonia by inpatient provider(s) within 48 hours of admission, as assessed by chart review of provider notes. Treatment for pneumonia using any terminology except with “hospital-acquired pneumonia” (HAP) or “ventilator-associated pneumonia” (VAP) were counted. Provider-selected indication of CAP (in an antibiotic order) was compared against this reference standard; sensitivity, specificity, and positive and negative predictive values were calculated. Performance characteristics of International Classification of Disease, Tenth Revision (ICD-10) codes for pneumonia in identifying CAP patients were assessed against the same reference standard. A secondary analysis including terms HAP and VAP in the reference standard was performed. Results: Provider-selected antibiotic indication for CAP had a sensitivity of 64.4%, specificity of 96.3%, positive predictive value (PPV) of 73.1%, and negative predictive value (NPV) of 96.1%, giving comparable performance to ICD-10 codes (Table 1). Of those with 21 false-negative results, 13 (61.9%) had a healthcare-associated lower respiratory tract infection and 14 (66.7%) had sepsis indicated in at least 1 antibiotic order. Conclusions: Provider-selected antibiotic indication showed moderate sensitivity and high specificity for identifying CAP-treated cases. Importantly, use of this method can be deployed for real-time antibiotic stewardship interventions for CAP. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anping Xie, Hugo Sax, Oluseyi Daodu, Lamia Alam, Marium Sultan, Clare Rock, Shawna Perry, Ayse Gurses
Background: Environmental cleaning is critical in preventing pathogen transmission and potential consecutive healthcare-acquired infections. In operating rooms (ORs), multiple invasive procedures increase the infectious risk for patients, making proper cleaning and disinfection of environmental surfaces of paramount importance. A human-factors engineering (HFE) approach emphasizing the impact of the entire work system on care processes and outcomes has been proposed to improve environmental cleaning. Using the lens of this HFE approach, we conducted a systematic review to synthesize existing evidence and identify gaps in the literature on OR cleaning. Methods: The systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and limited to English-written, peer-reviewed journal articles reporting empirical studies on OR cleaning. Figure 1 shows the flowchart of study search and screening. The following data were extracted from each included article: (1) general information of the article (eg, first author, title, journal, year of publication) and (2) characteristics of the study (eg, country, objectives, design, outcome measures and measuring techniques, findings, funding source). In addition, work-system elements (eg, people, tasks, tools and technologies, physical environment, organizational conditions) and cleaning processes (eg, turnover cleaning, terminal cleaning) addressed in each included studywere coded based on the Systems Engineering Initiative for Patient Safety (SEIPS) model. The methodological quality of included studies using a (non)randomized controlled design was assessed using the version 2 of the Cochrane risk-of-bias tool for randomized trials. Results: In total, 35 studies were included in this review, among which 10 examined the effectiveness of OR cleaning in reducing environmental contamination (Fig. 2), 1 examined the compliance of OR cleaning practices (Fig. 3), and 24 examined interventions for improving OR cleaning effectiveness and/or compliance (Fig. 4). Figure 5 summarizes the characteristics of the included studies. Conclusions: In this review, OR cleaning was inconsistently performed in practice, and mixed findings were reported regarding the effectiveness of OR cleaning in reducing environmental contamination. No study has systematically examined work-system factors influencing OR cleaning. Efforts to improve OR cleaning focused on cleaning tools and technologies (eg, ultraviolet light) and staff monitoring and training. Interventions targeting the broader work system influencing the cleaning processes are lacking. The scientific rigor of the included studies was modest. Most studies were either commercially funded or did not reveal their funding sources, which might introduce a desirability bias. Financial support: This study was funded by the Centers for Disease Control and Prevention. Disclosures: None
