Feasibility and utility of a combined nasogastric-tube-and-string-test device for bacteriologic confirmation of pulmonary tuberculosis in young children.

For microbiological confirmation of pediatric pulmonary tuberculosis (PTB), gastric aspirates (GA) are often operationally unfeasible without hospitalization, and the encapsulated orogastric string test is not easily swallowed in young children. The Combined-NasoGastric-Tube-and-String-Test (CNGTST) enables dual collection of GA and string specimens. In a prospective cohort study in Kenya, we examined its feasibility in children under five with presumptive PTB and compared the bacteriological yield of string to GA. Paired GA and string samples were successfully collected in 95.6 % (281/294) of children. Mycobacterium tuberculosis was isolated from 7.0 % (38/541) of GA and 4.3 % (23/541) of string samples, diagnosing 8.2 % (23/281) of children using GA and 5.3 % (15/281) using string. The CNGTST was feasible in nearly all children. Yield from string was two-thirds that of GA despite a half-hour median dwelling time. In settings where the feasibility of hospitalisation for GA is uncertain, the string component can be used to confirm PTB.

Predicting Food Sources of Listeria monocytogenes Based on Genomic Profiling Using Random Forest Model.

Listeria monocytogenes can cause severe foodborne illness, including miscarriage during pregnancy or death in newborn infants. When outbreaks of L. monocytogenes illness occur, it may be possible to determine the food source of the outbreak. However, most reported L. monocytogenes illnesses do not occur as part of a recognized outbreak and most of the time the food source of sporadic L. monocytogenes illness in people cannot be determined. In the United States, L. monocytogenes isolates from patients, foods, and environments are routinely sequenced and analyzed by whole genome multilocus sequence typing (wgMLST) for outbreak detection by PulseNet, the national molecular surveillance system for foodborne illnesses. We investigated whether machine learning approaches applied to wgMLST allele call data could assist in attribution analysis of food source of L. monocytogenes isolates. We compiled isolates with a known source from five food categories (dairy, fruit, meat, seafood, and vegetable) using the metadata of L. monocytogenes isolates in PulseNet, deduplicated closely genetically related isolates, and developed random forest models to predict the food sources of isolates. Prediction accuracy of the final model varied across the food categories; it was highest for meat (65%), followed by fruit (45%), vegetable (45%), dairy (44%), and seafood (37%); overall accuracy was 49%, compared with the naive prediction accuracy of 28%. Our results show that random forest can be used to capture genetically complex features of high-resolution wgMLST for attribution of isolates to their sources.

Machine learning to predict bacteriologic confirmation of Mycobacterium tuberculosis in infants and very young children.

Diagnosis of tuberculosis (TB) among young children (<5 years) is challenging due to the paucibacillary nature of clinical disease and clinical similarities to other childhood diseases. We used machine learning to develop accurate prediction models of microbial confirmation with simply defined and easily obtainable clinical, demographic, and radiologic factors. We evaluated eleven supervised machine learning models (using stepwise regression, regularized regression, decision tree, and support vector machine approaches) to predict microbial confirmation in young children (<5 years) using samples from invasive (reference-standard) or noninvasive procedure. Models were trained and tested using data from a large prospective cohort of young children with symptoms suggestive of TB in Kenya. Model performance was evaluated using areas under the receiver operating curve (AUROC) and precision-recall curve (AUPRC), accuracy metrics. (i.e., sensitivity, specificity), F-beta scores, Cohen's Kappa, and Matthew's Correlation Coefficient. Among 262 included children, 29 (11%) were microbially confirmed using any sampling technique. Models were accurate at predicting microbial confirmation in samples obtained from invasive procedures (AUROC range: 0.84-0.90) and from noninvasive procedures (AUROC range: 0.83-0.89). History of household contact with a confirmed case of TB, immunological evidence of TB infection, and a chest x-ray consistent with TB disease were consistently influential across models. Our results suggest machine learning can accurately predict microbial confirmation of M. tuberculosis in young children using simply defined features and increase the bacteriologic yield in diagnostic cohorts. These findings may facilitate clinical decision making and guide clinical research into novel biomarkers of TB disease in young children.

Use of High-Resolution Geospatial and Genomic Data to Characterize Recent Tuberculosis Transmission, Botswana.

