Patterns, Predictors, and Intercenter Variability in Empiric Gram-Negative Antibiotic Use Across 928 United States Hospitals.

BACKGROUND: Empiric antibiotic use among hospitalized adults in the United States (US) is largely undescribed. Identifying factors associated with broad-spectrum empiric therapy may inform antibiotic stewardship interventions and facilitate benchmarking. METHODS: We performed a retrospective cohort study of adults discharged in 2019 from 928 hospitals in the Premier Healthcare Database. "Empiric" gram-negative antibiotics were defined by administration before day 3 of hospitalization. Multivariable logistic regression models with random effects by hospital were used to evaluate associations between patient and hospital characteristics and empiric receipt of broad-spectrum, compared to narrow-spectrum, gram-negative antibiotics. RESULTS: Of 8 017 740 hospitalized adults, 2 928 657 (37%) received empiric gram-negative antibiotics. Among 1 781 306 who received broad-spectrum therapy, 30% did not have a common infectious syndrome present on admission (pneumonia, urinary tract infection, sepsis, or bacteremia), surgery, or an intensive care unit stay in the empiric window. Holding other factors constant, males were 22% more likely (adjusted odds ratio [aOR], 1.22 [95% confidence interval, 1.22-1.23]), and all non-White racial groups 6%-13% less likely (aOR range, 0.87-0.94), to receive broad-spectrum therapy. There were significant prescribing differences by region, with the highest adjusted odds of broad-spectrum therapy in the US West South Central division. Even after model adjustment, there remained substantial interhospital variability: Among patients receiving empiric therapy, the probability of receiving broad-spectrum antibiotics varied as much as 34+ percentage points due solely to the admitting hospital (95% interval of probabilities: 43%-77%). CONCLUSIONS: Empiric gram-negative antibiotic use is highly variable across US regions, and there is high, unexplained interhospital variability. Sex and racial disparities in the receipt of broad-spectrum therapy warrant further investigation.

Impact of Sex and Metabolic Comorbidities on Coronavirus Disease 2019 (COVID-19) Mortality Risk Across Age Groups: 66 646 Inpatients Across 613 U.S. Hospitals.

BACKGROUND: The relationship between common patient characteristics, such as sex and metabolic comorbidities, and mortality from coronavirus disease 2019 (COVID-19) remains incompletely understood. Emerging evidence suggests that metabolic risk factors may also vary by age. This study aimed to determine the association between common patient characteristics and mortality across age-groups among COVID-19 inpatients. METHODS: We performed a retrospective cohort study of patients discharged from hospitals in the Premier Healthcare Database between April-June 2020. Inpatients were identified using COVID-19 ICD-10-CM diagnosis codes. A priori-defined exposures were sex and present-on-admission hypertension, diabetes, obesity, and interactions between age and these comorbidities. Controlling for additional confounders, we evaluated relationships between these variables and in-hospital mortality in a log-binomial model. RESULTS: Among 66 646 (6.5%) admissions with a COVID-19 diagnosis, across 613 U.S. hospitals, 12 388 (18.6%) died in-hospital. In multivariable analysis, male sex was independently associated with 30% higher mortality risk (aRR, 1.30, 95% CI: 1.26-1.34). Diabetes without chronic complications was not a risk factor at any age (aRR 1.01, 95% CI: 0.96-1.06), and hypertension without chronic complications was a risk factor only in 20-39 year-olds (aRR, 1.68, 95% CI: 1.17-2.40). Diabetes with chronic complications, hypertension with chronic complications, and obesity were risk factors in most age-groups, with highest relative risks among 20-39 year-olds (respective aRRs 1.79, 2.33, 1.92; P-values ≤ .002). CONCLUSIONS: Hospitalized men with COVID-19 are at increased risk of death across all ages. Hypertension, diabetes with chronic complications, and obesity demonstrated age-dependent effects, with the highest relative risks among adults aged 20-39.

Wohlfahrtiimonas chitiniclastica Monomicrobial Bacteremia in a Homeless Man.

