Assessing Clinician Utilization of Next-Generation Antibiotics Against Resistant Gram-Negative Infections in U.S. Hospitals : A Retrospective Cohort Study.

BACKGROUND: The U.S. antibiotic market failure has threatened future innovation and supply. Understanding when and why clinicians underutilize recently approved gram-negative antibiotics might help prioritize the patient in future antibiotic development and potential market entry rewards. OBJECTIVE: To determine use patterns of recently U.S. Food and Drug Administration (FDA)-approved gram-negative antibiotics (ceftazidime-avibactam, ceftolozane-tazobactam, meropenem-vaborbactam, plazomicin, eravacycline, imipenem-relebactam-cilastatin, and cefiderocol) and identify factors associated with their preferential use (over traditional generic agents) in patients with gram-negative infections due to pathogens displaying difficult-to-treat resistance (DTR; that is, resistance to all first-line antibiotics). DESIGN: Retrospective cohort. SETTING: 619 U.S. hospitals. PARTICIPANTS: Adult inpatients. MEASUREMENTS: Quarterly percentage change in antibiotic use was calculated using weighted linear regression. Machine learning selected candidate variables, and mixed models identified factors associated with new (vs. traditional) antibiotic use in DTR infections. RESULTS: Between quarter 1 of 2016 and quarter 2 of 2021, ceftolozane-tazobactam (approved 2014) and ceftazidime-avibactam (2015) predominated new antibiotic usage whereas subsequently approved gram-negative antibiotics saw relatively sluggish uptake. Among gram-negative infection hospitalizations, 0.7% (2551 [2631 episodes] of 362 142) displayed DTR pathogens. Patients were treated exclusively using traditional agents in 1091 of 2631 DTR episodes (41.5%), including "reserve" antibiotics such as polymyxins, aminoglycosides, and tigecycline in 865 of 1091 episodes (79.3%). Patients with bacteremia and chronic diseases had greater adjusted probabilities and those with do-not-resuscitate status, acute liver failure, and Acinetobacter baumannii complex and other nonpseudomonal nonfermenter pathogens had lower adjusted probabilities of receiving newer (vs. traditional) antibiotics for DTR infections, respectively. Availability of susceptibility testing for new antibiotics increased probability of usage. LIMITATION: Residual confounding. CONCLUSION: Despite FDA approval of 7 next-generation gram-negative antibiotics between 2014 and 2019, clinicians still frequently treat resistant gram-negative infections with older, generic antibiotics with suboptimal safety-efficacy profiles. Future antibiotics with innovative mechanisms targeting untapped pathogen niches, widely available susceptibility testing, and evidence demonstrating improved outcomes in resistant infections might enhance utilization. PRIMARY FUNDING SOURCE: U.S. Food and Drug Administration; NIH Intramural Research Program.

Measures and Impact of Caseload Surge During the COVID-19 Pandemic: A Systematic Review.

OBJECTIVES: COVID-19 pandemic surges strained hospitals globally. We performed a systematic review to examine measures of pandemic caseload surge and its impact on mortality of hospitalized patients. DATA SOURCES: PubMed, Embase, and Web of Science. STUDY SELECTION: English-language studies published between December 1, 2019, and November 22, 2023, which reported the association between pandemic "surge"-related measures and mortality in hospitalized patients. DATA EXTRACTION: Three authors independently screened studies, extracted data, and assessed individual study risk of bias. We assessed measures of surge qualitatively across included studies. Given multidomain heterogeneity, we semiquantitatively aggregated surge-mortality associations. DATA SYNTHESIS: Of 17,831 citations, we included 39 studies, 17 of which specifically described surge effects in ICU settings. The majority of studies were from high-income countries (n = 35 studies) and included patients with COVID-19 (n = 31). There were 37 different surge metrics which were mapped into four broad themes, incorporating caseloads either directly as unadjusted counts (n = 11), nested in occupancy (n = 14), including additional factors (e.g., resource needs, speed of occupancy; n = 10), or using indirect proxies (e.g., altered staffing ratios, alternative care settings; n = 4). Notwithstanding metric heterogeneity, 32 of 39 studies (82%) reported detrimental adjusted odds/hazard ratio for caseload surge-mortality outcomes, reporting point estimates of up to four-fold increased risk of mortality. This signal persisted among study subgroups categorized by publication year, patient types, clinical settings, and country income status. CONCLUSIONS: Pandemic caseload surge was associated with lower survival across most studies regardless of jurisdiction, timing, and population. Markedly variable surge strain measures precluded meta-analysis and findings have uncertain generalizability to lower-middle-income countries (LMICs). These findings underscore the need for establishing a consensus surge metric that is sensitive to capturing harms in everyday fluctuations and future pandemics and is scalable to LMICs.

Trends in Patient Transfers From Overall and Caseload-Strained US Hospitals During the COVID-19 Pandemic.

