ABSTRACT
Lower respiratory tract infections (LRTIs) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, noninfectious inflammatory syndromes resembling LRTIs further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome, and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed a rules-based model (RBM) and logistic regression model (LRM) in a derivation cohort of 20 patients with LRTIs or noninfectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an area under the receiver-operating curve (AUC) of 0.96 (95% CI, 0.86-1.00), the diversity metric with an AUC of 0.80 (95% CI, 0.63-0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI, 0.75-1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for LRTI diagnosis.
Subject(s)
Respiratory Tract Infections/diagnosis , Respiratory Tract Infections/immunology , Sequence Analysis, DNA/methods , Adult , Aged , Aged, 80 and over , Area Under Curve , Case-Control Studies , Cohort Studies , Critical Illness , Female , Humans , Male , Microbiota/genetics , Middle Aged , Predictive Value of Tests , Respiratory Tract Infections/microbiology , Transcriptome/genetics , Whole Genome Sequencing/methodsABSTRACT
BACKGROUND: Recurrent pleural effusions are a major cause of morbidity and frequently lead to hospitalization. Indwelling pleural catheters (IPCs) are tunneled catheters that allow ambulatory intermittent drainage of pleural fluid without repeated thoracentesis. Despite the efficacy and safety of IPCs, data supporting postplacement follow-up is limited and variable. Our study aims to characterize the impact of a dedicated pleural clinic (PC) on patient outcomes as they relate to IPCs. METHODS: Patients who underwent IPC placement between 2015 and 2021 were included in this retrospective study. Differences in outcomes were analyzed between patients with an IPC placed and managed by Interventional Pulmonology (IP) through the PC and those placed by non-IP services (non-PC providers) before and after the PC implementation. RESULTS: In total, 371 patients received IPCs. Since the implementation of the PC, there was an increase in ambulatory IPC placement (31/133 pre-PC vs. 96/238 post-PC; P =0.001). There were fewer admissions before IPC placement (18/103 vs. 43/133; P =0.01), and fewer thoracenteses per patient (2.7±2.5 in PC cohort vs. 4±5.1 in non-PC cohort; P <0.01). The frequency of pleurodesis was higher in the PC cohort (40/103 vs. 41/268; P <0.001). A Fine and Gray competing risks model indicated higher likelihood of pleurodesis in the PC cohort (adjusted subhazard ratio 3.8, 95% CI: 2.5-5.87). CONCLUSION: Our experience suggests that the implementation of a dedicated PC can lead to improved patient outcomes including fewer procedures and admissions before IPC placement, and increased rates of pleurodesis with IPC removal.
Subject(s)
Pleural Effusion, Malignant , Humans , Retrospective Studies , Pleural Effusion, Malignant/therapy , Pleural Effusion, Malignant/etiology , Catheterization , Catheters, Indwelling/adverse effects , Pleurodesis/methods , Drainage/methodsABSTRACT
STUDY OBJECTIVES: To examine the association of self-identified race with sleep quality in heavy smokers. METHODS: We studied baseline data from 1965 non-Hispanic White and 462 African American participants from SPIROMICS with ≥ 20 pack-years smoking history. We first examined the Pittsburgh Sleep Quality Index's (PSQI) internal consistency and item-total correlation in a population with chronic obstructive pulmonary disease. We then used staged multivariable regression to investigate the association of race and sleep quality as measured by the PSQI) The first model included demographics, the second added measures of health status, and the third, indicators of socioeconomic status. We next explored the correlation between sleep quality with 6-minute walk distance and St. George's Respiratory Questionnaire score as chronic obstructive pulmonary disease-relevant outcomes. We tested for interactions between self-identified race and the most important determinants of sleep quality in our conceptual model. RESULTS: We found that the PSQI had good internal consistency and item-total correlation in our study population of heavy smokers with and without chronic obstructive pulmonary disease. African American race was associated with increased PSQI in univariable analysis and after adjustment for demographics, health status, and socioenvironmental exposures (P = .02; 0.44 95%CI: .06 to .83). Increased PSQI was associated with higher postbronchodilator forced expiratory volume in 1 second and lower household income, higher depressive symptoms, and female sex. We identified an interaction wherein depressive symptoms had a greater impact on PSQI score for non-Hispanic White than African American participants (P for interaction = .01). CONCLUSIONS: In heavy smokers, self-reported African American race is independently associated with worse sleep quality. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov; Name: Study of COPD Subgroups and Biomarkers (SPIROMICS); URL: https://clinicaltrials.gov/ct2/show/NCT01969344; Identifier: NCT01969344. CITATION: Baugh AD, Acho M, Arhin A, et al. African American race is associated with worse sleep quality in heavy smokers. J Clin Sleep Med. 2023;19(8):1523-1532.