We report a case of septic shock attributable to monomicrobial bloodstream infection secondary to Wohlfahrtiimonas chitiniclastica infection. This case suggests that W. chitiniclastica likely possesses the virulence to cause severe disease. Culture-independent techniques were essential in the identification of this organism, which enabled selection of appropriate therapy.

Antibiotic Use and Bacterial Infection among Inpatients in the First Wave of COVID-19: a Retrospective Cohort Study of 64,691 Patients.

Hospitalized patients with SARS-CoV-2 infection (COVID-19) often receive antibiotics for suspected bacterial coinfection. We estimated the incidence of bacterial coinfection and secondary infection in COVID-19 using clinical diagnoses to determine how frequently antibiotics are administered when bacterial infection is absent. We performed a retrospective cohort study of inpatients with COVID-19 present on admission to hospitals in the Premier Healthcare Database between April and June 2020. Bacterial infections were defined using ICD-10-CM diagnosis codes and associated "present on admission" coding. Coinfections were defined by bacterial infection present on admission, while secondary infections were defined by bacterial infection that developed after admission. Coinfection and secondary infection were not mutually exclusive. A total of 18.5% of 64,961 COVID-19 patients (n = 12,040) presented with bacterial infection at admission, 3.8% (n = 2,506) developed secondary infection after admission, and 0.9% (n = 574) had both; 76.3% (n = 49,551) received an antibiotic while hospitalized, including 71% of patients who had no diagnosis of bacterial infection. Secondary bacterial infection occurred in 5.7% of patients receiving steroids in the first 2 days of hospitalization, 9.9% receiving tocilizumab in the first 2 days of hospitalization, and 10.3% of patients receiving both. After adjusting for patient and hospital characteristics, bacterial coinfection (adjusted relative risk [aRR], 1.15; 95% confidence interval [CI], 1.11 to 1.20) and secondary infection (aRR 1.93; 95% CI, 1.82 to 2.04) were both independently associated with increased mortality. Although 1 in 5 inpatients with COVID-19 presents with bacterial infection, secondary infections in the hospital are uncommon. Most inpatients with COVID-19 receive antibiotic therapy, including 71% of those not diagnosed with bacterial infection.

Adherence to the SEP-1 Sepsis Bundle in Hospital-Onset v. Community-Onset Sepsis: a Multicenter Retrospective Cohort Study.

BACKGROUND: Sepsis is the leading cause of in-hospital death. The SEP-1 sepsis bundle is a protocol for early sepsis care that requires providers to diagnose and treat sepsis quickly. Limited evidence suggests that adherence to the sepsis bundle is lower in cases of hospital-onset sepsis. OBJECTIVE: To compare sepsis bundle adherence in hospital-onset vs. community-onset sepsis. DESIGN: Retrospective cohort study using multivariable analysis of clinical data. PARTICIPANTS: A total of 4658 inpatients age 18 or older were identified by diagnosis codes consistent with sepsis or disseminated infection. SETTING: Four university hospitals in California between 2014 and 2016. MAIN OUTCOMES AND MEASURES: The primary outcome was adherence to key components of the sepsis bundle defined by the Centers for Medicare and Medicaid Services in their core measure, SEP-1. Covariates included clinical characteristics related to the patient, infection, and pathogen. KEY RESULTS: Compared with community-onset, cases of hospital-onset sepsis were less likely to receive SEP-1 adherent care (relative risk 0.33, 95% confidence interval 0.29-0.38, p < 0.001). With the exception of vasopressors (RR 1.11, p = 0.002), each component of SEP-1 evaluated-blood cultures (RR 0.76, p < 0.001), serum lactate (RR 0.51, p < 0001), broad-spectrum antibiotics (RR 0.62, p < 0.001), intravenous fluids (0.47, p < 0.001), and follow-up lactate (RR 0.71, p < 0.001)-was less likely to be performed within the recommended time frame in hospital-onset sepsis. Within the hospital, cases of hospital-onset sepsis arising on the ward were less likely to receive SEP-1-adherent care than were cases arising in the intensive care unit (RR 0.68, p = 0.004). CONCLUSIONS: Inpatients with hospital-onset sepsis receive different management than individuals with community-onset sepsis. It remains to be determined whether system-level factors, provider-level factors, or factors related to measurement explain the observed variation in care or whether variation in care affects outcomes.