Combining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis transmission in high-burden tuberculosis (TB) settings. We performed whole-genome sequencing on M. tuberculosis DNA extracted from sputum cultures from a population-based TB study conducted in Gaborone, Botswana, during 2012-2016. We determined spatial distribution of cases on the basis of shared genotypes among isolates. We considered clusters of isolates with ≤5 single-nucleotide polymorphisms identified by whole-genome sequencing to indicate recent transmission and clusters of ≥10 persons to be outbreaks. We obtained both molecular and geospatial data for 946/1,449 (65%) participants with culture-confirmed TB; 62 persons belonged to 5 outbreaks of 10-19 persons each. We detected geospatial clustering in just 2 of those 5 outbreaks, suggesting heterogeneous spatial patterns. Our findings indicate that targeted interventions applied in smaller geographic areas of high-burden TB identified using integrated genomic and geospatial data might help interrupt TB transmission during outbreaks.

Development of treatment-decision algorithms for children evaluated for pulmonary tuberculosis: an individual participant data meta-analysis.

BACKGROUND: Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres. METHODS: For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings. FINDINGS: Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms. INTERPRETATION: We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance. FUNDING: WHO, US National Institutes of Health.

Longitudinal Analysis of Electronic Health Information to Identify Possible COVID-19 Sequelae.

Ongoing symptoms might follow acute COVID-19. Using electronic health information, we compared pre‒ and post‒COVID-19 diagnostic codes to identify symptoms that had higher encounter incidence in the post‒COVID-19 period as sequelae. This method can be used for hypothesis generation and ongoing monitoring of sequelae of COVID-19 and future emerging diseases.

Clinical and Radiologic Factors Associated With Detection of Mycobacterium tuberculosis in Children Under 5†Years old Using Invasive and Noninvasive Sample Collection Techniques-Kenya.

Background: Pediatric tuberculosis (TB) remains a critical public health concern, yet bacteriologic confirmation of TB in children is challenging. Clinical, demographic, and radiological factors associated with a positive Mycobacterium tuberculosis specimen in young children (≤5 years) are poorly understood. Methods: We conducted a prospective cohort study of young children with presumptive TB and examined clinical, demographic, and radiologic factors associated with invasive and noninvasive specimen collection techniques (gastric aspirate, induced sputum, nasopharyngeal aspirate, stool, and string test); up to 2 samples were taken per child, per technique. We estimated associations between these factors and a positive specimen for each technique using generalized estimating equations (GEEs) and logistic regression. Results: A median (range) of 544 (507-566) samples were obtained for each specimen collection technique from 300 enrolled children; bacteriologic yield was low across all collection techniques (range, 1%-7% from Xpert MTB/RIF or culture), except for lymph node fine needle aspiration (29%) taken for children with cervical lymphadenopathy. Factors associated with positive M. tuberculosis samples across all techniques included prolonged lethargy (median [range] adjusted odds ratio [aOR], 8.1 [3.9-10.1]), history of exposure with a TB case (median [range] aOR, 6.1 [2.9-9.0]), immunologic evidence of M. tuberculosis infection (median [range] aOR, 4.6 [3.7-9.2]), large airway compression (median [range] aOR, 6.7 [4.7-9.5]), and hilar/mediastinal density (median [range] aOR, 2.9 [1.7-3.2]). Conclusions: Identifying factors that lead to a positive M. tuberculosis specimen in very young children can inform clinical management and increase the efficiency of diagnostic testing in children being assessed for TB.

Severe Monkeypox in Hospitalized Patients - United States, August 10-October 10, 2022.