Importance: Transferring patients to other hospitals because of inpatient saturation or need for higher levels of care was often challenging during the early waves of the COVID-19 pandemic. Understanding how transfer patterns evolved over time and amid hospital overcrowding could inform future care delivery and load balancing efforts. Objective: To evaluate trends in outgoing transfers at overall and caseload-strained hospitals during the COVID-19 pandemic vs prepandemic times. Design, Setting, and Participants: This retrospective cohort study used data for adult patients at continuously reporting US hospitals in the PINC-AI Healthcare Database. Data analysis was performed from February to July 2023. Exposures: Pandemic wave, defined as wave 1 (March 1, 2020, to May 31, 2020), wave 2 (June 1, 2020, to September 30, 2020), wave 3 (October 1, 2020, to June 19, 2021), Delta (June 20, 2021, to December 18, 2021), and Omicron (December 19, 2021, to February 28, 2022). Main Outcomes and Measures: Weekly trends in cumulative mean daily acute care transfers from all hospitals were assessed by COVID-19 status, hospital urbanicity, and census index (calculated as daily inpatient census divided by nominal bed capacity). At each hospital, the mean difference in transfer counts was calculated using pairwise comparisons of pandemic (vs prepandemic) weeks in the same census index decile and averaged across decile hospitals in each wave. For top decile (ie, high-surge) hospitals, fold changes (and 95% CI) in transfers were adjusted for hospital-level factors and seasonality. Results: At 681 hospitals (205 rural [30.1%] and 476 urban [69.9%]; 360 [52.9%] small with <200 beds and 321 [47.1%] large with ≥200 beds), the mean (SD) weekly outgoing transfers per hospital remained lower than the prepandemic mean of 12.1 (10.4) transfers per week for most of the pandemic, ranging from 8.5 (8.3) transfers per week during wave 1 to 11.9 (10.7) transfers per week during the Delta wave. Despite more COVID-19 transfers, overall transfers at study hospitals cumulatively decreased during each high national surge period. At 99 high-surge hospitals, compared with a prepandemic baseline, outgoing acute care transfers decreased in wave 1 (fold change -15.0%; 95% CI, -22.3% to -7.0%; P < .001), returned to baseline during wave 2 (2.2%; 95% CI, -4.3% to 9.2%; P = .52), and displayed a sustained increase in subsequent waves: 19.8% (95% CI, 14.3% to 25.4%; P < .001) in wave 3, 19.2% (95% CI, 13.4% to 25.4%; P < .001) in the Delta wave, and 15.4% (95% CI, 7.8% to 23.5%; P < .001) in the Omicron wave. Observed increases were predominantly limited to small urban hospitals, where transfers peaked (48.0%; 95% CI, 36.3% to 60.8%; P < .001) in wave 3, whereas large urban and small rural hospitals displayed little to no increases in transfers from baseline throughout the pandemic. Conclusions and Relevance: Throughout the COVID-19 pandemic, study hospitals reported paradoxical decreases in overall patient transfers during each high-surge period. Caseload-strained rural (vs urban) hospitals with fewer than 200 beds were unable to proportionally increase transfers. Prevailing vulnerabilities in flexing transfer capabilities for care or capacity reasons warrant urgent attention.

Impact of Surge Strain and Pandemic Progression on Prognostication by an Established COVID-19-Specific Severity Score.

IMPORTANCE: Many U.S. State crisis standards of care (CSC) guidelines incorporated Sequential Organ Failure Assessment (SOFA), a sepsis-related severity score, in pandemic triage algorithms. However, SOFA performed poorly in COVID-19. Although disease-specific scores may perform better, their prognostic utility over time and in overcrowded care settings remains unclear. OBJECTIVES: We evaluated prognostication by the modified 4C (m4C) score, a COVID-19-specific prognosticator that demonstrated good predictive capacity early in the pandemic, as a potential tool to standardize triage across time and hospital-surge environments. DESIGN: Retrospective observational cohort study. SETTING: Two hundred eighty-one U.S. hospitals in an administrative healthcare dataset. PARTICIPANTS: A total of 298,379 hospitalized adults with COVID-19 were identified from March 1, 2020, to January 31, 2022. m4C scores were calculated from admission diagnosis codes, vital signs, and laboratory values. MAIN OUTCOMES AND MEASURES: Hospital-surge index, a severity-weighted measure of COVID-19 caseload, was calculated for each hospital-month. Discrimination of in-hospital mortality by m4C and surge index-adjusted models was measured by area under the receiver operating characteristic curves (AUC). Calibration was assessed by training models on early pandemic waves and measuring fit (deviation from bisector) in subsequent waves. RESULTS: From March 2020 to January 2022, 298,379 adults with COVID-19 were admitted across 281 U.S. hospitals. m4C adequately discriminated mortality in wave 1 (AUC 0.779 [95% CI, 0.769-0.789]); discrimination was lower in subsequent waves (wave 2: 0.772 [95% CI, 0.765-0.779]; wave 3: 0.746 [95% CI, 0.743-0.750]; delta: 0.707 [95% CI, 0.702-0.712]; omicron: 0.729 [95% CI, 0.721-0.738]). m4C demonstrated reduced calibration in contemporaneous waves that persisted despite periodic recalibration. Performance characteristics were similar with and without adjustment for surge. CONCLUSIONS AND RELEVANCE: Mortality prediction by the m4C score remained robust to surge strain, making it attractive for when triage is most needed. However, score performance has deteriorated in recent waves. CSC guidelines relying on defined prognosticators, especially for dynamic disease processes like COVID-19, warrant frequent reappraisal to ensure appropriate resource allocation.

