Background: Understanding of the diagnosis and treatment of adults with community-acquired pneumonia (CAP) has evolved thanks to new evidence, experience, and emerging technologies. This document updates evidence-based clinical practice guidelines on four key questions for the diagnosis and management of adult patients with CAP.Methods: A multidisciplinary panel integrated systematic reviews of comparative evidence with other relevant research and clinical experience, then applied Grading of Recommendations, Assessment, Development and Evaluation methodology to produce recommendations using the Evidence to Decision Framework.Results: The panel formulated clinical recommendations that address questions related to CAP, including lung ultrasound for diagnosis, empiric antibacterial therapy if a test result for a respiratory virus is positive, antibiotic duration, and the use of systemic corticosteroids.Conclusions: The panel formulated and provided the rationale for recommendations on selected diagnostic and treatment strategies for adult patients with CAP.

OBJECTIVE:We assessed the impact of an oral care initiative on non-ventilator-associated hospital-acquired pneumonia (NV-HAP) risk using two different measurement strategies. METHODS:We evaluated changes in NV-HAP events among all patients admitted to 17 VA Medical Centers (1) across the period 10/01/2015-12/31/2019, and (2) one-year pre- vs post- each hospital's oral care initiative start date. We modeled and compared observed versus predicted NV-HAP events per hospitalization using (1) an electronic clinical definition and (2) diagnosis codes, adjusting for patients' demographics, vital signs, and laboratory results at presentation. RESULTS:Among 333,257 hospitalizations, 1,922 (0.58%) met NV-HAP electronic clinical criteria and 2,386 (0.72%) diagnostic coding criteria. The risk of NV-HAP defined by electronic clinical criteria was 0.62% in October 2015 and 0.54% in December 2019 (estimated difference -0.084% [95% CI: -0.17%, 0.0056%]; the risk of NV-HAP defined by diagnostic coding decreased from 1.0% to 0.48% (estimated difference -0.53% [-0.63%, -0.43%]). In the one-year pre- vs post-analysis, there was no evidence of effect of the implementation on NV-HAP using either electronic clinical criteria (adjusted risk difference -0.078% (95% CI: -0.25%, 0.091%) or diagnostic coding criteria (adjusted risk difference -0.021% (95% CI: -0.18%, 0.14%). CONCLUSIONS:In a large multi-center study of hospitalized patients, we were unable to identify a clear effect of an oral care initiative on NV-HAP using electronic clinical criteria or diagnostic coding criteria.

Objectives We sought to (1) characterize the process of diagnosing pneumonia in an emergency department (ED) and (2) examine clinician reactions to a clinician-facing diagnostic discordance feedback tool.Materials and Methods We designed a diagnostic feedback tool, using electronic health record data from ED clinicians' patients to establish concordance or discordance between ED diagnosis, radiology reports, and hospital discharge diagnosis for pneumonia. We conducted semistructured interviews with 11 ED clinicians about pneumonia diagnosis and reactions to the feedback tool. We administered surveys measuring individual differences in mindset beliefs, comfort with feedback, and feedback tool usability. We qualitatively analyzed interview transcripts and descriptively analyzed survey data.Results Thematic results revealed: (1) the diagnostic process for pneumonia in the ED is characterized by diagnostic uncertainty and may be secondary to goals to treat and dispose the patient; (2) clinician diagnostic self-evaluation is a fragmented, inconsistent process of case review and follow-up that a feedback tool could fill; (3) the feedback tool was described favorably, with task and normative feedback harnessing clinician values of high-quality patient care and personal excellence; and (4) strong reactions to diagnostic feedback varied from implicit trust to profound skepticism about the validity of the concordance metric. Survey results suggested a relationship between clinicians' individual differences in learning and failure beliefs, feedback experience, and usability ratings.Discussion and Conclusion Clinicians value feedback on pneumonia diagnoses. Our results highlight the importance of feedback about diagnostic performance and suggest directions for considering individual differences in feedback tool design and implementation.