{"title":"Environmental cleaning in operating rooms: A systematic review from the human factors engineering perspective","authors":"Anping Xie, Hugo Sax, Oluseyi Daodu, Lamia Alam, Marium Sultan, Clare Rock, Shawna Perry, Ayse Gurses","doi":"10.1017/ash.2023.317","DOIUrl":"https://doi.org/10.1017/ash.2023.317","url":null,"abstract":"Background: Environmental cleaning is critical in preventing pathogen transmission and potential consecutive healthcare-acquired infections. In operating rooms (ORs), multiple invasive procedures increase the infectious risk for patients, making proper cleaning and disinfection of environmental surfaces of paramount importance. A human-factors engineering (HFE) approach emphasizing the impact of the entire work system on care processes and outcomes has been proposed to improve environmental cleaning. Using the lens of this HFE approach, we conducted a systematic review to synthesize existing evidence and identify gaps in the literature on OR cleaning. Methods: The systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and limited to English-written, peer-reviewed journal articles reporting empirical studies on OR cleaning. Figure 1 shows the flowchart of study search and screening. The following data were extracted from each included article: (1) general information of the article (eg, first author, title, journal, year of publication) and (2) characteristics of the study (eg, country, objectives, design, outcome measures and measuring techniques, findings, funding source). In addition, work-system elements (eg, people, tasks, tools and technologies, physical environment, organizational conditions) and cleaning processes (eg, turnover cleaning, terminal cleaning) addressed in each included studywere coded based on the Systems Engineering Initiative for Patient Safety (SEIPS) model. The methodological quality of included studies using a (non)randomized controlled design was assessed using the version 2 of the Cochrane risk-of-bias tool for randomized trials. Results: In total, 35 studies were included in this review, among which 10 examined the effectiveness of OR cleaning in reducing environmental contamination (Fig. 2), 1 examined the compliance of OR cleaning practices (Fig. 3), and 24 examined interventions for improving OR cleaning effectiveness and/or compliance (Fig. 4). Figure 5 summarizes the characteristics of the included studies. Conclusions: In this review, OR cleaning was inconsistently performed in practice, and mixed findings were reported regarding the effectiveness of OR cleaning in reducing environmental contamination. No study has systematically examined work-system factors influencing OR cleaning. Efforts to improve OR cleaning focused on cleaning tools and technologies (eg, ultraviolet light) and staff monitoring and training. Interventions targeting the broader work system influencing the cleaning processes are lacking. The scientific rigor of the included studies was modest. Most studies were either commercially funded or did not reveal their funding sources, which might introduce a desirability bias. Financial support: This study was funded by the Centers for Disease Control and Prevention. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Identification of predictors of antibiotic use can inform targeted antimicrobial stewardship initiatives and can account for sources of bias in before-and-after interventional stewardship studies. To date, no study has identified clinical predictors of antimicrobial use within intensive care units (ICUs), where antimicrobial resistance is most prevalent and problematic. Methods: As part of an ongoing prospective, single-arm, pilot feasibility trial of an ICU diagnostic stewardship intervention, we performed a nested retrospective cohort study to explore associations between patient clinical variables and ICUs antimicrobial use and resistance rates (AURs). We included all patients hospitalized in 3 ICUs (surgical, medical, and cardiac) from 2017 to 2021 at Michigan Medicine, a large, tertiary-care, academic medical center. Data were extracted from the electronic medical record using a structured query. Admission-level data were captured, including patient demographics, medical comorbidities, International Classification of Disease, Tenth Revision (ICD-10) admission diagnoses, as well as calendar day-level data including vital signs, clinical and microbiologic laboratory data, measures of acute severity of illness, ventilator–supplemental oxygen metrics, and procedural interventions using current procedural terminology (CPT) codes. ICU AURs were defined as total antibiotic days of therapy per patient per 100 ICU days. Associations between clinical variables and ICU AURs were calculated as rate ratios (RRs). Multiple imputation using fully conditional specification was performed to create 25 imputation data sets. Negative binomial regression models were constructed for each data set using backward selection. Variables retained in >50% of models were included in a final multivariate model. Results: In total, 15,177 ICU patient admissions were captured. Age, sex assigned at birth, and race did not independently associate with ICU AURs. Comorbidities, medical interventions, admission diagnoses, and laboratory data that independently associated with ICU-AURs are shown in Table 1. The clinical variables most strongly associated with increased ICU-AURs were pneumonia (RR, 1.55; 95% CI, 1.451.64), bacteremia (RR, 1.35; 95% CI, 1.25– 1.46), intraabdominal infection (RR, 1.35; 95% CI, 1.18–1.55), SOFA score (RR, 1.27; 95% CI, 1.14–1.42), abnormal WBC (RR, 1.26; 95% CI, 1.20–1.32), and immunocompromised status (RR, 1.20; 95% CI, 1.10–1.31). Clinical variables most strongly associated with decreased ICU-AURs were cardiac ICU (RR, 0.56; 95% CI, 0.52–0.60), COVID-19 (RR, 0.62; 95% CI, 0.56–0.70), and receipt of an invasive nonsurgical procedure (RR, 0.90; 95% CI, 0.82–0.98). Conclusions: In this single-center retrospective cohort study, several clinical variables were independently associated with ICU-AURs. These results may be used to identify patient subgroups for potentially high-yield ICU-based stewardship interventions and to account for sour
{"title":"Predictors of antimicrobial use in intensive care unit patients","authors":"Owen Albin, Jonathan Troost, Keith Kaye","doi":"10.1017/ash.2023.269","DOIUrl":"https://doi.org/10.1017/ash.2023.269","url":null,"abstract":"Background: Identification of predictors of antibiotic use can inform targeted antimicrobial stewardship initiatives and can account for sources of bias in before-and-after interventional stewardship studies. To date, no study has identified clinical predictors of antimicrobial use within intensive care units (ICUs), where antimicrobial resistance is most prevalent and problematic. Methods: As part of an ongoing prospective, single-arm, pilot feasibility trial of an ICU diagnostic stewardship intervention, we performed a nested retrospective cohort study to explore associations between patient clinical variables and ICUs antimicrobial use and resistance rates (AURs). We included all patients hospitalized in 3 ICUs (surgical, medical, and cardiac) from 2017 to 2021 at Michigan Medicine, a large, tertiary-care, academic medical center. Data were extracted from the electronic medical record using a structured query. Admission-level data were captured, including patient demographics, medical comorbidities, International Classification of Disease, Tenth Revision (ICD-10) admission diagnoses, as well as calendar day-level data including vital signs, clinical and microbiologic laboratory data, measures of acute severity of illness, ventilator–supplemental oxygen metrics, and procedural interventions using current procedural terminology (CPT) codes. ICU AURs were defined as total antibiotic days of therapy per patient per 100 ICU days. Associations between clinical variables and ICU AURs were calculated as rate ratios (RRs). Multiple imputation using fully conditional specification was performed to create 25 imputation data sets. Negative binomial regression models were constructed for each data set using backward selection. Variables retained in >50% of models were included in a final multivariate model. Results: In total, 15,177 ICU patient admissions were captured. Age, sex assigned at birth, and race did not independently associate with ICU AURs. Comorbidities, medical interventions, admission diagnoses, and laboratory data that independently associated with ICU-AURs are shown in Table 1. The clinical variables most strongly associated with increased ICU-AURs were pneumonia (RR, 1.55; 95% CI, 1.451.64), bacteremia (RR, 1.35; 95% CI, 1.25– 1.46), intraabdominal infection (RR, 1.35; 95% CI, 1.18–1.55), SOFA score (RR, 1.27; 95% CI, 1.14–1.42), abnormal WBC (RR, 1.26; 95% CI, 1.20–1.32), and immunocompromised status (RR, 1.20; 95% CI, 1.10–1.31). Clinical variables most strongly associated with decreased ICU-AURs were cardiac ICU (RR, 0.56; 95% CI, 0.52–0.60), COVID-19 (RR, 0.62; 95% CI, 0.56–0.70), and receipt of an invasive nonsurgical procedure (RR, 0.90; 95% CI, 0.82–0.98). Conclusions: In this single-center retrospective cohort study, several clinical variables were independently associated with ICU-AURs. These results may be used to identify patient subgroups for potentially high-yield ICU-based stewardship interventions and to account for sour","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mari Freitas, Ashley Fell, Susan Gerbensky Klammer, Ruth Lynfield, Amanda Beaudoin