Contribution of Key Odorants from Skins, Seeds, and Stems to the Aroma of Chardonnay Marc: A Valuable Coproduct of the Wine Industry.

Chardonnay marc, a co-product of the wine making industry, has recently garnered attention due to its health-promoting properties and is growing in popularity as a potential healthy and flavorful food ingredient. While previous studies have characterized the odorants in marc skins and identified the key odorants in marc seeds, the key odorants in the skins and stems and the contribution of each component to the whole marc aroma remains unknown. In this study, 27 odorants were identified in marc stems using solvent-assisted flavor evaporation and aroma extract dilution analysis. Four odorants were quantitated employing stable isotope dilution assays, and odor activity values (OAVs) were calculated. An odor simulation model prepared using odorants with OAVs > 1 sensorially matched the aroma of the marc stems. Omission studies showed that 3-methylnonane-2,4-dione, ethyl octanoate, oct-1-en-3-one, (2E,4E)-deca-2,4-dienal, (2E,4E)-nona-2,4-dienal, ß-ionone, linalool, hexanal, HDMF, and 3-(methylsulfonyl)propanal were the key odorants in marc skins, while hexanal and 3-methylnonane-2,4-dione were the key odorants in marc stems. Mass balance studies suggested that the skins were the main contributor to the hay, floral, and fruity attributes of the whole marc, the seeds contributed mostly to the fatty attribute, and the stems had a minor contribution.

Assessment of Hospital-Onset SARS-CoV-2 Infection Rates and Testing Practices in the US, 2020-2022.

Importance: Characterizing the scale and factors associated with hospital-onset SARS-CoV-2 infections could help inform hospital and public health policies regarding prevention and surveillance needs for these infections. Objective: To evaluate associations of hospital-onset SARS-CoV-2 infection rates with different periods of the COVID-19 pandemic, hospital characteristics, and testing practices. Design, Setting, and Participants: This cohort study of US hospitals reporting SARS-CoV-2 testing data in the PINC AI Healthcare Database COVID-19 special release files was conducted from July 2020 through June 2022. Data were collected from hospitals that reported at least 1 SARS-CoV-2 reverse transcription-polymerase chain reaction or antigen test during hospitalizations discharged that month. For each hospital-month where the hospital reported sufficient data, all hospitalizations discharged in that month were included in the cohort. SARS-CoV-2 viral tests and results reported in the microbiology files for all hospitalizations in the study period by discharge month were identified. Data analysis was conducted from September 2022 to March 2023. Exposure: Hospitalizations discharged in an included hospital-month. Main Outcomes and Measures: Multivariable generalized estimating equation negative-binomial regression models were used to assess associations of monthly rates of hospital-onset SARS-CoV-2 infections per 1000 patient-days (defined as a first positive SARS-CoV-2 test during after hospitalization day 7) with the phase of the pandemic (defined as the predominant SARS-CoV-2 variant in circulation), admission testing rates, and hospital characteristics (hospital bed size, teaching status, urban vs rural designation, Census region, and patient distribution variables). Results: A total of 5687 hospital-months from 288 distinct hospitals were included, which contributed 4 421 268 hospitalization records. Among 171 564 hospitalizations with a positive SARS-CoV-2 test, 7591 (4.4%) were found to be hospital onset and 6455 (3.8%) were indeterminate onset. The mean monthly hospital-onset infection rate per 1000 patient-days was 0.27 (95 CI, 0.26-0.29). Hospital-onset infections occurred in 2217 of 5687 hospital-months (39.0%). The monthly percentage of discharged patients tested for SARS-CoV-2 at admission varied; 1673 hospital-months (29.4%) had less than 25% of hospitalizations tested at admission; 2199 hospital-months (38.7%) had 25% to 50% of all hospitalizations tested, and 1815 hospital months (31.9%) had more than 50% of all hospitalizations tested at admission. Postadmission testing rates and community-onset infection rates increased with admission testing rates. In multivariable models restricted to hospital-months testing at least 25% of hospitalizations at admission, a 10% increase in community-onset SARS-CoV-2 infection rate was associated with a 178% increase in the hospital-onset infection rate (rate ratio, 2.78; 95% CI, 2.52-3.07). Additionally, the phase of the COVID-19 pandemic, the admission testing rate, Census region, and bed size were all significantly associated with hospital-onset SARS-CoV-2 infection rates. Conclusions and Relevance: In this cohort study of hospitals reporting SARS-CoV-2 infections, there was an increase of hospital-onset SARS-CoV-2 infections when community-onset infections were higher, indicating a need for ongoing and enhanced surveillance and prevention efforts to reduce in-hospital transmission of SARS-CoV-2 infections, particularly when community-incidence of SARS-CoV-2 infections is high.