Background Community-acquired pneumonia is a well-studied condition; yet, in the urgent care setting, patient characteristics and adherence to guideline-recommended care are poorly described. Within Intermountain Health, a nonprofit integrated US health care system based in Utah, more patients present to urgent care clinics (UCCs) than emergency departments (EDs) for pneumonia care. Methods We performed a retrospective cohort study 1 January 2019 through 31 December 2020 in 28 UCCs within Utah. We extracted electronic health record data for patients aged ≥12 years with ICD-10 pneumonia diagnoses entered by the bedside clinician, excluding patients with preceding pneumonia within 30 days or missing vital signs. We compared UCC patients with radiographic pneumonia (n = 4689), without radiographic pneumonia (n = 1053), without chest imaging (n = 1472), and matched controls with acute cough/bronchitis (n = 15 972). Additional outcomes were 30-day mortality and the proportion of patients with ED visits or hospital admission within 7 days after the index encounter. Results UCC patients diagnosed with pneumonia and possible/likely radiographic pneumonia by radiologist report had a mean age of 40 years and 52% were female. Almost all patients with pneumonia (93%) were treated with antibiotics, including those without radiographic confirmation. Hospital admissions and ED visits within 7 days were more common in patients with radiographic pneumonia vs patients with “unlikely” radiographs (6% vs 2% and 10% vs 6%, respectively). Observed 30-day all-cause mortality was low (0.26%). Patients diagnosed without chest imaging presented similarly to matched patients with cough/acute bronchitis. Most patients admitted to the hospital the same day after the UCC visit (84%) had an interim ED encounter. Pneumonia severity scores (pneumonia severity index, electronic CURB-65, and shock index) overestimated patient need for hospitalization. Conclusions Most UCC patients with pneumonia were successfully treated as outpatients. Opportunities to improve care include clinical decision support for diagnosing pneumonia with radiographic confirmation and development of pneumonia severity scores tailored to the UCC.

Continued improvements in the treatment of pulmonary infections have paradoxically resulted in a growing challenge of individuals with postinfectious pulmonary complications (PIPCs). PIPCs have been long recognized after tuberculosis, but recent experiences such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic have underscored the importance of PIPCs following other lower respiratory tract infections. Independent of the causative pathogen, most available studies of pulmonary infections focus on short-term outcomes rather than long-term morbidity among survivors. In this document, we establish a conceptual scope for PIPCs with discussion of globally significant pulmonary pathogens and an examination of how these pathogens can damage different components of the lung, resulting in a spectrum of PIPCs. We also review potential mechanisms for the transition from acute infection to PIPC, including the interplay between pathogen- mediated injury and aberrant host responses, which together result in PIPCs. Finally, we identify cross-cutting research priorities for the field to facilitate future studies to establish the incidence of PIPCs, define common mechanisms, identify therapeutic strategies, and ultimately reduce the burden of morbidity in survivors of pulmonary infections.

Diagnostic error, a cause of substantial morbidity and mortality, is largely discovered and evaluated through self-report and manual review, which is costly and not suitable to real-time intervention. Opportunities exist to leverage electronic health record data for automated detection of potential misdiagnosis, executed at scale and generalized across diseases. We propose a novel automated approach to identifying diagnostic divergence considering both diagnosis and risk of mortality. Our objective was to identify cases of emergency department infectious disease misdiagnoses by measuring the deviation between predicted diagnosis and documented diagnosis, weighted by mortality. Two machine learning models were trained for prediction of infectious disease and mortality using the first 24h of data. Charts were manually reviewed by clinicians to determine whether there could have been a more correct or timely diagnosis. The proposed approach was validated against manual reviews and compared using the Spearman rank correlation. We analyzed 6.5 million ED visits and over 700 million associated clinical features from over one hundred emergency departments. The testing set performances of the infectious disease (Macro F1 = 86.7, AUROC 90.6 to 94.7) and mortality model (Macro F1 = 97.6, AUROC 89.1 to 89.1) were in expected ranges. Human reviews and the proposed automated metric demonstrated positive correlations ranging from 0.231 to 0.358. The proposed approach for diagnostic deviation shows promise as a potential tool for clinicians to find diagnostic errors. Given the vast number of clinical features used in this analysis, further improvements likely need to either take greater account of data structure (what occurs before when) or involve natural language processing. Further work is needed to explain the potential reasons for divergence and to refine and validate the approach for implementation in real-world settings.