As of October 21, 2022, a total of 27,884 monkeypox cases (confirmed and probable) have been reported in the United States.§ Gay, bisexual, and other men who have sex with men have constituted a majority of cases, and persons with HIV infection and those from racial and ethnic minority groups have been disproportionately affected (1,2). During previous monkeypox outbreaks, severe manifestations of disease and poor outcomes have been reported among persons with HIV infection, particularly those with AIDS (3-5). This report summarizes findings from CDC clinical consultations provided for 57 patients aged ≥18 years who were hospitalized with severe manifestations of monkeypox¶ during August 10-October 10, 2022, and highlights three clinically representative cases. Overall, 47 (82%) patients had HIV infection, four (9%) of whom were receiving antiretroviral therapy (ART) before monkeypox diagnosis. Most patients were male (95%) and 68% were non-Hispanic Black (Black). Overall, 17 (30%) patients received intensive care unit (ICU)-level care, and 12 (21%) have died. As of this report, monkeypox was a cause of death or contributing factor in five of these deaths; six deaths remain under investigation to determine whether monkeypox was a causal or contributing factor; and in one death, monkeypox was not a cause or contributing factor.** Health care providers and public health professionals should be aware that severe morbidity and mortality associated with monkeypox have been observed during the current outbreak in the United States (6,7), particularly among highly immunocompromised persons. Providers should test all sexually active patients with suspected monkeypox for HIV at the time of monkeypox testing unless a patient is already known to have HIV infection. Providers should consider early commencement and extended duration of monkeypox-directed therapy†† in highly immunocompromised patients with suspected or laboratory-diagnosed monkeypox.§§ Engaging all persons with HIV in sustained care remains a critical public health priority.

Orthopoxvirus Testing Challenges for Persons in Populations at Low Risk or Without Known Epidemiologic Link to Monkeypox - United States, 2022.

Since May 2022, approximately 20,000 cases of monkeypox have been identified in the United States, part of a global outbreak occurring in approximately 90 countries and currently affecting primarily gay, bisexual, and other men who have sex with men (MSM) (1). Monkeypox virus (MPXV) spreads from person to person through close, prolonged contact; a small number of cases have occurred in populations who are not MSM (e.g., women and children), and testing is recommended for persons who meet the suspected case definition* (1). CDC previously developed five real-time polymerase chain reaction (PCR) assays for detection of orthopoxviruses from lesion specimens (2,3). CDC was granted 510(k) clearance for the nonvariola-orthopoxvirus (NVO)-specific PCR assay by the Food and Drug Administration. This assay was implemented within the Laboratory Response Network (LRN) in the early 2000s and became critical for early detection of MPXV and implementation of public health action in previous travel-associated cases as well as during the current outbreak (4-7). PCR assays (NVO and other Orthopoxvirus laboratory developed tests [LDT]) represent the primary tool for monkeypox diagnosis. These tests are highly sensitive, and cross-contamination from other MPXV specimens being processed, tested, or both alongside negative specimens can occasionally lead to false-positive results. This report describes three patients who had atypical rashes and no epidemiologic link to a monkeypox case or known risk factors; these persons received diagnoses of monkeypox based on late cycle threshold (Ct) values ≥34, which were false-positive test results. The initial diagnoses were followed by administration of antiviral treatment (i.e., tecovirimat) and JYNNEOS vaccine postexposure prophylaxis (PEP) to patients' close contacts. After receiving subsequent testing, none of the three patients was confirmed to have monkeypox. Knowledge gained from these and other cases resulted in changes to CDC guidance. When testing for monkeypox in specimens from patients without an epidemiologic link or risk factors or who do not meet clinical criteria (or where these are unknown), laboratory scientists should reextract and retest specimens with late Ct values (based on this report, Ct ≥34 is recommended) (8). CDC can be consulted for complex cases including those that appear atypical or questionable cases and can perform additional viral species- and clade-specific PCR testing and antiorthopoxvirus serologic testing.

Performance of Xpert MTB/RIF and Mycobacterial Culture on Multiple Specimen Types for Diagnosis of Tuberculosis Disease in Young Children and Clinical Characterization According to Standardized Research Case Definitions.

BACKGROUND: Tuberculosis (TB) is a leading cause of illness and death in children globally. Improved bacteriologic and clinical diagnostic approaches in children are urgently needed. METHODS: In a prospective cohort study, a consecutive series of young (<5 years) children presenting with symptoms suggestive of TB and parenchymal abnormality on chest radiograph in inpatient and outpatient settings in Kisumu County, Kenya from October 2013 to August 2015 were evaluated at baseline and over 6 months. Up to 14 specimens per child were tested for the Mycobacterium tuberculosis complex by fluorescence microscopy, Xpert MTB/RIF and mycobacterial culture. Using detailed clinical characterization, cases were retrospectively classified according to standardized research case definitions and the sensitivity and specificity of microbiological tests on different specimen types were determined. RESULTS: Among 300 young children enrolled, 266 had sufficient information to be classified according to the research clinical case definition. Of these, 36% (96/266) had TB disease; 32% (31/96) with bacteriologically confirmed intrathoracic TB. Compared to culture, the sensitivity of a single Xpert test ranged from 60 to 67% and specificity from 97.5 to 100% for different specimen types. CONCLUSIONS: Despite extensive specimen collection and laboratory testing, TB could not be bacteriologically confirmed in almost two-thirds of children with intrathoracic TB classified by research clinical case definitions. Improved diagnostic tests are needed to identify children with TB and to exclude other potential causes of illness.