Reliability of Admission Procalcitonin Testing for Capturing Bacteremia Across the Sepsis Spectrum: Real-World Utilization and Performance Characteristics, 65 U.S. Hospitals, 2008-2017.

OBJECTIVES: Serum procalcitonin is often ordered at admission for patients with suspected sepsis and bloodstream infections (BSIs), although its performance characteristics in this setting remain contested. This study aimed to evaluate use patterns and performance characteristics of procalcitonin-on-admission in patients with suspected BSI, with or without sepsis. DESIGN: Retrospective cohort study. SETTING: Cerner HealthFacts Database (2008-2017). PATIENTS: Adult inpatients (≥ 18 yr) who had blood cultures and procalcitonin drawn within 24 hours of admission. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Testing frequency of procalcitonin was determined. Sensitivity of procalcitonin-on-admission for detecting BSI due to different pathogens was calculated. Area under the receiver operating characteristic curve (AUC) was calculated to assess discrimination by procalcitonin-on-admission for BSI in patients with and without fever/hypothermia, ICU admission and sepsis defined by Centers for Disease Control and Prevention Adult Sepsis Event criteria. AUCs were compared using Wald test and p values were adjusted for multiple comparisons. At 65 procalcitonin-reporting hospitals, 74,958 of 739,130 patients (10.1%) who had admission blood cultures also had admission procalcitonin testing. Most patients (83%) who had admission day procalcitonin testing did not have a repeat procalcitonin test. Median procalcitonin varied considerably by pathogen, BSI source, and acute illness severity. At a greater than or equal to 0.5 ng/mL cutoff, sensitivity for BSI detection was 68.2% overall, ranging between 58.0% for enterococcal BSI without sepsis and 96.4% for pneumococcal sepsis. Procalcitonin-on-admission displayed moderate discrimination at best for overall BSI (AUC, 0.73; 95% CI, 0.72-0.73) and showed no additional utility in key subgroups. Empiric antibiotic use proportions were not different between blood culture sampled patients with a positive procalcitonin (39.7%) and negative procalcitonin (38.4%) at admission. CONCLUSIONS: At 65 study hospitals, procalcitonin-on-admission demonstrated poor sensitivity in ruling out BSI, moderate-to-poor discrimination for both bacteremic sepsis and occult BSI and did not appear to meaningfully alter empiric antibiotic usage. Diagnostic stewardship of procalcitonin-on-admission and risk assessment of admission procalcitonin-guided clinical decisions is warranted.

Early Discontinuation of Antibiotics in Patients Admitted With Clinically Suspected Serious Infection but Negative Cultures: Retrospective Cohort Study of Practice Patterns and Outcomes at 111†US Hospitals.

Background: The optimal duration for antibiotics in patients hospitalized with culture-negative serious infection (CNSI) is unknown. We compared outcomes in patients with CNSI treated with 3 or 4 vs ≥5 days of antibiotics. Methods: CNSI was identified among adults admitted to 111 US hospitals between 2009 and 2014 via electronic health record data, defined as suspected serious infection (blood cultures drawn and ≥3 days of antibiotics) and negative culture- and nonculture-based tests for infection. Patients treated with antibiotics on their last hospital day and patients with diagnosis codes for sepsis-mimicking conditions were excluded. Among patients without fevers/hypothermia or vasopressors by day 3, we calculated odds ratios for in-hospital mortality or discharge to hospice associated with 3 or 4 vs ≥5 days of antibiotics, adjusting for confounders. Results: Antibiotics were discontinued in 3 or 4 days in 1862 (9%) of 20 714 patients with CNSI. Early discontinuation was not associated with higher mortality odds overall (adjusted odds ratio [aOR], 1.27; 95% CI, .98-1.65), in patients presenting with (1.39; .88-2.22) and without sepsis (1.17; .81-1.69), and in those with pulmonary (1.23; .65-2.34) and nonpulmonary CNSI (1.30; .99-1.72). Early discontinuation appeared detrimental with propensity score weighting (aOR, 1.36; 95% CI, 1.03-1.80) and when retaining patients with sepsis mimics (1.38; 1.16-1.65), but it was protective (0.48; .37-.64]) when retaining patients who received antibiotics on their last hospital day. Conclusions: Early discontinuation of antibiotics in CNSI was not associated with significant harm in our primary analysis, but different conclusions based on alternative analytic decisions, as well as risk of residual confounding, indicate that randomized controlled trials are needed.

Association between minimum inhibitory concentration values and mortality risk in patients with Stenotrophomonas maltophilia infections: a retrospective cohort study of electronic health records from 148 US hospitals.