During COVID-19 in the US, social determinants of health (SDH) have driven health disparities. However, the use of SDH in COVID-19 vaccine modeling is unclear. This review aimed to summarize the current landscape of incorporating SDH into COVID-19 vaccine transmission modeling in the US. Medline and Embase were searched up to October 2022. We included studies that used transmission modeling to assess the effects of COVID-19 vaccine strategies in the US. Studies’ characteristics, factors incorporated into models, and approaches to incorporate these factors were extracted. Ninety-two studies were included. Of these, 11 studies incorporated SDH factors (alone or combined with demographic factors). Various sets of SDH factors were integrated, with occupation being the most common (8 studies), followed by geographical location (5 studies). The results show that few studies incorporate SDHs into their models, highlighting the need for research on SDH impact and approaches to incorporating SDH into modeling.FundingThis research was funded by the Centers for Disease Control and Prevention (CDC).

BACKGROUND:Evidence-based practice in community-acquired pneumonia often assumes an accurate initial diagnosis. OBJECTIVE:To examine the evolution of pneumonia diagnoses among patients hospitalized from the emergency department (ED). DESIGN:Retrospective nationwide cohort. SETTING:118 U.S. Veterans Affairs medical centers. PATIENTS:Aged 18 years or older and hospitalized from the ED between 1 January 2015 and 31 January 2022. MEASUREMENTS:Discordances between initial pneumonia diagnosis, discharge diagnosis, and radiographic diagnosis identified by natural language processing of clinician text, diagnostic coding, and antimicrobial treatment. Expressions of uncertainty in clinical notes, patient illness severity, treatments, and outcomes were compared. RESULTS:Among 2 383 899 hospitalizations, 13.3% received an initial or discharge diagnosis and treatment of pneumonia: 9.1% received an initial diagnosis and 10.0% received a discharge diagnosis. Discordances between initial and discharge occurred in 57%. Among patients discharged with a pneumonia diagnosis and positive initial chest image, 33% lacked an initial diagnosis. Among patients diagnosed initially, 36% lacked a discharge diagnosis and 21% lacked positive initial chest imaging. Uncertainty was frequently expressed in clinical notes (58% in ED; 48% at discharge); 27% received diuretics, 36% received corticosteroids, and 10% received antibiotics, corticosteroids, and diuretics within 24 hours. Patients with discordant diagnoses had greater uncertainty and received more additional treatments, but only patients lacking an initial pneumonia diagnosis had higher 30-day mortality than concordant patients (14.4% [95% CI, 14.1% to 14.7%] vs. 10.6% [CI, 10.4% to 10.7%]). Patients with diagnostic discordance were more likely to present to high-complexity facilities with high ED patient load and inpatient census. LIMITATION:Retrospective analysis; did not examine causal relationships. CONCLUSION:More than half of all patients hospitalized and treated for pneumonia had discordant diagnoses from initial presentation to discharge. Treatments for other diagnoses and expressions of uncertainty were common. These findings highlight the need to recognize diagnostic uncertainty and treatment ambiguity in research and practice of pneumonia-related care. PRIMARY FUNDING SOURCE:The Gordon and Betty Moore Foundation.