Factors Associated With Severe Illness in Patients Aged <21 Years Hospitalized for COVID-19.

OBJECTIVES: To describe coronavirus disease 2019 (COVID-19)-related pediatric hospitalizations during a period of B.1.617.2 (Δ) variant predominance and to determine age-specific factors associated with severe illness. METHODS: We abstracted data from medical charts to conduct a cross-sectional study of patients aged <21 years hospitalized at 6 United States children's hospitals from July to August 2021 for COVID-19 or with an incidental positive severe acute respiratory syndrome coronavirus 2 test. Among patients with COVID-19, we assessed factors associated with severe illness by calculating age-stratified prevalence ratios (PR). We defined severe illness as receiving high-flow nasal cannula, positive airway pressure, or invasive mechanical ventilation. RESULTS: Of 947 hospitalized patients, 759 (80.1%) had COVID-19, of whom 287 (37.8%) had severe illness. Factors associated with severe illness included coinfection with respiratory syncytial virus (RSV) (PR 3.64) and bacteria (PR 1.88) in infants; RSV coinfection in patients aged 1 to 4 years (PR 1.96); and obesity in patients aged 5 to 11 (PR 2.20) and 12 to 17 years (PR 2.48). Having ≥2 underlying medical conditions was associated with severe illness in patients aged <1 (PR 1.82), 5 to 11 (PR 3.72), and 12 to 17 years (PR 3.19). CONCLUSIONS: Among patients hospitalized for COVID-19, factors associated with severe illness included RSV coinfection in those aged <5 years, obesity in those aged 5 to 17 years, and other underlying conditions for all age groups <18 years. These findings can inform pediatric practice, risk communication, and prevention strategies, including vaccination against COVID-19.

Nearest-Neighbors Matching for Case-Control Study Analyses: Better Risk Factor Identification From a Study of Sporadic Campylobacteriosis in the United States.

BACKGROUND: Case-control studies are commonly used to explore factors associated with enteric bacterial diseases. Control of confounding is challenging due to a large number of exposures of interest and the low frequencies of many of them. METHODS: We evaluated nearest-neighbors matching in a case-control study (originally 1:1 matched, published in 2004) of sporadic Campylobacter infections that included information on 433 exposures in 2632 subjects during 1998-1999. We performed multiple imputations of missing data (m = 100) and calculated Gower distances between cases and controls using all possible confounders for each exposure in each dataset. We matched each case with ≤20 controls within a data-determined distance. We calculated odds ratios and population attributable fractions (PAFs). RESULTS: Examination of pairwise correlation between exposures found very strong associations for 1046 pairs of exposures. More than 100 exposures were associated with campylobacteriosis, including nearly all risk factors identified using the previously published approach that included only 16 exposures and some less studied, rare exposures such as consumption of chicken liver and raw clams. Consumption of chicken and nonpoultry meat had the highest PAFs (62% and 59%, respectively). CONCLUSIONS: Nearest-neighbors matching appear to provide an improved ability to examine rare exposures and better control for numerous highly associated confounders.

Characterizing tuberculosis transmission dynamics in high-burden urban and rural settings.

Mycobacterium tuberculosis transmission dynamics in high-burden settings are poorly understood. Growing evidence suggests transmission may be characterized by extensive individual heterogeneity in secondary cases (i.e., superspreading), yet the degree and influence of such heterogeneity is largely unknown and unmeasured in high burden-settings. We conducted a prospective, population-based molecular epidemiology study of TB transmission in both an urban and rural setting of Botswana, one of the highest TB burden countries in the world. We used these empirical data to fit two mathematical models (urban and rural) that jointly quantified both the effective reproductive number, [Formula: see text], and the propensity for superspreading in each population. We found both urban and rural populations were characterized by a high degree of individual heterogeneity, however such heterogeneity disproportionately impacted the rural population: 99% of secondary transmission was attributed to only 19% of infectious cases in the rural population compared to 60% in the urban population and the median number of incident cases until the first outbreak of 30 cases was only 32 for the rural model compared to 791 in the urban model. These findings suggest individual heterogeneity plays a critical role shaping local TB epidemiology within subpopulations.