Burkholderia pseudomallei: Challenges for the Clinical Microbiology Laboratory.

Melioidosis is a potentially fatal infection caused by the bacterium Burkholderia pseudomallei Clinical diagnosis of melioidosis can be challenging since there is no pathognomonic clinical syndrome, and the organism is often misidentified by methods used routinely in clinical laboratories. Although the disease is more prevalent in Thailand and northern Australia, sporadic cases may be encountered in areas where it is not endemic, including the United States. Since the organism is considered a tier 1 select agent according to the Centers for Disease Control and Prevention and the U.S. Department of Agriculture Animal and Plant Health Inspection Service, clinical laboratories must be proficient at rapidly recognizing isolates suspicious for B. pseudomallei, be able to safely perform necessary rule-out tests, and to refer suspect isolates to Laboratory Response Network reference laboratories. In this minireview, we report a case of melioidosis encountered at our institution and discuss the laboratory challenges encountered when dealing with clinical isolates suspicious for B. pseudomallei or clinical specimens from suspected melioidosis cases.

Clinical decision support for gastrointestinal panel testing.

Objective: This study aimed to assess the impact of clinical decision support (CDS) to improve ordering of multiplex gastrointestinal polymerase chain reaction (PCR) testing panel ("GI panel"). Design: Single-center, retrospective, before-after study. Setting: Tertiary care Veteran's Affairs (VA) Medical Center provides inpatient, outpatient, and residential care. Patients: All patients tested with a GI panel between June 22, 2022 and April 20, 2023. Intervention: We designed a CDS questionnaire in the electronic medical record (EMR) to guide appropriate ordering of the GI panel. A "soft stop" reminder at the point of ordering prompted providers to confirm five appropriateness criteria: 1) documented diarrhea, 2) no recent receipt of laxatives, 3) C. difficile is not the leading suspected cause of diarrhea, 4) time period since a prior test is >14 days or prior positive test is >4 weeks and 5) duration of hospitalization <72 hours. The CDS was implemented in November 2022. Results: Compared to the pre-implementation period (n = 136), fewer tests were performed post-implementation (n = 92) with an IRR of 0.61 (p = 0.003). Inappropriate ordering based on laxative use or undocumented diarrhea decreased (IRR 0.37, p = 0.012 and IRR 0.25, p = 0.08, respectively). However, overall inappropriate ordering and outcome measures did not significantly differ before and after the intervention. Conclusions: Implementation of CDS in the EMR decreased testing and inappropriate ordering based on use of laxatives or undocumented diarrhea. However, inappropriate ordering of tests overall remained high post-intervention, signaling the need for continued diagnostic stewardship efforts.

Changes in use of multiplex respiratory panel testing during the COVID-19 pandemic.

BACKGROUND: COVID-19 changed the epidemiology of community-acquired respiratory viruses. We explored patterns of respiratory viral testing to understand which tests are most clinically useful in the postpandemic era. METHODS: We conducted a retrospective observational study of discharge data from PINC-AI (formerly Premier), a large administrative database. Use of multiplex nucleic acid amplification respiratory panels in acute care, including small (2-5 targets), medium (6-11), and large panels (>11), were compared between the early pandemic (03/2020-10/2020), late pandemic (11/2020-4/2021), and prepandemic respiratory season (11/2019 - 02/2020) using ANOVA. RESULTS: A median of 160.5 facilities contributed testing data per quarter (IQR 155.5-169.5). Prepandemic, facilities averaged 103 respiratory panels monthly (sd 138), including 79 large (sd 126), 7 medium (sd 31), and 16 small panels (sd 73). Relative to prepandemic, utilization decreased during the early pandemic (62 panels monthly/facility; sd 112) but returned to the prepandemic baseline by the late pandemic (107 panels monthly/facility; sd 211). Relative to prepandemic, late pandemic testing involved more small panel use (58 monthly/facility, sd 156) and less large panel use (47 monthly/facility, sd 116). Comparisons among periods demonstrated significant differences in overall testing (P < 0.0001), large panel use (P < 0.0001), and small panel use (P < 0.0001). CONCLUSIONS: Postpandemic, clinical use of respiratory panel testing shifted from predominantly large panels to predominantly small panels. Factors driving this change may include resource availability, costs, and the clinical utility of targeting important pathogenic viruses instead of testing "for everything."