Background: Clinical data informing antimicrobial susceptibility breakpoints for Stenotrophomonas maltophilia infections are lacking. We sought to leverage real-world data to identify MIC values within the currently defined susceptible range that could discriminate mortality risk for patients with S. maltophilia infections and guide future breakpoint revisions. Methods: Inpatients with S. maltophilia infection who received single-agent targeted therapy with levofloxacin or trimethoprim/sulfamethoxazole were identified in the Cerner HealthFacts electronic health record database. Encounters were restricted to those with MIC values reported to be in the susceptible range for both agents. Curation for exact (non-range) MIC values yielded sequentially granular model populations. Logistic regression was used to calculate adjusted OR (aOR) of mortality or hospice discharge associated with different susceptible-range MICs, controlling for patient- and centre-related factors, and infection site, polymicrobial infection and receipt of empirical therapy. Results: Seventy-three of 851 levofloxacin-treated patients had levofloxacin MIC of exactly 2 mg/L (current Clinical and Laboratory Standards Institute (CLSI) susceptibility breakpoint) and served as the reference category for levofloxacin breakpoint models. In breakpoint model I (n = 501), aOR of mortality associated with infection due to isolates with levofloxacin MIC of ≤1 versus 2 mg/L were similar [aOR = 1.79 (95% CI 0.88-3.62), P = 0.11]. In breakpoint model IIa (n = 358), aOR of mortality associated with MIC ≤0.5 versus 2 mg/L were also similar [aOR 0.1.36 (95% CI 0.65-2.83), P = 0.41]. However, breakpoint model IIb (n = 297) displayed higher aOR of mortality associated with an MIC of 1 versus 2 mg/L [aOR 2.36 (95% CI 1.14-4.88), P = 0.02]. Only 9/645 trimethoprim/sulfamethoxazole-treated patients had trimethoprim/sulfamethoxazole MIC of exactly 2/38 mg/L precluding informative models for this agent. Conclusions: In this retrospective study of real-world patients with S. maltophilia infection, risk-adjusted survival data do not appear to stratify patients clinically within current susceptible-range MIC breakpoint for levofloxacin (≤2 mg/L) by mortality.

Noninvasive genomic profiling of somatic mutations in oral cavity cancers.

OBJECTIVES: Somatic mutations may predict prognosis, therapeutic response, or cancer progression. We evaluated targeted sequencing of oral rinse samples (ORS) for non-invasive mutational profiling of oral squamous cell carcinomas (OSCC). MATERIALS AND METHODS: A custom hybrid capture panel targeting 42 frequently mutated genes in OSCC was used to identify DNA sequence variants in matched ORS and fresh-frozen tumors from 120 newly-diagnosed patients. Receiver operating characteristic (ROC) curves determined the optimal variant allele fraction (VAF) cutoff for variant discrimination in ORS. Behavioral, clinical, and analytical factors were evaluated for impacts on assay performance. RESULTS: Half of tumors involved oral tongue (50 %), and a majority were T1-T2 tumor stage (55 %). Median depth of sequencing coverage was 260X for OSCC and 1,563X for ORS. Frequencies of single nucleotide variants (SNVs) at highly mutated genes (including TP53, FAT1, HRAS, NOTCH1, CDKN2A, CASP8, NFE2L2, and PIK3CA) in OSCC were highly correlated with TCGA data (R = 0.96, p = 2.5E-22). An ROC curve with area-under-the-curve (AUC) of 0.80 showed that, at an optimal VAF cutoff of 0.10 %, ORS provided 76 % sensitivity, 96 % specificity, but precision of only 2.6E-4. At this VAF cutoff, 206 of 270 SNVs in OSCC were detected in matched ORS. Sensitivity varied by patient, T stage and target gene. Neither downsampled ORS as matched control nor a naïve Bayesian classifier adjusting for sequencing bias appreciably improved assay performance. CONCLUSION: Targeted sequencing of ORS provides moderate assay performance for noninvasive detection of SNVs in OSCC. Our findings strongly rationalize further clinical and laboratory optimization of this assay, including strategies to improve precision.

Association between piperacillin/tazobactam MIC and survival among hospitalized patients with Enterobacterales infections: retrospective cohort analysis of electronic health records from 161 US hospitals.

