A Transcriptomic Classifier Model Identifies High-Risk Endotypes in a Prospective Study of Sepsis in Uganda.

OBJECTIVES: In high-income countries (HICs), sepsis endotypes defined by distinct pathobiological mechanisms, mortality risks, and responses to corticosteroid treatment have been identified using blood transcriptomics. The generalizability of these endotypes to low-income and middle-income countries (LMICs), where the global sepsis burden is concentrated, is unknown. We sought to determine the prevalence, prognostic relevance, and immunopathological features of HIC-derived transcriptomic sepsis endotypes in sub-Saharan Africa. DESIGN: Prospective cohort study. SETTING: Public referral hospital in Uganda. PATIENTS: Adults ( n = 128) hospitalized with suspected sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Using whole-blood RNA sequencing data, we applied 19-gene and 7-gene classifiers derived and validated in HICs (SepstratifieR) to assign patients to one of three sepsis response signatures (SRS). The 19-gene classifier assigned 30 (23.4%), 92 (71.9%), and 6 (4.7%) patients to SRS-1, SRS-2, and SRS-3, respectively, the latter of which is designed to capture individuals transcriptionally closest to health. SRS-1 was defined biologically by proinflammatory innate immune activation and suppressed natural killer-cell, T-cell, and B-cell immunity, whereas SRS-2 was characterized by dampened innate immune activation, preserved lymphocyte immunity, and suppressed transcriptional responses to corticosteroids. Patients assigned to SRS-1 were predominantly (80.0% [24/30]) persons living with HIV with advanced immunosuppression and frequent tuberculosis. Mortality at 30-days differed significantly by endotype and was highest (48.1%) in SRS-1. Agreement between 19-gene and 7-gene SRS assignments was poor (Cohen's kappa 0.11). Patient stratification was suboptimal using the 7-gene classifier with 15.1% (8/53) of individuals assigned to SRS-3 deceased at 30-days. CONCLUSIONS: Sepsis endotypes derived in HICs share biological and clinical features with those identified in sub-Saharan Africa, with major differences in host-pathogen profiles. Our findings highlight the importance of context-specific sepsis endotyping, the generalizability of conserved biological signatures of critical illness across disparate settings, and opportunities to develop more pathobiologically informed sepsis treatment strategies in LMICs.

Adherence Measured Using Electronic Dose Monitoring is Associated with Emergent Antiretroviral Resistance and Poor Outcomes in People with Human Immunodeficiency Virus/AIDS and Multidrug-Resistant Tuberculosis.

BACKGROUND: Medication adherence is known to challenge treatment of human immunodeficiency virus (HIV)/AIDS and multidrug-resistant tuberculosis (MDR-TB). We hypothesized that adherence using electronic dose monitoring (EDM) would identify an antiretroviral therapy (ART) adherence threshold for emergent ART resistance and predict treatment outcomes in patients with MDR-TB and HIV on ART and bedaquiline-containing TB regimens. METHODS: A prospective cohort of adults with MDR-TB and HIV on ART and initiating MDR-TB treatment with bedaquiline were enrolled at a public hospital in KwaZulu-Natal, South Africa (PRAXIS Study). Participants received separate EDM devices that measure adherence to bedaquiline and ART (nevirapine or lopinavir/ritonavir). Adherence was calculated cumulatively over 6 months. Participants were followed through completion of MDR-TB treatment. HIV genome sequencing was performed at baseline and 2 and 6 months on samples with HIV RNA ≥1000 copies/mL. RESULTS: From November 2016 through February 2018, 198 persons with MDR-TB and HIV were enrolled and followed (median, 17.2 months; interquartile range, 12.2-19.6). Eleven percent had baseline ART resistance mutations, and 7.5% developed emergent ART resistance at 6 months. ART adherence was independently associated with ART resistance and mortality. Modeling identified a significant (P < .001), linear association between ART adherence and emergent resistance, suggesting a strong association without a specific threshold. CONCLUSIONS: Our findings highlight the need for ART resistance testing, especially in patients with MDR-TB and HIV, which is currently not the standard of care in resource-limited settings. Despite short follow-up duration, reduced ART adherence was significantly associated with emergent resistance and increased mortality. CLINICAL TRIALS REGISTRATION: NCT03162107.