Informing estimates of probability of Clostridioides difficile infection for testing and treatment: expert consensus from a modified-Delphi procedure.

Background: Clostridioides difficile infection (CDI) may be misdiagnosed if testing is performed in the absence of signs or symptoms of disease. This study sought to support appropriate testing by estimating the impact of signs, symptoms, and healthcare exposures on pre-test likelihood of CDI. Methods: A panel of fifteen experts in infectious diseases participated in a modified UCLA/RAND Delphi study to estimate likelihood of CDI. Consensus, defined as agreement by >70% of panelists, was assessed via a REDCap survey. Items without consensus were discussed in a virtual meeting followed by a second survey. Results: All fifteen panelists completed both surveys (100% response rate). In the initial survey, consensus was present on 6 of 15 (40%) items related to risk of CDI. After panel discussion and clarification of questions, consensus (>70% agreement) was reached on all remaining items in the second survey. Antibiotics were identified as the primary risk factor for CDI and grouped into three categories: high-risk (likelihood ratio [LR] 7, 93% agreement among panelists in first survey), low-risk (LR 3, 87% agreement in first survey), and minimal-risk (LR 1, 71% agreement in first survey). Other major factors included new or unexplained severe diarrhea (e.g., ≥ 10 liquid bowel movements per day; LR 5, 100% agreement in second survey) and severe immunosuppression (LR 5, 87% agreement in second survey). Conclusion: Infectious disease experts concurred on the importance of signs, symptoms, and healthcare exposures for diagnosing CDI. The resulting risk estimates can be used by clinicians to optimize CDI testing and treatment.

Delivery outcomes in a cohort of pregnant patients with COVID-19 with and without viral pneumonia.

BACKGROUND: Among pregnant people, COVID-19 can lead to adverse outcomes, but the specific pregnancy outcomes that are affected by the disease are unclear. In addition, the effect of the severity of COVID-19 on pregnancy outcomes has not been clearly identified. OBJECTIVE: This study aimed to evaluate the associations between COVID-19 with and without viral pneumonia and cesarean delivery, preterm delivery, preeclampsia, and stillbirth. STUDY DESIGN: We conducted a retrospective cohort study (April 2020-May 2021) of deliveries between 20 and 42 weeks of gestation from US hospitals in the Premier Healthcare Database. The primary outcomes were cesarean delivery, preterm delivery, preeclampsia, and stillbirth. We used a viral pneumonia diagnosis (International Classification of Diseases -Tenth-Clinical Modification codes J12.8 and J12.9) to categorize patients by severity of COVID-19. Pregnancies were categorized into 3 groups: NOCOVID (no COVID-19), COVID (COVID-19 without viral pneumonia), and PNA (COVID-19 with viral pneumonia). Groups were balanced for risk factors by propensity-score matching. RESULTS: A total of 814,649 deliveries from 853 US hospitals were included (NOCOVID: n=799,132; COVID: n=14,744; PNA: n=773). After propensity-score matching, the risks of cesarean delivery and preeclampsia were similar in the COVID group compared with the NOCOVID group (matched risk ratio, 0.97; 95% confidence interval, 0.94-1.00; and matched risk ratio, 1.02; 95% confidence interval, 0.96-1.07; respectively). The risks of preterm delivery and stillbirth were greater in the COVID group than in the NOCOVID group (matched risk ratio, 1.11; 95% confidence interval, 1.05-1.19; and matched risk ratio, 1.30; 95% confidence interval, 1.01-1.66; respectively). The risks of cesarean delivery, preeclampsia, and preterm delivery were higher in the PNA group than in the COVID group (matched risk ratio, 1.76; 95% confidence interval, 1.53-2.03; matched risk ratio, 1.37; 95% confidence interval, 1.08-1.74; and matched risk ratio, 3.33; 95% confidence interval, 2.56-4.33; respectively). The risk of stillbirth was similar in the PNA and COVID group (matched risk ratio, 1.17; 95% confidence interval, 0.40-3.44). CONCLUSION: Within a large national cohort of hospitalized pregnant people, we found that the risk of some adverse delivery outcomes was elevated in people with COVID-19 with and without viral pneumonia, with much higher risks in the group with viral pneumonia.