Introduction: A recent randomized trial has suggested an increased risk of mortality for ceftriaxone-non-susceptible Enterobacterales infections treated with piperacillin/tazobactam compared with meropenem despite MICs within the susceptible range. Methods: We conducted a retrospective cohort study of clinical encounters within the Cerner Health Facts database to identify all encounters between 2001 and 2017 in which Enterobacterales infections were treated empirically with piperacillin/tazobactam and for which MICs to the drug were available. Multivariate regression analysis was performed to enable partitioning of MICs into discrete strata based on statistically significant difference in mortality risk. Results: During the study period, 10 101 inpatient encounters were identified meeting inclusion criteria. The crude in-hospital mortality for the entire cohort was 16.5%. Partitioning analysis identified a breakpoint of ≤16/4 mg/L that dichotomized encounters into lower versus higher mortality risk strata in the primary cohort of overall infections. This finding persisted in sequentially granular subsets where specific MICs ≤8/4 mg/L were reported (in lieu of ranges) as well as in the high-reliability subset with bloodstream infections. A higher clinical breakpoint of ≥128/4 mg/L dichotomized encounters with respiratory tract infection. No breakpoint was identified when restricting to encounters with urinary tract infections, ICU admits or upon restricting analysis to encounters with ceftriaxone-resistant isolates. Conclusions: Clinical data suggest improved outcomes when piperacillin/tazobactam is prescribed for Enterobacterales infections with an MIC of ≤16/4 mg/L compared with ≥32/4 mg/L.

Semi-parametric modeling of SARS-CoV-2 transmission using tests, cases, deaths, and seroprevalence data.

Mechanistic models fit to streaming surveillance data are critical to understanding the transmission dynamics of an outbreak as it unfolds in real-time. However, transmission model parameter estimation can be imprecise, and sometimes even impossible, because surveillance data are noisy and not informative about all aspects of the mechanistic model. To partially overcome this obstacle, Bayesian models have been proposed to integrate multiple surveillance data streams. We devised a modeling framework for integrating SARS-CoV-2 diagnostics test and mortality time series data, as well as seroprevalence data from cross-sectional studies, and tested the importance of individual data streams for both inference and forecasting. Importantly, our model for incidence data accounts for changes in the total number of tests performed. We model the transmission rate, infection-to-fatality ratio, and a parameter controlling a functional relationship between the true case incidence and the fraction of positive tests as time-varying quantities and estimate changes of these parameters nonparametrically. We compare our base model against modified versions which do not use diagnostics test counts or seroprevalence data to demonstrate the utility of including these often unused data streams. We apply our Bayesian data integration method to COVID-19 surveillance data collected in Orange County, California between March 2020 and February 2021 and find that 32-72% of the Orange County residents experienced SARS-CoV-2 infection by mid-January, 2021. Despite this high number of infections, our results suggest that the abrupt end of the winter surge in January 2021 was due to both behavioral changes and a high level of accumulated natural immunity.

Outcomes of Patients With Primary Cardiac Diagnoses Admitted to Cardiac vs Noncardiac Intensive Care Units.

BACKGROUND: Demographics in cardiac intensive care units (CICUs) have evolved, with increased prevalence of noncardiac critical illnesses. OBJECTIVES: This study compares outcomes of patients with primary cardiac diagnoses admitted to CICUs vs those of patients with primary cardiac diagnoses admitted to noncardiac ICUs. METHODS: The Cerner Health Facts Database was queried to identify adults with primary cardiac diagnoses admitted to ICUs within 48 hours of presentation between 2009 and 2014. Only hospitals with multiple ICUs including a CICU were studied. Information on ICU staffing was not available. A univariate analysis of ICU type (model 1) and multivariate analyses incorporating patient- and hospital-level variables (model 2) and concurrent, noncardiac, ICU-level diagnoses (model 3) were utilized to assess the impact of ICU type on inpatient mortality. RESULTS: Of 16,163 encounters across 14 hospitals, 8,499 (52.6%) were admitted to CICUs and 7,664 (47.4%) to noncardiac ICUs. Univariate analysis (model 1) demonstrated increased mortality in noncardiac ICUs compared to CICUs (odds ratio [OR]: 1.47, 95% CI: 1.32-1.64; P < 0.0001). This risk dissipated (OR: 1.04, 95% CI: 0.91-1.18; P = 0.56) after controlling for patient- and hospital-level variables (model 2). Inclusion of concurrent, noncardiac, ICU-level diagnoses (model 3) lead to a reversal with decreased mortality in noncardiac ICUs (OR: 0.86, 95% CI: 0.76-0.98; P = 0.03). CONCLUSIONS: In this historical cohort study evaluating CICU outcomes prior to the evolution of proposed staffing and care model modernization, survival of cardiac patients with concurrent, noncardiac critical illnesses may have been better with the expertise available in general system ICUs. These results may support contemporary efforts to increase the capacity to manage noncardiac critical illnesses in CICUs.

Characterization of Key Odorants in Chardonnay Seeds.