OBJECTIVES:To determine if the implementation of automated clinical decision support (CDS) with embedded minor severe community-acquired pneumonia (sCAP) criteria was associated with improved ICU utilization among emergency department (ED) patients with pneumonia who did not require vasopressors or positive pressure ventilation at admission. DESIGN:Planned secondary analysis of a stepped-wedge, cluster-controlled CDS implementation trial. SETTING:Sixteen hospitals in six geographic clusters from Intermountain Health; a large, integrated, nonprofit health system in Utah and Idaho. PATIENTS:Adults admitted to the hospital from the ED with pneumonia identified by: 1) discharge International Classification of Diseases, 10th Revision codes for pneumonia or sepsis/respiratory failure and 2) ED chest imaging consistent with pneumonia, who did not require vasopressors or positive pressure ventilation at admission. INTERVENTIONS:After implementation, patients were exposed to automated, open-loop, comprehensive CDS that aided disposition decision (ward vs. ICU), based on objective severity scores (sCAP). MEASUREMENTS AND MAIN RESULTS:The analysis included 2747 patients, 1814 before and 933 after implementation. The median age was 71, median Elixhauser index was 17, 48% were female, and 95% were Caucasian. A mixed-effects regression model with cluster as the random effect estimated that implementation of CDS utilizing sCAP increased 30-day ICU-free days by 1.04 days (95% CI, 0.48-1.59; p < 0.001). Among secondary outcomes, the odds of being admitted to the ward, transferring to the ICU within 72 hours, and receiving a critical therapy decreased by 57% (odds ratio [OR], 0.43; 95% CI, 0.26-0.68; p < 0.001) post-implementation; mortality within 72 hours of admission was unchanged (OR, 1.08; 95% CI, 0.56-2.01; p = 0.82) while 30-day all-cause mortality was lower post-implementation (OR, 0.71; 95% CI, 0.52-0.96; p = 0.03). CONCLUSIONS:Implementation of electronic CDS using minor sCAP criteria to guide disposition of patients with pneumonia from the ED was associated with safe reduction in ICU utilization.

Meta-analyses have investigated associations between race and ethnicity and COVID-19 outcomes. However, there is uncertainty about these associations' existence, magnitude, and level of evidence. We, therefore, aimed to synthesize, quantify, and grade the strength of evidence of race and ethnicity and COVID-19 outcomes in the US.

Distributed through the core of the brainstem and forebrain, neuronal populations, which utilize particular neurotransmitters and project in a widespread or diffuse manner through ascending relays to the cortex and/or descending relays to the spinal cord, generate sleep–wake states. Ascending systems stimulate cortical activation and include glutamatergic neurons of the reticular formation (RF) and nonspecific thalamo-cortical projection system and cholinergic neurons of the pontomesencephalic tegmentum and basal forebrain (BF). Overlapping diffuse or descending systems also stimulate behavioral arousal with muscle tone and include glutamatergic, noradrenergic, histaminergic, and orexinergic neurons. Neurons of the activating and arousal systems are inhibited during slow-wave sleep (SWS) and/or paradoxical sleep (PS) largely by GABAergic neurons.

Abstract Objective: Surveillance of non–ventilator-associated hospital-acquired pneumonia (NV-HAP) is complicated by subjectivity and variability in diagnosing pneumonia. We compared a fully automatable surveillance definition using routine electronic health record data to manual determinations of NV-HAP according to surveillance criteria and clinical diagnoses. Methods: We retrospectively applied an electronic surveillance definition for NV-HAP to all adults admitted to Veterans’ Affairs (VA) hospitals from January 1, 2015, to November 30, 2020. We randomly selected 250 hospitalizations meeting NV-HAP surveillance criteria for independent review by 2 clinicians and calculated the percent of hospitalizations with (1) clinical deterioration, (2) CDC National Healthcare Safety Network (CDC-NHSN) criteria, (3) NV-HAP according to a reviewer, (4) NV-HAP according to a treating clinician, (5) pneumonia diagnosis in discharge summary; and (6) discharge diagnosis codes for HAP. We assessed interrater reliability by calculating simple agreement and the Cohen κ (kappa). Results: Among 3.1 million hospitalizations, 14,023 met NV-HAP electronic surveillance criteria. Among reviewed cases, 98% had a confirmed clinical deterioration; 67% met CDC-NHSN criteria; 71% had NV-HAP according to a reviewer; 60% had NV-HAP according to a treating clinician; 49% had a discharge summary diagnosis of pneumonia; and 82% had NV-HAP according to any definition according to at least 1 reviewer. Only 8% had diagnosis codes for HAP. Interrater agreement was 75% (κ = 0.50) for CDC-NHSN criteria and 78% (κ = 0.55) for reviewer diagnosis of NV-HAP. Conclusions: Electronic NV-HAP surveillance criteria correlated moderately with existing manual surveillance criteria. Reviewer variability for all manual assessments was high. Electronic surveillance using clinical data may therefore allow for more consistent and efficient surveillance with similar accuracy compared to manual assessments or diagnosis codes.