Tuberculosis attributed to transmission within healthcare facilities, Botswana-The Kopanyo Study.

OBJECTIVE: Healthcare facilities are a well-known high-risk environment for transmission of M. tuberculosis, the etiologic agent of tuberculosis (TB) disease. However, the link between M. tuberculosis transmission in healthcare facilities and its role in the general TB epidemic is unknown. We estimated the proportion of overall TB transmission in the general population attributable to healthcare facilities. METHODS: We combined data from a prospective, population-based molecular epidemiologic study with a universal electronic medical record (EMR) covering all healthcare facilities in Botswana to identify biologically plausible transmission events occurring at the healthcare facility. Patients with M. tuberculosis isolates of the same genotype visiting the same facility concurrently were considered an overlapping event. We then used TB diagnosis and treatment data to categorize overlapping events into biologically plausible definitions. We calculated the proportion of overall TB cases in the cohort that could be attributable to healthcare facilities. RESULTS: In total, 1,881 participants had TB genotypic and EMR data suitable for analysis, resulting in 46,853 clinical encounters at 338 healthcare facilities. We identified 326 unique overlapping events involving 370 individual patients; 91 (5%) had biologic plausibility for transmission occurring at a healthcare facility. A sensitivity analysis estimated that 3%-8% of transmission may be attributable to healthcare facilities. CONCLUSIONS: Although effective interventions are critical in reducing individual risk for healthcare workers and patients at healthcare facilities, our findings suggest that development of targeted interventions aimed at community transmission may have a larger impact in reducing TB.

Pulmonary and Critical Care Considerations for e-Cigarette, or Vaping, Product Use-Associated Lung Injury.

BACKGROUND: In 2019, the United States experienced a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). More than one-half of these patients required admission to an ICU. RESEARCH QUESTION: What are the recent literature and expert opinions which inform the diagnosis and management of patients with critical illness with EVALI? STUDY DESIGN AND METHODS: To synthesize information critical to pulmonary/critical care specialists in the care of patients with EVALI, this study examined data available from patients hospitalized with EVALI between August 2019 and January 2020; reviewed the clinical course and critical care experience with those patients admitted to the ICU; and compiled opinion of national experts. RESULTS: Of the 2,708 patients with confirmed or probable EVALI requiring hospitalization as of January 21, 2020, a total of 1,604 (59.2%) had data available on ICU admission; of these, 705 (44.0%) were admitted to the ICU and are included in this analysis. The majority of ICU patients required respiratory support (88.5%) and in severe cases required intubation (36.1%) or extracorporeal membrane oxygenation (6.7%). The majority (93.0%) of these ICU patients survived to discharge. Review of the clinical course and expert opinion provided insight into: imaging; considerations for bronchoscopy; medical treatment, including use of empiric antibiotics, antiviral agents, and corticosteroids; respiratory support, including considerations for intubation, positioning maneuvers, and extracorporeal membrane oxygenation; and patient outcomes. INTERPRETATION: Review of the clinical course of patients with EVALI requiring ICU admission and compilation of expert opinion provided critical insight into pulmonary/critical care-specific considerations for this patient population. Because a large proportion of patients hospitalized with EVALI required ICU admission, it is important to remain prepared to care for patients with EVALI.

Characteristics and Clinical Outcomes of Children and Adolescents Aged <18 Years Hospitalized with COVID-19 - Six Hospitals, United States, July-August 2021.