#Coronavirus on TikTok: user engagement with misinformation as a potential threat to public health behavior.

Coronavirus disease (COVID)-related misinformation is prevalent online, including on social media. The purpose of this study was to explore factors associated with user engagement with COVID-related misinformation on the social media platform, TikTok. A sample of TikTok videos associated with the hashtag #coronavirus was downloaded on September 20, 2020. Misinformation was evaluated on a scale (low, medium, and high) using a codebook developed by experts in infectious diseases. Multivariable modeling was used to evaluate factors associated with number of views and presence of user comments indicating intention to change behavior. One hundred and sixty-six TikTok videos were identified and reviewed. Moderate misinformation was present in 36 (22%) videos viewed a median of 6.8 million times (interquartile range [IQR] 3.6-16 million), and high-level misinformation was present in 11 (7%) videos viewed a median of 9.4 million times (IQR 5.1-18 million). After controlling for characteristics and content, videos containing moderate misinformation were less likely to generate a user response indicating intended behavior change. By contrast, videos containing high-level misinformation were less likely to be viewed but demonstrated a nonsignificant trend towards higher engagement among viewers. COVID-related misinformation is less frequently viewed on TikTok but more likely to engage viewers. Public health authorities can combat misinformation on social media by posting informative content of their own.

Developing a diagnosis calculator to estimate the probability of bacterial pneumonia.

Misdiagnosis of bacterial pneumonia increases risk of exposure to inappropriate antibiotics and adverse events. We developed a diagnosis calculator (https://calculator.testingwisely.com) to inform clinical diagnosis of community-acquired bacterial pneumonia using objective indicators, including incidence of disease, risk factors, and sensitivity and specificity of diagnostic tests, that were identified through literature review.

Diagnostic stewardship to support optimal use of multiplex molecular respiratory panels: A survey from the Society for Healthcare Epidemiology of America Research Network.

OBJECTIVES: Multiplex polymerase chain reaction (PCR) respiratory panels are rapid, highly sensitive tests for viral and bacterial pathogens that cause respiratory infections. In this study, we (1) described best practices in the implementation of respiratory panels based on expert perspectives and (2) identified tools for diagnostic stewardship to enhance the usefulness of testing. METHODS: We conducted a survey of the Society for Healthcare Epidemiology of America Research Network to explore current and future approaches to diagnostic stewardship of multiplex PCR respiratory panels. RESULTS: In total, 41 sites completed the survey (response rate, 50%). Multiplex PCR respiratory panels were perceived as supporting accurate diagnoses at 35 sites (85%), supporting more efficient patient care at 33 sites (80%), and improving patient outcomes at 23 sites (56%). Thirteen sites (32%) reported that testing may support diagnosis or patient care without improving patient outcomes. Furthermore, 24 sites (58%) had implemented diagnostic stewardship, with a median of 3 interventions (interquartile range, 1-4) per site. The interventions most frequently reported as effective were structured order sets to guide test ordering (4 sites), restrictions on test ordering based on clinician or patient characteristics (3 sites), and structured communication of results (2 sites). Education was reported as "helpful" but with limitations (3 sites). CONCLUSIONS: Many hospital epidemiologists and experts in infectious diseases perceive multiplex PCR respiratory panels as useful tests that can improve diagnosis, patient care, and patient outcomes. However, institutions frequently employ diagnostic stewardship to enhance the usefulness of testing, including most commonly clinical decision support to guide test ordering.