Michael E. Ohl, MD, MSPH; Kelly Richardson Miell, PhD; Brice F. Beck, MA; Bradley Mecham, PhD; George Bailey, MS; Michelle Mengeling, PhD; Mary Vaughan-Sarrazin, PhD

Background Over 870 000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have occurred among Veterans Health Administration users, and 24 000 have resulted in death. We examined early outcomes of SARS-CoV-2 infection in hospitalized veterans. Methods In an ongoing, prospective cohort study, we enrolled veterans age ≥18 tested for SARS-CoV-2 and hospitalized at 15 Department of Veterans Affairs medical centers between February 2021 and June 2022. We estimated adjusted odds ratios (aORs), adjusted incidence rate ratios (aIRRs), and adjusted hazard ratios (aHRs) for maximum illness severity within 30 days of study entry (defined using the 4-category VA Severity Index for coronavirus disease 2019 [COVID-19]), as well as length of hospitalization and rehospitalization within 60 days, in relationship with demographic characteristics, Charlson comorbidity index (CCI), COVID-19 vaccination, and calendar period of enrollment. Results The 542 participants included 329 (61%) who completed a primary vaccine series (with or without booster; "vaccinated"), 292 (54%) enrolled as SARS-CoV-2-positive, and 503 (93%) men, with a mean age of 64.4 years. High CCI scores (≥5) occurred in 61 (44%) vaccinated and 29 (19%) unvaccinated SARS-CoV-2-positive participants. Severe illness or death occurred in 29 (21%; 6% died) vaccinated and 31 (20%; 2% died) unvaccinated SARS-CoV-2-positive participants. SARS-CoV-2-positive inpatients per unit increase in CCI had greater multivariable-adjusted odds of severe illness (aOR, 1.21; 95% CI, 1.01-1.45), more hospitalization days (aIRR, 1.06; 95% CI, 1.03-1.10), and rehospitalization (aHR, 1.07; 95% CI, 1.01-1.12). Conclusions In a cohort of hospitalized US veterans with SARS-CoV-2 infection, those with a higher CCI had more severe COVID-19 illness, more hospital days, and rehospitalization, after adjusting for vaccination status, age, sex, and calendar period.