Multidimensional analysis of the host response reveals prognostic and pathogen-driven immune subtypes among adults with sepsis in Uganda.

BACKGROUND: The global burden of sepsis is concentrated in sub-Saharan Africa, where severe infections disproportionately affect young, HIV-infected adults and high-burden pathogens are unique. In this context, poor understanding of sepsis immunopathology represents a crucial barrier to development of locally-effective treatment strategies. We sought to determine inter-individual immunologic heterogeneity among adults hospitalized with sepsis in a sub-Saharan African setting, and characterize associations between immune subtypes, infecting pathogens, and clinical outcomes. METHODS: Among a prospective observational cohort of 288 adults hospitalized with suspected sepsis in Uganda, we applied machine learning methods to 14 soluble host immune mediators, reflective of key domains of sepsis immunopathology (innate and adaptive immune activation, endothelial dysfunction, fibrinolysis), to identify immune subtypes in randomly-split discovery (N = 201) and internal validation (N = 87) sub-cohorts. In parallel, we applied similar methods to whole-blood RNA-sequencing data from a consecutive subset of patients (N = 128) to identify transcriptional subtypes, which we characterized using biological pathway and immune cell-type deconvolution analyses. RESULTS: Unsupervised clustering consistently identified two immune subtypes defined by differential activation of pro-inflammatory innate and adaptive immune pathways, with transcriptional evidence of concomitant CD56(-)/CD16( +) NK-cell expansion, T-cell exhaustion, and oxidative-stress and hypoxia-induced metabolic and cell-cycle reprogramming in the hyperinflammatory subtype. Immune subtypes defined by greater pro-inflammatory immune activation, T-cell exhaustion, and metabolic reprogramming were consistently associated with a high-prevalence of severe and often disseminated HIV-associated tuberculosis, as well as more extensive organ dysfunction, worse functional outcomes, and higher 30-day mortality. CONCLUSIONS: Our results highlight unique host- and pathogen-driven features of sepsis immunopathology in sub-Saharan Africa, including the importance of severe HIV-associated tuberculosis, and reinforce the need to develop more biologically-informed treatment strategies in the region, particularly those incorporating immunomodulation.

Latent Class Analysis Reveals COVID-19-related Acute Respiratory Distress Syndrome Subgroups with Differential Responses to Corticosteroids.

Rationale: Two distinct subphenotypes have been identified in acute respiratory distress syndrome (ARDS), but the presence of subgroups in ARDS associated with coronavirus disease (COVID-19) is unknown. Objectives: To identify clinically relevant, novel subgroups in COVID-19-related ARDS and compare them with previously described ARDS subphenotypes. Methods: Eligible participants were adults with COVID-19 and ARDS at Columbia University Irving Medical Center. Latent class analysis was used to identify subgroups with baseline clinical, respiratory, and laboratory data serving as partitioning variables. A previously developed machine learning model was used to classify patients as the hypoinflammatory and hyperinflammatory subphenotypes. Baseline characteristics and clinical outcomes were compared between subgroups. Heterogeneity of treatment effect for corticosteroid use in subgroups was tested. Measurements and Main Results: From March 2, 2020, to April 30, 2020, 483 patients with COVID-19-related ARDS met study criteria. A two-class latent class analysis model best fit the population (P = 0.0075). Class 2 (23%) had higher proinflammatory markers, troponin, creatinine, and lactate, lower bicarbonate, and lower blood pressure than class 1 (77%). Ninety-day mortality was higher in class 2 versus class 1 (75% vs. 48%; P < 0.0001). Considerable overlap was observed between these subgroups and ARDS subphenotypes. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR cycle threshold was associated with mortality in the hypoinflammatory but not the hyperinflammatory phenotype. Heterogeneity of treatment effect to corticosteroids was observed (P = 0.0295), with improved mortality in the hyperinflammatory phenotype and worse mortality in the hypoinflammatory phenotype, with the caveat that corticosteroid treatment was not randomized. Conclusions: We identified two COVID-19-related ARDS subgroups with differential outcomes, similar to previously described ARDS subphenotypes. SARS-CoV-2 PCR cycle threshold had differential value for predicting mortality in the subphenotypes. The subphenotypes had differential treatment responses to corticosteroids.