Clinical, contextual and hospital-level factors associated with escalation and de-escalation of empiric Gram-negative antibiotics among US inpatients.

Background: Empiric Gram-negative antibiotics are frequently changed in response to new information. To inform antibiotic stewardship, we sought to identify predictors of antibiotic changes using information knowable before microbiological test results. Methods: We performed a retrospective cohort study. Survival-time models were used to evaluate clinical factors associated with antibiotic escalation and de-escalation (defined as an increase or decrease, respectively, in the spectrum or number of Gram-negative antibiotics within 5 days of initiation). Spectrum was categorized as narrow, broad, extended or protected. Tjur's D statistic was used to estimate the discriminatory power of groups of variables. Results: In 2019, 2 751 969 patients received empiric Gram-negative antibiotics at 920 study hospitals. Antibiotic escalation occurred in 6.5%, and 49.2% underwent de-escalation; 8.8% were changed to an equivalent regimen. Escalation was more likely when empiric antibiotics were narrow-spectrum (HR 19.0 relative to protected; 95% CI: 17.9-20.1), broad-spectrum (HR 10.3; 95% CI: 9.78-10.9) or extended-spectrum (HR 3.49; 95% CI: 3.30-3.69). Patients with sepsis present on admission (HR 1.94; 95% CI: 1.91-1.96) and urinary tract infection present on admission (HR 1.36; 95% CI: 1.35-1.38) were more likely to undergo antibiotic escalation than patients without these syndromes. De-escalation was more likely with combination therapy (HR 2.62 per additional agent; 95% CI: 2.61-2.63) or narrow-spectrum empiric antibiotics (HR 1.67 relative to protected; 95% CI: 1.65-1.69). Choice of empiric regimen accounted for 51% and 74% of the explained variation in antibiotic escalation and de-escalation, respectively. Conclusions: Empiric Gram-negative antibiotics are frequently de-escalated early in hospitalization, whereas escalation is infrequent. Changes are primarily driven by choice of empiric therapy and presence of infectious syndromes.

Comorbidities associated with 30-day readmission following index coronavirus disease 2019 (COVID-19) hospitalization: A retrospective cohort study of 331,136 patients in the United States.

OBJECTIVE: Hospital readmission is unsettling to patients and caregivers, costly to the healthcare system, and may leave patients at additional risk for hospital-acquired infections and other complications. We evaluated the association between comorbidities present during index coronavirus disease 2019 (COVID-19) hospitalization and the risk of 30-day readmission. DESIGN, SETTING, AND PARTICIPANTS: We used the Premier Healthcare database to perform a retrospective cohort study of COVID-19 hospitalized patients discharged between April 2020 and March 2021 who were followed for 30 days after discharge to capture readmission to the same hospital. RESULTS: Among the 331,136 unique patients in the index cohort, 36,827 (11.1%) had at least 1 all-cause readmission within 30 days. Of the readmitted patients, 11,382 (3.4%) were readmitted with COVID-19 as the primary diagnosis. In the multivariable model adjusted for demographics, hospital characteristics, coexisting comorbidities, and COVID-19 severity, each additional comorbidity category was associated with an 18% increase in the odds of all-cause readmission (adjusted odds ratio [aOR], 1.18; 95% confidence interval [CI], 1.17-1.19) and a 10% increase in the odds of readmission with COVID-19 as the primary readmission diagnosis (aOR, 1.10; 95% CI, 1.09-1.11). Lymphoma (aOR, 1.86; 95% CI, 1.58-2.19), renal failure (aOR, 1.32; 95% CI, 1.25-1.40), and chronic lung disease (aOR, 1.29; 95% CI, 1.24-1.34) were most associated with readmission for COVID-19. CONCLUSIONS: Readmission within 30 days was common among COVID-19 survivors. A better understanding of comorbidities associated with readmission will aid hospital care teams in improving postdischarge care. Additionally, it will assist hospital epidemiologists and quality administrators in planning resources, allocating staff, and managing bed-flow issues to improve patient care and safety.