Importance Non–ventilator-associated hospital-acquired pneumonia (NV-HAP) is a common and deadly hospital-acquired infection. However, inconsistent surveillance methods and unclear estimates of attributable mortality challenge prevention. Objective To estimate the incidence, variability, outcomes, and population attributable mortality of NV-HAP. Design, Setting, and Participants This cohort study retrospectively applied clinical surveillance criteria for NV-HAP to electronic health record data from 284 US hospitals. Adult patients admitted to the Veterans Health Administration hospital from 2015 to 2020 and HCA Healthcare hospitals from 2018 to 2020 were included. The medical records of 250 patients who met the surveillance criteria were reviewed for accuracy. Exposures NV-HAP, defined as sustained deterioration in oxygenation for 2 or more days in a patient who was not ventilated concurrent with abnormal temperature or white blood cell count, performance of chest imaging, and 3 or more days of new antibiotics. Main Outcomes and Measures NV-HAP incidence, length-of-stay, and crude inpatient mortality. Attributable inpatient mortality by 60 days follow-up was estimated using inverse probability weighting, accounting for both baseline and time-varying confounding. Results Among 6 022 185 hospitalizations (median [IQR] age, 66 [54-75] years; 1 829 475 [26.1%] female), there were 32 797 NV-HAP events (0.55 per 100 admissions [95% CI, 0.54-0.55] per 100 admissions and 0.96 per 1000 patient-days [95% CI, 0.95-0.97] per 1000 patient-days). Patients with NV-HAP had multiple comorbidities (median [IQR], 6 [4-7]), including congestive heart failure (9680 [29.5%]), neurologic conditions (8255 [25.2%]), chronic lung disease (6439 [19.6%]), and cancer (5,467 [16.7%]); 24 568 cases (74.9%) occurred outside intensive care units. Crude inpatient mortality was 22.4% (7361 of 32 797) for NV-HAP vs 1.9% (115 530 of 6 022 185) for all hospitalizations; 12 449 (8.0%) were discharged to hospice. Median [IQR] length-of-stay was 16 (11-26) days vs 4 (3-6) days. On medical record review, pneumonia was confirmed by reviewers or bedside clinicians in 202 of 250 patients (81%). It was estimated that NV-HAP accounted for 7.3% (95% CI, 7.1%-7.5%) of all hospital deaths (total hospital population inpatient death risk of 1.87% with NV-HAP events included vs 1.73% with NV-HAP events excluded; risk ratio, 0.927; 95% CI, 0.925-0.929). Conclusions and Relevance In this cohort study, NV-HAP, which was defined using electronic surveillance criteria, was present in approximately 1 in 200 hospitalizations, of whom 1 in 5 died in the hospital. NV-HAP may account for up to 7% of all hospital deaths. These findings underscore the need to systematically monitor NV-HAP, define best practices for prevention, and track their impact.

OBJECTIVES:Age is important for prognosis in community-onset pneumonia, but how it influences admission decisions in the emergency department (ED) is not well characterized. Using clinical data from the electronic health record in a national cohort, we examined pneumonia hospitalization patterns, variation, and relationships with mortality among older versus younger Veterans. METHODS:In a retrospective cohort of patients ≥ 18 years presenting to EDs with a diagnosis of pneumonia at 118 VA Medical Centers January 1, 2006, to December 31, 2016, we compared observed, predicted, and residual hospitalization risk for Veterans < 70, 70-79, and ≥ 80 years of age using generalized estimating equations and machine learning models with 71 patient factors. We examined facility variation in residual hospitalization across facilities and explored whether facility differences in hospitalization risk correlated with differences in 30-day mortality. RESULTS:Among 297,498 encounters, 165,003 (55%) were for Veterans < 70 years, 61,076 (21%) 70-80, and 71,419 (24%) ≥ 80. Hospitalization rates were 52%, 67%, and 76%, respectively. After other patient factors were adjusting for, age 70-79 had an odds ratio (OR) of 1.39 (95% confidence interval [CI] 1.34-1.44) and ≥ 80 had an OR of 2.1 (95% CI 2.0-2.2) compared to age < 70. There was substantial variation in hospitalization across facilities among Veterans < 70 (<35% hospitalization at the lowest decile of facilities vs. > 66% at the highest decile) that was similar but with higher risk for patients 70-79 years (54% vs. 82%) and ≥ 80 years (59% vs. 85%) and remained after accounting for patient factors, with no consistently positive or negative associations with facility-level 30-day mortality. CONCLUSIONS:Older Veterans with community-onset pneumonia experience high risk of hospitalization, with widespread facility variation that has no clear relationship to short-term mortality.

Pneumonia imposes a significant clinical burden on people with immunocompromising conditions. Millions of individuals live with compromised immunity because of cytotoxic cancer treatments, biological therapies, organ transplants, inherited and acquired immunodeficiencies, and other immune disorders. Despite broad awareness among clinicians that these patients are at increased risk for developing infectious pneumonia, immunocompromised people are often excluded from pneumonia clinical guidelines and treatment trials. The absence of a widely accepted definition for immunocompromised host pneumonia is a significant knowledge gap that hampers consistent clinical care and research for infectious pneumonia in these vulnerable populations. To address this gap, the American Thoracic Society convened a workshop whose participants had expertise in pulmonary disease, infectious diseases, immunology, genetics, and laboratory medicine, with the goal of defining the entity of immunocompromised host pneumonia and its diagnostic criteria.