Electronic Dose Monitoring Identifies a High-Risk Subpopulation in the Treatment of Drug-resistant Tuberculosis and Human Immunodeficiency Virus.

BACKGROUND: In generalized drug-resistant tuberculosis (DR-TB) human immunodeficiency virus (HIV) epidemics, identifying subpopulations at high risk for treatment failure and loss to care is critically important to improve treatment outcomes and prevent amplification of drug resistance. We hypothesized that an electronic dose-monitoring (EDM) device could empirically identify adherence-challenged patients and that a mixed-methods approach would characterize treatment challenges. METHODS: A prospective study of patients with DR-TB HIV on antiretroviral therapy (ART) initiating bedaquiline-containing regimens in KwaZulu-Natal, South Africa. Separate EDM devices measured adherence for bedaquiline and ART. Patients with low adherence (<85%) to both bedaquiline and ART were identified as high risk for poor outcomes. Baseline survey, study visit notes, and focus group discussions characterized treatment challenges. RESULTS: From December 2016-February 2018, 32 of 198 (16%) enrolled patients with DR-TB HIV were identified as dual-adherence challenged. In a multivariate model including baseline characteristics, only receiving a disability grant was significantly associated with dual nonadherence at 6 months. Mixed-methods identified treatment barriers including alcohol abuse, family conflicts, and mental health issues. Compared with adherent patients, dual-adherence-challenged patients struggled to prioritize treatment and lacked support, and dual-adherence-challenged patients experienced higher rates of detectable HIV viral load and mortality than more adherent patients. CONCLUSIONS: EDM empirically identified a subpopulation of patients with DR-TB HIV with dual-adherence challenges early in treatment. Mixed-methods revealed intense psychosocial, behavioral, and structural barriers to care in this subpopulation. Our data support developing differential, patient-centered, adherence support interventions focused on psychosocial and structural challenges for subpopulations of at-risk DR-TB HIV patients.

Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study.

BACKGROUND: Over 40 000 patients with COVID-19 have been hospitalised in New York City (NY, USA) as of April 28, 2020. Data on the epidemiology, clinical course, and outcomes of critically ill patients with COVID-19 in this setting are needed. METHODS: This prospective observational cohort study took place at two NewYork-Presbyterian hospitals affiliated with Columbia University Irving Medical Center in northern Manhattan. We prospectively identified adult patients (aged ≥18 years) admitted to both hospitals from March 2 to April 1, 2020, who were diagnosed with laboratory-confirmed COVID-19 and were critically ill with acute hypoxaemic respiratory failure, and collected clinical, biomarker, and treatment data. The primary outcome was the rate of in-hospital death. Secondary outcomes included frequency and duration of invasive mechanical ventilation, frequency of vasopressor use and renal replacement therapy, and time to in-hospital clinical deterioration following admission. The relation between clinical risk factors, biomarkers, and in-hospital mortality was modelled using Cox proportional hazards regression. Follow-up time was right-censored on April 28, 2020 so that each patient had at least 28 days of observation. FINDINGS: Between March 2 and April 1, 2020, 1150 adults were admitted to both hospitals with laboratory-confirmed COVID-19, of which 257 (22%) were critically ill. The median age of patients was 62 years (IQR 51-72), 171 (67%) were men. 212 (82%) patients had at least one chronic illness, the most common of which were hypertension (162 [63%]) and diabetes (92 [36%]). 119 (46%) patients had obesity. As of April 28, 2020, 101 (39%) patients had died and 94 (37%) remained hospitalised. 203 (79%) patients received invasive mechanical ventilation for a median of 18 days (IQR 9-28), 170 (66%) of 257 patients received vasopressors and 79 (31%) received renal replacement therapy. The median time to in-hospital deterioration was 3 days (IQR 1-6). In the multivariable Cox model, older age (adjusted hazard ratio [aHR] 1·31 [1·09-1·57] per 10-year increase), chronic cardiac disease (aHR 1·76 [1·08-2·86]), chronic pulmonary disease (aHR 2·94 [1·48-5·84]), higher concentrations of interleukin-6 (aHR 1·11 [95%CI 1·02-1·20] per decile increase), and higher concentrations of D-dimer (aHR 1·10 [1·01-1·19] per decile increase) were independently associated with in-hospital mortality. INTERPRETATION: Critical illness among patients hospitalised with COVID-19 in New York City is common and associated with a high frequency of invasive mechanical ventilation, extrapulmonary organ dysfunction, and substantial in-hospital mortality. FUNDING: National Institute of Allergy and Infectious Diseases and the National Center for Advancing Translational Sciences, National Institutes of Health, and the Columbia University Irving Institute for Clinical and Translational Research.