Chardonnay marc, a co-product of the winemaking industry, is a combination of skins, seeds, and stems remaining after the juice is pressed from the grapes. This co-product amounts to over half a million tons per year. Recently, Chardonnay marc has been emerging as a healthy and flavorful food ingredient. The aroma contribution of the seeds to the overall aroma of Chardonnay marc remains unknown. In the present study, 43 odorants were identified in Chardonnay seeds employing aroma extract dilution analysis (AEDA) performed on a distillate prepared by solvent extraction and solvent-assisted flavor evaporation (SAFE) distillation. Of those, 6 odorants with a flavor dilution (FD) factor ≥64 were quantitated using stable isotope dilution assays (SIDAs). The odorants included (2E,4E)-deca-2,4-dienal (fatty, OAV 8028), 3-methylnonane-2,4-dione (hay, OAV 4772), (2E,4E)-nona-2,4-dienal (fatty, OAV 1750), hexanal (green, OAV 1481), linalool (floral, citrus, OAV 28), and 2-phenylethanol (floral, rose, OAV 2). An aroma simulation model was prepared based on the quantitative data, and its aroma was a close match to the Chardonnay seed powder. Omission studies applied to the aroma simulation model showed that hexanal and 3-methylnonane-2,4-dione were the key odorants driving the aroma profile. This research established a foundation for future studies aimed at optimizing the flavor of Chardonnay marc powder.

Antiviral innate immunity is diminished in the upper respiratory tract of severe COVID-19 patients.

Understanding early innate immune responses to coronavirus disease 2019 (COVID-19) is crucial to developing targeted therapies to mitigate disease severity. Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 infection elicits interferon expression leading to transcription of IFN-stimulated genes (ISGs) to control viral replication and spread. SARS-CoV-2 infection also elicits NF-κB signaling which regulates inflammatory cytokine expression contributing to viral control and likely disease severity. Few studies have simultaneously characterized these two components of innate immunity to COVID-19. We designed a study to characterize the expression of interferon alpha-2 (IFNA2) and interferon beta-1 (IFNB1), both type-1 interferons (IFN-1), interferon-gamma (IFNG), a type-2 interferon (IFN-2), ISGs, and NF-κB response genes in the upper respiratory tract (URT) of patients with mild (outpatient) versus severe (hospitalized) COVID-19. Further, we characterized the weekly dynamics of these responses in the upper and lower respiratory tracts (LRTs) and blood of severe patients to evaluate for compartmental differences. We observed significantly increased ISG and NF-κB responses in the URT of mild compared with severe patients early during illness. This pattern was associated with increased IFNA2 and IFNG expression in the URT of mild patients, a trend toward increased IFNB1-expression and significantly increased STING/IRF3/cGAS expression in the URT of severe patients. Our by-week across-compartment analysis in severe patients revealed significantly higher ISG responses in the blood compared with the URT and LRT of these patients during the first week of illness, despite significantly lower expression of IFNA2, IFNB1, and IFNG in blood. NF-κB responses, however, were significantly elevated in the LRT compared with the URT and blood of severe patients during peak illness (week 2). Our data support that severe COVID-19 is associated with impaired interferon signaling in the URT during early illness and robust pro-inflammatory responses in the LRT during peak illness.

Epidemiology of ICU-Onset Bloodstream Infection: Prevalence, Pathogens, and Risk Factors Among 150,948 ICU Patients at 85 U.S. Hospitals.

OBJECTIVES: Bloodstream infections (BSIs) acquired in the ICU represent a detrimental yet potentially preventable condition. We determined the prevalence of BSI acquired in the ICU (ICU-onset BSI), pathogen profile, and associated risk factors. DESIGN: Retrospective cohort study. DATA SOURCES: Eighty-five U.S. hospitals in the Cerner Healthfacts Database. PATIENT SELECTION: Adult hospitalizations between January 2009 and December 2015 including a (≥ 3 d) ICU stay. DATA EXTRACTION AND DATA SYNTHESIS: Prevalence of ICU-onset BSI (between ICU Day 3 and ICU discharge) and associated pathogen and antibiotic resistance distributions were compared with BSI present on (ICU) admission (ICU-BSI POA ); and BSI present on ICU admission day or Day 2. Cox models identified risk factors for ICU-onset BSI among host, care setting, and treatment-related factors. Among 150,948 ICU patients, 5,600 (3.7%) had ICU-BSI POA and 1,306 (0.9%) had ICU-onset BSI. Of those with ICU-BSI POA , 4,359 (77.8%) were admitted to ICU at hospital admission day. Patients with ICU-onset BSI (vs ICU-BSI POA ) displayed higher crude mortality of 37.9% (vs 20.4%) ( p < 0.001) and longer median (interquartile range) length of stay of 13 days (8-23 d) (vs 5 d [3-8 d]) ( p < 0.001) (considering all ICU stay). Compared with ICU-BSI POA , ICU-onset BSI displayed more Pseudomonas , Acinetobacter , Enterococcus, Candida , and Coagulase-negative Staphylococcus species, and more methicillin-resistant staphylococci, vancomycin-resistant enterococci, ceftriaxone-resistant Enterobacter , and carbapenem-resistant Enterobacterales and Acinetobacter species, respectively. Being younger, male, Black, Hispanic, having greater comorbidity burden, sepsis, trauma, acute pulmonary or gastrointestinal presentations, and pre-ICU exposure to antibacterial and antifungal agents was associated with greater ICU-onset BSI risk after adjusted analysis. Mixed ICUs (vs medical or surgical ICUs) and urban and small/medium rural hospitals were also associated with greater ICU-onset BSI risk. The associated risk of acquiring ICU-onset BSI manifested with any duration of mechanical ventilation and 7 days after insertion of central venous or arterial catheters. CONCLUSIONS: ICU-onset BSI is a serious condition that displays a unique pathogen and resistance profile compared with ICU-BSI POA . Further scrutiny of modifiable risk factors for ICU-onset BSI may inform control strategies.