During June 2021, the highly transmissible† B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19, became the predominant circulating strain in the United States. U.S. pediatric COVID-19-related hospitalizations increased during July-August 2021 following emergence of the Delta variant and peaked in September 2021.§ As of May 12, 2021, CDC recommended COVID-19 vaccinations for persons aged ≥12 years,¶ and on November 2, 2021, COVID-19 vaccinations were recommended for persons aged 5-11 years.** To date, clinical signs and symptoms, illness course, and factors contributing to hospitalizations during the period of Delta predominance have not been well described in pediatric patients. CDC partnered with six children's hospitals to review medical record data for patients aged <18 years with COVID-19-related hospitalizations during July-August 2021.†† Among 915 patients identified, 713 (77.9%) were hospitalized for COVID-19 (acute COVID-19 as the primary or contributing reason for hospitalization), 177 (19.3%) had incidental positive SARS-CoV-2 test results (asymptomatic or mild infection unrelated to the reason for hospitalization), and 25 (2.7%) had multisystem inflammatory syndrome in children (MIS-C), a rare but serious inflammatory condition associated with COVID-19.§§ Among the 713 patients hospitalized for COVID-19, 24.7% were aged <1 year, 17.1% were aged 1-4 years, 20.1% were aged 5-11 years, and 38.1% were aged 12-17 years. Approximately two thirds of patients (67.5%) had one or more underlying medical conditions, with obesity being the most common (32.4%); among patients aged 12-17 years, 61.4% had obesity. Among patients hospitalized for COVID-19, 15.8% had a viral coinfection¶¶ (66.4% of whom had respiratory syncytial virus [RSV] infection). Approximately one third (33.9%) of patients aged <5 years hospitalized for COVID-19 had a viral coinfection. Among 272 vaccine-eligible (aged 12-17 years) patients hospitalized for COVID-19, one (0.4%) was fully vaccinated.*** Approximately one half (54.0%) of patients hospitalized for COVID-19 received oxygen support, 29.5% were admitted to the intensive care unit (ICU), and 1.5% died; of those requiring respiratory support, 14.5% required invasive mechanical ventilation (IMV). Among pediatric patients with COVID-19-related hospitalizations, many had severe illness and viral coinfections, and few vaccine-eligible patients hospitalized for COVID-19 were vaccinated, highlighting the importance of vaccination for those aged ≥5 years and other prevention strategies to protect children and adolescents from COVID-19, particularly those with underlying medical conditions.

Late Conditions Diagnosed 1-4 Months Following an Initial Coronavirus Disease 2019 (COVID-19) Encounter: A Matched-Cohort Study Using Inpatient and Outpatient Administrative Data-United States, 1 March-30 June 2020.

BACKGROUND: Late sequelae of COVID-19 have been reported; however, few studies have investigated the time course or incidence of late new COVID-19-related health conditions (post-COVID conditions) after COVID-19 diagnosis. Studies distinguishing post-COVID conditions from late conditions caused by other etiologies are lacking. Using data from a large administrative all-payer database, we assessed type, association, and timing of post-COVID conditions following COVID-19 diagnosis. METHODS: Using the Premier Healthcare Database Special COVID-19 Release (release date, 20 October 2020) data, during March-June 2020, 27 589 inpatients and 46 857 outpatients diagnosed with COVID-19 (case-patients) were 1:1 matched with patients without COVID-19 through the 4-month follow-up period (control-patients) by using propensity score matching. In this matched-cohort study, adjusted ORs were calculated to assess for late conditions that were more common in case-patients than control-patients. Incidence proportion was calculated for conditions that were more common in case-patients than control-patients during 31-120 days following a COVID-19 encounter. RESULTS: During 31-120 days after an initial COVID-19 inpatient hospitalization, 7.0% of adults experienced ≥1 of 5 post-COVID conditions. Among adult outpatients with COVID-19, 7.7% experienced ≥1 of 10 post-COVID conditions. During 31-60 days after an initial outpatient encounter, adults with COVID-19 were 2.8 times as likely to experience acute pulmonary embolism as outpatient control-patients and also more likely to experience a range of conditions affecting multiple body systems (eg, nonspecific chest pain, fatigue, headache, and respiratory, nervous, circulatory, and gastrointestinal symptoms) than outpatient control-patients. CONCLUSIONS: These findings add to the evidence of late health conditions possibly related to COVID-19 in adults following COVID-19 diagnosis and can inform healthcare practice and resource planning for follow-up COVID-19 care.

Sensitive and Feasible Specimen Collection and Testing Strategies for Diagnosing Tuberculosis in Young Children.