Clinical yield of multiple testing with respiratory pathogen panels.

Though multiplex respiratory pathogen panels (RPP) have high sensitivity, multiple tests are occasionally performed simultaneously or in rapid succession in an attempt to increase the yield. The purpose of this study was to assess the impact of this practice. METHODS: "Multiple testing" was defined as >1 RPP performed within 12 hours on the same patient and specimen type. All cases of multiple testing for adults at two hospitals over a 5-year period were included. Chart review was performed to determine whether discordant results led to a clinical diagnosis or change in clinical management. RESULTS: Of 18,779 RPPs, 462 (2.5%) represented cases of multiple testing. Twenty-six of 462 cases (5.6%) produced discordant results. Five discordant results (1.1% of 462 multiple testing episodes) were associated with a clinical diagnosis, and 4 (0.9%) influenced clinical management. CONCLUSION: Multiple RPP testing facilitates clinical management in <1% of cases. Medical centers may consider de-implementing this practice.

Exploration of Primary Care Clinician Attitudes and Cognitive Characteristics Associated With Prescribing Antibiotics for Asymptomatic Bacteriuria.

Importance: Antibiotic treatment for asymptomatic bacteriuria is not recommended in guidelines but is a major driver of inappropriate antibiotic use. Objective: To evaluate whether clinician culture and personality traits are associated with a predisposition toward inappropriate prescribing. Design, Setting, and Participants: This survey study involved secondary analysis of a previously completed survey. A total of 723 primary care clinicians in active practice in Texas, the Mid-Atlantic, and the Pacific Northwest, including physicians and advanced practice clinicians, were surveyed from June 1, 2018, to November 26, 2019, regarding their approach to a hypothetical patient with asymptomatic bacteriuria. Clinician culture was represented by training background and region of practice. Attitudes and cognitive characteristics were represented using validated instruments to assess numeracy, risk-taking preferences, burnout, and tendency to maximize care. Data were analyzed from November 8, 2021, to March 29, 2022. Interventions: The survey described a male patient with asymptomatic bacteriuria and changes in urine character. Clinicians were asked to indicate whether they would prescribe antibiotics. Main Outcomes and Measures: The main outcome was self-reported willingness to prescribe antibiotics for asymptomatic bacteriuria. Willingness to prescribe antibiotics was hypothesized to be associated with clinician characteristics, background, and attitudes, including orientation on the Medical Maximizer-Minimizer Scale. Individuals with a stronger orientation toward medical maximizing prefer treatment even when the value of treatment is ambiguous. Results: Of the 723 enrolled clinicians, 551 (median age, 32 years [IQR, 29-44 years]; 292 [53%] female; 296 [54%] White) completed the survey (76% response rate), including 288 resident physicians, 202 attending physicians, and 61 advanced practice clinicians. A total of 303 respondents (55%) were from the Mid-Atlantic, 136 (25%) were from Texas, and 112 (20%) were from the Pacific Northwest. A total of 392 clinicians (71% of respondents) indicated that they would prescribe antibiotic treatment for asymptomatic bacteriuria in the absence of an indication. In multivariable analyses, clinicians with a background in family medicine (odds ratio [OR], 2.93; 95% CI, 1.53-5.62) or a high score on the Medical Maximizer-Minimizer Scale (indicating stronger medical maximizing orientation; OR, 2.06; 95% CI, 1.38-3.09) were more likely to prescribe antibiotic treatment for asymptomatic bacteriuria. Resident physicians (OR, 0.57; 95% CI, 0.38-0.85) and clinicians in the Pacific Northwest (OR, 0.49; 95% CI, 0.33-0.72) were less likely to prescribe antibiotics for asymptomatic bacteriuria. Conclusions and Relevance: The findings of this survey study suggest that most primary care clinicians prescribe inappropriate antibiotic treatment for asymptomatic bacteriuria in the absence of risk factors. This tendency is more pronounced among family medicine physicians and medical maximizers and is less common among resident physicians and clinicians in the US Pacific Northwest. Clinician characteristics should be considered when designing antibiotic stewardship interventions.