Frailty subtypes and recovery in older survivors of acute respiratory failure: a pilot study.

BACKGROUND: Identifying subtypes of acute respiratory failure survivors may facilitate patient selection for post-intensive care unit (ICU) follow-up clinics and trials. METHODS: We conducted a single-centre prospective cohort study of 185 acute respiratory failure survivors, aged ≥ 65 years. We applied latent class modelling to identify frailty subtypes using frailty phenotype and cognitive impairment measurements made during the week before hospital discharge. We used Fine-Gray competing risks survival regression to test associations between frailty subtypes and recovery, defined as returning to a basic Activities of Daily Living disability count less than or equal to the pre-hospitalisation count within 6 months. We characterised subtypes by pre-ICU frailty (Clinical Frailty Scale score ≥ 5), the post-ICU frailty phenotype, and serum inflammatory cytokines, hormones and exosome proteomics during the week before hospital discharge. RESULTS: We identified five frailty subtypes. The recovery rate decreased 49% across each subtype independent of age, sex, pre-existing disability, comorbidity and Acute Physiology and Chronic Health Evaluation II score (recovery rate ratio: 0.51, 95% CI 0.41 to 0.63). Post-ICU frailty phenotype prevalence increased across subtypes, but pre-ICU frailty prevalence did not. In the subtype with the slowest recovery, all had cognitive impairment. The three subtypes with the slowest recovery had higher interleukin-6 levels (p=0.03) and a higher prevalence of ≥ 2 deficiencies in insulin growth factor-1, dehydroepiandrostersone-sulfate, or free-testosterone (p=0.02). Exosome proteomics revealed impaired innate immunity in subtypes with slower recovery. CONCLUSIONS: Frailty subtypes varied by prehospitalisation frailty and cognitive impairment at hospital discharge. Subtypes with the slowest recovery were similarly characterised by greater systemic inflammation and more anabolic hormone deficiencies at hospital discharge.

Spatiotemporal Clustering of Multidrug-Resistant and Extensively Drug-Resistant Tuberculosis Is Associated With Human Immunodeficiency Virus Status and Drug-Susceptibility Patterns in KwaZulu-Natal, South Africa.

Using an open-access spatiotemporal analytics program, we mapped spatiotemporal heterogeneity loci in tuberculosis (TB) cases (clusters) and dynamic changes, and characterized the drug-resistant TB clustering risk using routine microbiological data from KwaZulu-Natal, South Africa. The data may provide insight into transmission dynamics and support efficient deployment of public health resources.

Precision Surveillance for Viral Respiratory Pathogens: Virome Capture Sequencing for the Detection and Genomic Characterization of Severe Acute Respiratory Infection in Uganda.