Preintubation Sequential Organ Failure Assessment Score for Predicting COVID-19 Mortality: External Validation Using Electronic Health Record From 86 U.S. Healthcare Systems to Appraise Current Ventilator Triage Algorithms.

OBJECTIVES: Prior research has hypothesized the Sequential Organ Failure Assessment (SOFA) score to be a poor predictor of mortality in mechanically ventilated patients with COVID-19. Yet, several U.S. states have proposed SOFA-based algorithms for ventilator triage during crisis standards of care. Using a large cohort of mechanically ventilated patients with COVID-19, we externally validated the predictive capacity of the preintubation SOFA score for mortality prediction with and without other commonly used algorithm elements. DESIGN: Multicenter, retrospective cohort study using electronic health record data. SETTING: Eighty-six U.S. health systems. PATIENTS: Patients with COVID-19 hospitalized between January 1, 2020, and February 14, 2021, and subsequently initiated on mechanical ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among 15,122 mechanically ventilated patients with COVID-19, SOFA score alone demonstrated poor discriminant accuracy for inhospital mortality in mechanically ventilated patients using the validation cohort (area under the receiver operating characteristic curve [AUC], 0.66; 95% CI, 0.65-0.67). Discriminant accuracy was even poorer using SOFA score categories (AUC, 0.54; 95% CI, 0.54-0.55). Age alone demonstrated greater discriminant accuracy for inhospital mortality than SOFA score (AUC, 0.71; 95% CI, 0.69-0.72). Discriminant accuracy for mortality improved upon addition of age to the continuous SOFA score (AUC, 0.74; 95% CI, 0.73-0.76) and categorized SOFA score (AUC, 0.72; 95% CI, 0.71-0.73) models, respectively. The addition of comorbidities did not substantially increase model discrimination. Of 36 U.S. states with crisis standards of care guidelines containing ventilator triage algorithms, 31 (86%) feature the SOFA score. Of these, 25 (81%) rely heavily on the SOFA score (12 exclusively propose SOFA; 13 place highest weight on SOFA or propose SOFA with one other variable). CONCLUSIONS: In a U.S. cohort of over 15,000 ventilated patients with COVID-19, the SOFA score displayed poor predictive accuracy for short-term mortality. Our findings warrant reappraisal of the SOFA score's implementation and weightage in existing ventilator triage pathways in current U.S. crisis standards of care guidelines.

Risk Factors for Severe COVID-19 Outcomes Among Persons Aged ≥18 Years Who Completed a Primary COVID-19 Vaccination Series - 465 Health Care Facilities, United States, December 2020-October 2021.

Vaccination against SARS-CoV-2, the virus that causes COVID-19, is highly effective at preventing COVID-19-associated hospitalization and death; however, some vaccinated persons might develop COVID-19 with severe outcomes† (1,2). Using data from 465 facilities in a large U.S. health care database, this study assessed the frequency of and risk factors for developing a severe COVID-19 outcome after completing a primary COVID-19 vaccination series (primary vaccination), defined as receipt of 2 doses of an mRNA vaccine (BNT162b2 [Pfizer-BioNTech] or mRNA-1273 [Moderna]) or a single dose of JNJ-78436735 [Janssen (Johnson & Johnson)] ≥14 days before illness onset. Severe COVID-19 outcomes were defined as hospitalization with a diagnosis of acute respiratory failure, need for noninvasive ventilation (NIV), admission to an intensive care unit (ICU) including all persons requiring invasive mechanical ventilation, or death (including discharge to hospice). Among 1,228,664 persons who completed primary vaccination during December 2020-October 2021, a total of 2,246 (18.0 per 10,000 vaccinated persons) developed COVID-19 and 189 (1.5 per 10,000) had a severe outcome, including 36 who died (0.3 deaths per 10,000). Risk for severe outcomes was higher among persons who were aged ≥65 years, were immunosuppressed, or had at least one of six other underlying conditions. All persons with severe outcomes had at least one of these risk factors, and 77.8% of those who died had four or more risk factors. Severe COVID-19 outcomes after primary vaccination are rare; however, vaccinated persons who are aged ≥65 years, are immunosuppressed, or have other underlying conditions might be at increased risk. These persons should receive targeted interventions including chronic disease management, precautions to reduce exposure, additional primary and booster vaccine doses, and effective pharmaceutical therapy as indicated to reduce risk for severe COVID-19 outcomes. Increasing COVID-19 vaccination coverage is a public health priority.