Pregnancy and the Risk of In-Hospital Coronavirus Disease 2019 (COVID-19) Mortality.

OBJECTIVE: To evaluate whether pregnancy is an independent risk factor for in-hospital mortality among patients of reproductive age hospitalized with coronavirus disease 2019 (COVID-19) viral pneumonia. METHODS: We conducted a retrospective cohort study (April 2020-May 2021) of 23,574 female inpatients aged 15-45 years with an International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis code for COVID-19 discharged from 749 U.S. hospitals in the Premier Healthcare Database. We used a viral pneumonia diagnosis to select for patients with symptomatic COVID-19. The associations between pregnancy and in-hospital mortality, intensive care unit (ICU) admission, and mechanical ventilation were analyzed using propensity score-matched conditional logistic regression. Models were matched for age, marital status, race and ethnicity, Elixhauser comorbidity score, payer, hospital number of beds, season of discharge, hospital region, obesity, hypertension, diabetes mellitus, chronic pulmonary disease, deficiency anemias, depression, hypothyroidism, and liver disease. RESULTS: In-hospital mortality occurred in 1.1% of pregnant patients and 3.5% of nonpregnant patients hospitalized with COVID-19 and viral pneumonia (propensity score-matched odds ratio [OR] 0.39, 95% CI 0.25-0.63). The frequency of ICU admission for pregnant and nonpregnant patients was 22.0% and 17.7%, respectively (OR 1.34, 95% CI 1.15-1.55). Mechanical ventilation was used in 8.7% of both pregnant and nonpregnant patients (OR 1.05, 95% CI 0.86-1.29). Among patients who were admitted to an ICU, mortality was lower for pregnant compared with nonpregnant patients (OR 0.33, 95% CI 0.20-0.57), though mechanical ventilation rates were similar (35.7% vs 38.3%, OR 0.90, 95% CI 0.70-1.16). Among patients with mechanical ventilation, pregnant patients had a reduced risk of in-hospital mortality compared with nonpregnant patients (0.26, 95% CI 0.15-0.46). CONCLUSION: Despite a higher frequency of ICU admission, in-hospital mortality was lower among pregnant patients compared with nonpregnant patients with COVID-19 viral pneumonia, and these findings persisted after propensity score matching.

Clinician Attitudes and Beliefs Associated with More Aggressive Diagnostic Testing.

BACKGROUND: Variation in clinicians' diagnostic test utilization is incompletely explained by demographics and likely relates to cognitive characteristics. We explored clinician factors associated with diagnostic test utilization. METHODS: We used a self-administered survey of attitudes, cognitive characteristics, and reported likelihood of test ordering in common scenarios; frequency of lipid and liver testing in patients on statin therapy. Participants were 552 primary care physicians, nurse practitioners, and physician assistants from practices in 8 US states across 3 regions, from June 1, 2018 to November 26, 2019. We measured Testing Likelihood Score: the mean of 4 responses to testing frequency and self-reported testing frequency in patients on statins. RESULTS: Respondents were 52.4% residents, 36.6% attendings, and 11.0% nurse practitioners/physician assistants; most were white (53.6%) or Asian (25.5%). Median age was 32 years; 53.1% were female. Participants reported ordering tests for a median of 20% (stress tests) to 90% (mammograms) of patients; Testing Likelihood Scores varied widely (median 54%, interquartile range 43%-69%). Higher scores were associated with geography, training type, low numeracy, high malpractice fear, high medical maximizer score, high stress from uncertainty, high concern about bad outcomes, and low acknowledgment of medical uncertainty. More frequent testing of lipids and liver tests was associated with low numeracy, high medical maximizer score, high malpractice fear, and low acknowledgment of uncertainty. CONCLUSIONS: Clinician variation in testing was common, with more aggressive testing consistently associated with low numeracy, being a medical maximizer, and low acknowledgment of uncertainty. Efforts to reduce undue variations in testing should consider clinician cognitive drivers.