Subject(s)
Pulmonary Disease, Chronic Obstructive , Smokers , Humans , Female , Black or African American , Sleep Quality , Quality of LifeABSTRACT
BACKGROUND: Antimicrobial resistance (AMR) is rising at an alarming rate and complicating the management of infectious diseases including lower respiratory tract infections (LRTI). Metagenomic next-generation sequencing (mNGS) is a recently established method for culture-independent LRTI diagnosis, but its utility for predicting AMR has remained unclear. We aimed to assess the performance of mNGS for AMR prediction in bacterial LRTI and demonstrate proof of concept for epidemiological AMR surveillance and rapid AMR gene detection using Cas9 enrichment and nanopore sequencing. METHODS: We studied 88 patients with acute respiratory failure between 07/2013 and 9/2018, enrolled through a previous observational study of LRTI. Inclusion criteria were age ≥ 18, need for mechanical ventilation, and respiratory specimen collection within 72 h of intubation. Exclusion criteria were decline of study participation, unclear LRTI status, or no matched RNA and DNA mNGS data from a respiratory specimen. Patients with LRTI were identified by clinical adjudication. mNGS was performed on lower respiratory tract specimens. The primary outcome was mNGS performance for predicting phenotypic antimicrobial susceptibility and was assessed in patients with LRTI from culture-confirmed bacterial pathogens with clinical antimicrobial susceptibility testing (n = 27 patients, n = 32 pathogens). Secondary outcomes included the association between hospital exposure and AMR gene burden in the respiratory microbiome (n = 88 patients), and AMR gene detection using Cas9 targeted enrichment and nanopore sequencing (n = 10 patients). RESULTS: Compared to clinical antimicrobial susceptibility testing, the performance of respiratory mNGS for predicting AMR varied by pathogen, antimicrobial, and nucleic acid type sequenced. For gram-positive bacteria, a combination of RNA + DNA mNGS achieved a sensitivity of 70% (95% confidence interval (CI) 47-87%) and specificity of 95% (CI 85-99%). For gram-negative bacteria, sensitivity was 100% (CI 87-100%) and specificity 64% (CI 48-78%). Patients with hospital-onset LRTI had a greater AMR gene burden in their respiratory microbiome versus those with community-onset LRTI (p = 0.00030), or those without LRTI (p = 0.0024). We found that Cas9 targeted sequencing could enrich for low abundance AMR genes by > 2500-fold and enabled their rapid detection using a nanopore platform. CONCLUSIONS: mNGS has utility for the detection and surveillance of resistant bacterial LRTI pathogens.
Subject(s)
Bacterial Infections , Respiratory Tract Infections , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Critical Illness , Drug Resistance, Bacterial/genetics , High-Throughput Nucleotide Sequencing/methods , Humans , Metagenomics/methods , RNA , Respiratory Tract Infections/diagnosis , Respiratory Tract Infections/drug therapy , Respiratory Tract Infections/microbiology , Sensitivity and SpecificityABSTRACT
Background: Following early implementation of public health measures, San Francisco has experienced a slow rise and a low peak level of coronavirus disease 2019 (COVID-19) cases and deaths. Methods and Findings: We included all patients with COVID-19 pneumonia admitted to the intensive care unit (ICU) at the safety net hospital for San Francisco through April 8, 2020. Each patient had ≥15 days of follow-up. Among 26 patients, the median age was 54 years (interquartile range, 43 to 62), 65% were men, and 77% were Latinx. Mechanical ventilation was initiated for 11 (42%) patients within 24 hours of ICU admission and 20 patients (77%) overall. The median duration of mechanical ventilation was 13.5 days (interquartile range, 5 to 20). Patients were managed with lung protective ventilation (tidal volume ≤8 ml/kg of ideal body weight and plateau pressure ≤30 cmH2O on 98% and 78% of ventilator days, respectively). Prone positioning was used for 13 of 20 (65%) ventilated patients for a median of 5 days (interquartile range, 2 to 10). Seventeen (65%) patients were discharged home, 1 (4%) was discharged to nursing home, 3 (12%) were discharged from the ICU, and 2 (8%) remain intubated in the ICU at the time of this report. Three (12%) patients have died. Conclusions: Good outcomes were achieved in critically ill patients with COVID-19 by using standard therapies for acute respiratory distress syndrome (ARDS) such as lung protective ventilation and prone positioning. Ensuring hospitals can deliver sustained high-quality and evidence-based critical care to patients with ARDS should remain a priority.