Importance: Criterion-standard specimens for tuberculosis diagnosis in young children, gastric aspirate (GA) and induced sputum, are invasive and rarely collected in resource-limited settings. A far less invasive approach to tuberculosis diagnostic testing in children younger than 5 years as sensitive as current reference standards is important to identify. Objective: To characterize the sensitivity of preferably minimally invasive specimen and assay combinations relative to maximum observed yield from all specimens and assays combined. Design, Setting, and Participants: In this prospective cross-sectional diagnostic study, the reference standard was a panel of up to 2 samples of each of 6 specimen types tested for Mycobacterium tuberculosis complex by Xpert MTB/RIF assay and mycobacteria growth indicator tube culture. Multiple different combinations of specimens and tests were evaluated as index tests. A consecutive series of children was recruited from inpatient and outpatient settings in Kisumu County, Kenya, between October 2013 and August 2015. Participants were children younger than 5 years who had symptoms of tuberculosis (unexplained cough, fever, malnutrition) and parenchymal abnormality on chest radiography or who had cervical lymphadenopathy. Children with 1 or more evaluable specimen for 4 or more primary study specimen types were included in the analysis. Data were analyzed from February 2015 to October 2020. Main Outcomes and Measures: Cumulative and incremental diagnostic yield of combinations of specimen types and tests relative to the maximum observed yield. Results: Of the 300 enrolled children, the median (interquartile range) age was 2.0 (1.0-3.6) years, and 151 (50.3%) were female. A total of 294 met criteria for analysis. Of 31 participants with confirmed tuberculosis (maximum observed yield), 24 (sensitivity, 77%; interdecile range, 68%-87%) had positive results on up to 2 GA samples and 20 (sensitivity, 64%; interdecile range, 53%-76%) had positive test results on up to 2 induced sputum samples. The yields of 2 nasopharyngeal aspirate (NPA) samples (23 of 31 [sensitivity, 74%; interdecile range, 64%-84%]), of 1 NPA sample and 1 stool sample (22 of 31 [sensitivity, 71%; interdecile range, 60%-81%]), or of 1 NPA sample and 1 urine sample (21.5 of 31 [sensitivity, 69%; interdecile range, 58%-80%]) were similar to reference-standard specimens. Combining up to 2 each of GA and NPA samples had an average yield of 90% (28 of 31). Conclusions and Relevance: NPA, in duplicate or in combination with stool or urine specimens, was readily obtainable and had diagnostic yield comparable with reference-standard specimens. This combination could improve tuberculosis diagnosis among children in resource-limited settings. Combining GA and NPA had greater yield than that of the current reference standards and may be useful in certain clinical and research settings.

Characteristics of Hospitalized COVID-19 Patients Discharged and Experiencing Same-Hospital Readmission - United States, March-August 2020.

Coronavirus disease 2019 (COVID-19) is a complex clinical illness with potential complications that might require ongoing clinical care (1-3). Few studies have investigated discharge patterns and hospital readmissions among large groups of patients after an initial COVID-19 hospitalization (4-7). Using electronic health record and administrative data from the Premier Healthcare Database,* CDC assessed patterns of hospital discharge, readmission, and demographic and clinical characteristics associated with hospital readmission after a patient's initial COVID-19 hospitalization (index hospitalization). Among 126,137 unique patients with an index COVID-19 admission during March-July 2020, 15% died during the index hospitalization. Among the 106,543 (85%) surviving patients, 9% (9,504) were readmitted to the same hospital within 2 months of discharge through August 2020. More than a single readmission occurred among 1.6% of patients discharged after the index hospitalization. Readmissions occurred more often among patients discharged to a skilled nursing facility (SNF) (15%) or those needing home health care (12%) than among patients discharged to home or self-care (7%). The odds of hospital readmission increased with age among persons aged ≥65 years, presence of certain chronic conditions, hospitalization within the 3 months preceding the index hospitalization, and if discharge from the index hospitalization was to a SNF or to home with health care assistance. These results support recent analyses that found chronic conditions to be significantly associated with hospital readmission (6,7) and could be explained by the complications of underlying conditions in the presence of COVID-19 (8), COVID-19 sequelae (3), or indirect effects of the COVID-19 pandemic (9). Understanding the frequency of, and risk factors for, readmission can inform clinical practice, discharge disposition decisions, and public health priorities such as health care planning to ensure availability of resources needed for acute and follow-up care of COVID-19 patients. With the recent increases in cases nationwide, hospital planning can account for these increasing numbers along with the potential for at least 9% of patients to be readmitted, requiring additional beds and resources.