Background: Nationally, >30% of all outpatient antibiotics are unnecessary or inappropriate, and only 52% of outpatients with sinusitis, otitis media, or pharyngitis receive recommended first-line antibiotics. The Minnesota All Payer Claims Database (MN APCD) collects medical claims, pharmacy claims, and eligibility files from private and public healthcare payers. We analyzed claims to describe overall and firstline antibiotic prescribing for acute bronchitis, adult acute sinusitis, and pediatric patients. Results: We analyzed 3,502,013 respiratory events from 1,612,501 members. Acute bronchitis accounted for 179,723 events (5.1%), acute sinusitis accounted for 236,901 adult events (10%), and otitis media accounted for 232,226 pediatric events (19%). Also, 73,385 bronchitis diagnoses (~40%) had no associated antibiotic. Antibiotics were associated with 199,445 adult sinusitis events (84.2%), of which 89,386 (44.8%) were firstline antibiotics, and 190,962 pediatric otitis media events (82.2%), of which 126,859 (66.4%) were firstline antibiotics. Common antibiotic classes used when a firstline drug was not selected were macrolides (28.9%) and tetracyclines (26.8%) for adult acute sinusitis and cephalosporins (61.4%) and macrolides (30.6%) for pediatric otitis media. Compared to the least vulnerable quartile, the most vulnerable social vulnerability index (SVI) quartile had lower odds of receiving firstline antibiotics for adult acute sinusitis if antibiotics were prescribed (OR, 0.90; 95% CI, 0.87–0.94) and higher odds of receiving firstline antibiotics for pediatric otitis media if antibiotics were prescribed (OR, 1.16; 95% CI, 1.12–1.21). Conclusions: Improvement is needed in avoiding antibiotics for acute bronchitis and selecting firstline drugs for sinusitis and otitis media. Additional analyses adjusting for demographic, geographic, and prescriber factors are planned to better understand differences in prescribing appropriateness among Minnesotans. Disclosures: None
{"title":"Using state claims data to explore first-line antibiotic prescribing for acute respiratory conditions—Minnesota, 2018–2019","authors":"Mari Freitas, Ashley Fell, Susan Gerbensky Klammer, Ruth Lynfield, Amanda Beaudoin","doi":"10.1017/ash.2023.277","DOIUrl":"https://doi.org/10.1017/ash.2023.277","url":null,"abstract":"Background: Nationally, >30% of all outpatient antibiotics are unnecessary or inappropriate, and only 52% of outpatients with sinusitis, otitis media, or pharyngitis receive recommended first-line antibiotics. The Minnesota All Payer Claims Database (MN APCD) collects medical claims, pharmacy claims, and eligibility files from private and public healthcare payers. We analyzed claims to describe overall and firstline antibiotic prescribing for acute bronchitis, adult acute sinusitis, and pediatric patients. Results: We analyzed 3,502,013 respiratory events from 1,612,501 members. Acute bronchitis accounted for 179,723 events (5.1%), acute sinusitis accounted for 236,901 adult events (10%), and otitis media accounted for 232,226 pediatric events (19%). Also, 73,385 bronchitis diagnoses (~40%) had no associated antibiotic. Antibiotics were associated with 199,445 adult sinusitis events (84.2%), of which 89,386 (44.8%) were firstline antibiotics, and 190,962 pediatric otitis media events (82.2%), of which 126,859 (66.4%) were firstline antibiotics. Common antibiotic classes used when a firstline drug was not selected were macrolides (28.9%) and tetracyclines (26.8%) for adult acute sinusitis and cephalosporins (61.4%) and macrolides (30.6%) for pediatric otitis media. Compared to the least vulnerable quartile, the most vulnerable social vulnerability index (SVI) quartile had lower odds of receiving firstline antibiotics for adult acute sinusitis if antibiotics were prescribed (OR, 0.90; 95% CI, 0.87–0.94) and higher odds of receiving firstline antibiotics for pediatric otitis media if antibiotics were prescribed (OR, 1.16; 95% CI, 1.12–1.21). Conclusions: Improvement is needed in avoiding antibiotics for acute bronchitis and selecting firstline drugs for sinusitis and otitis media. Additional analyses adjusting for demographic, geographic, and prescriber factors are planned to better understand differences in prescribing appropriateness among Minnesotans. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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