ABSTRACT
BACKGROUND: Most data on the clinical presentation, diagnostics, and outcomes of patients with COVID-19 have been presented as case series without comparison to patients with other acute respiratory illnesses. METHODS: We examined emergency department patients between February 3 and March 31, 2020 with an acute respiratory illness who were tested for SARS-CoV-2. We determined COVID-19 status by PCR and metagenomic next generation sequencing (mNGS). We compared clinical presentation, diagnostics, treatment, and outcomes. FINDINGS: Among 316 patients, 33 tested positive for SARS-CoV-2; 31 without COVID-19 tested positive for another respiratory virus. Among patients with additional viral testing (27/33), no SARS-CoV-2 co-infections were identified. Compared to those who tested negative, patients with COVID-19 reported longer symptoms duration (median 7d vs. 3d, p < 0.001). Patients with COVID-19 were more often hospitalized (79% vs. 56%, p = 0.014). When hospitalized, patients with COVID-19 had longer hospitalizations (median 10.7d vs. 4.7d, p < 0.001) and more often developed ARDS (23% vs. 3%, p < 0.001). Most comorbidities, medications, symptoms, vital signs, laboratories, treatments, and outcomes did not differ by COVID-19 status. INTERPRETATION: While we found differences in clinical features of COVID-19 compared to other acute respiratory illnesses, there was significant overlap in presentation and comorbidities. Patients with COVID-19 were more likely to be admitted to the hospital, have longer hospitalizations and develop ARDS, and were unlikely to have co-existent viral infections. FUNDING: National Center for Advancing Translational Sciences, National Heart Lung Blood Institute, National Institute of Allergy and Infectious Diseases, Chan Zuckerberg Biohub, Chan Zuckerberg Initiative.
ABSTRACT
BACKGROUND: Emerging data on the clinical presentation, diagnostics, and outcomes of patients with COVID-19 have largely been presented as case series. Few studies have compared these clinical features and outcomes of COVID-19 to other acute respiratory illnesses. METHODS: We examined all patients presenting to an emergency department in San Francisco, California between February 3 and March 31, 2020 with an acute respiratory illness who were tested for SARS-CoV-2. We determined COVID-19 status by PCR and metagenomic next generation sequencing (mNGS). We compared demographics, comorbidities, symptoms, vital signs, and laboratory results including viral diagnostics using PCR and mNGS. Among those hospitalized, we determined differences in treatment (antibiotics, antivirals, respiratory support) and outcomes (ICU admission, ICU interventions, acute respiratory distress syndrome, cardiac injury). FINDINGS: In a cohort of 316 patients, 33 (10%) tested positive for SARS-CoV-2; 31 patients, all without COVID-19, tested positive for another respiratory virus (16%). Among patients with additional viral testing, no co-infections with SARS-CoV-2 were identified by PCR or mNGS. Patients with COVID-19 reported longer symptoms duration (median 7 vs. 3 days), and were more likely to report fever (82% vs. 44%), fatigue (85% vs. 50%), and myalgias (61% vs 27%); p<0.001 for all comparisons. Lymphopenia (55% vs 34%, p=0.018) and bilateral opacities on initial chest radiograph (55% vs. 24%, p=0.001) were more common in patients with COVID-19. Patients with COVID-19 were more often hospitalized (79% vs. 56%, p=0.014). Of 186 hospitalized patients, patients with COVID-19 had longer hospitalizations (median 10.7d vs. 4.7d, p<0.001) and were more likely to develop ARDS (23% vs. 3%, p<0.001). Most comorbidities, home medications, signs and symptoms, vital signs, laboratory results, treatment, and outcomes did not differ by COVID-19 status. INTERPRETATION: While we found differences in clinical features of COVID-19 compared to other acute respiratory illnesses, there was significant overlap in presentation and comorbidities. Patients with COVID-19 were more likely to be admitted to the hospital, have longer hospitalizations and develop ARDS, and were unlikely to have co-existent viral infections. These findings enhance understanding of the clinical characteristics of COVID-19 in comparison to other acute respiratory illnesses. .
ABSTRACT
RESULTS: A total of 1,513 individuals underwent CTLS. Downstream data, pre-test cardiac risk factors and CAC scores were available for 88.3% (1,336/1,513). The average length of follow-up was 2.64 (SD ±0.72) years. There were a total of 43 events, occurring in 1.55% (6/386) of patients with mild CAC, 3.24% (11/339) of patients with moderate CAC, and 8.90% (26/292) of patients with marked CAC. There were no events among patients with no reported CAC (0/319). Using multivariable logistic modeling, the increased odds of an initial cardiac event was 2.56 (95% CI, 1.76-3.92, P<0.001) for mild CAC, 6.57 (95% CI, 3.10-15.4, P<0.001) for moderate CAC, and 16.8 (95% CI, 5.46-60.3, P<0.001) for marked CAC, as compared to individuals with no CAC. Time to event analysis showed distinct differences among the four CAC categories (P<0.001). CONCLUSIONS: Qualitative coronary artery calcification scoring of CTLS exams may provide a novel method to help select individuals at elevated risk for an initial cardiac event.