BACKGROUND: Precision public health is a novel set of methods to target disease prevention and mitigation interventions to high-risk subpopulations. We applied a precision public health strategy to syndromic surveillance for severe acute respiratory infection (SARI) in Uganda by combining spatiotemporal analytics with genomic sequencing to detect and characterize viral respiratory pathogens with epidemic potential. METHODS: Using a national surveillance network we identified patients with unexplained, influenza-negative SARI from 2010 to 2015. Spatiotemporal analyses were performed retrospectively to identify clusters of unexplained SARI. Within clusters, respiratory viruses were detected and characterized in naso- and oropharyngeal swab samples using a novel oligonucleotide probe capture (VirCapSeq-VERT) and high-throughput sequencing platform. Linkage to conventional epidemiologic strategies further characterized transmission dynamics of identified pathogens. RESULTS: Among 2901 unexplained SARI cases, 9 clusters were detected, accounting for 301 (10.4%) cases. Clusters were more likely to occur in urban areas and during biannual rainy seasons. Within detected clusters, we identified an unrecognized outbreak of measles-associated SARI; sequence analysis implicated cocirculation of endemic genotype B3 and genotype D4 likely imported from England. We also detected a likely nosocomial SARI cluster associated with a novel picobirnavirus most closely related to swine and dromedary viruses. CONCLUSIONS: Using a precision approach to public health surveillance, we detected and characterized the genomics of vaccine-preventable and zoonotic respiratory viruses associated with clusters of severe respiratory infections in Uganda. Future studies are needed to assess the feasibility, scalability, and impact of applying similar approaches during real-time public health surveillance in low-income settings.

Early Detection of Emergent Extensively Drug-Resistant Tuberculosis by Flow Cytometry-Based Phenotyping and Whole-Genome Sequencing.

A critical gap in tuberculosis (TB) treatment is detection of emergent drug resistance. We hypothesized that advanced phenotyping with whole-genome sequencing (WGS) will detect low-frequency Mycobacterium tuberculosis drug resistance. We assessed a reporter mycobacteriophage (Φ2GFP10) in vitro to detect drug-resistant subpopulations and predict M. tuberculosis bactericidal activity in this pilot study. Subsequently, we prospectively studied 20 TB patients with serial Φ2GFP10, Xpert MTB/RIF, and M. tuberculosis culture through end of treatment. WGS was performed, and single nucleotide polymorphisms (SNPs) were examined to detect mixed infection in selected M. tuberculosis isolates. Resistant M. tuberculosis isolates were detected at 1:100,000, and changes in cytometry-gated events were predictive of in vitroM. tuberculosis bactericidal activity using the Φ2GFP10 assay. Emergent drug resistance was detected in one patient by Φ2GFP10 at 3 weeks but not by conventional testing (M. tuberculosis culture and GeneXpert). WGS revealed a phylogeographically distinct extensively drug-resistant tuberculosis (XDR-TB) genome, identical to an XDR-TB isolate from the patient's spouse. Variant lineage-specific SNPs were present early, suggesting mixed infection as the etiology of emergent resistance with temporal trends providing evidence for selection during treatment. Φ2GFP10 can detect low-frequency drug-resistant M. tuberculosis and with WGS characterize emergent M. tuberculosis resistance. In areas of high TB transmission and drug resistance, rapid screening for heteroresistance should be considered.

Evolution of Extensively Drug-Resistant Tuberculosis over Four Decades: Whole Genome Sequencing and Dating Analysis of Mycobacterium tuberculosis Isolates from KwaZulu-Natal.

BACKGROUND: The continued advance of antibiotic resistance threatens the treatment and control of many infectious diseases. This is exemplified by the largest global outbreak of extensively drug-resistant (XDR) tuberculosis (TB) identified in Tugela Ferry, KwaZulu-Natal, South Africa, in 2005 that continues today. It is unclear whether the emergence of XDR-TB in KwaZulu-Natal was due to recent inadequacies in TB control in conjunction with HIV or other factors. Understanding the origins of drug resistance in this fatal outbreak of XDR will inform the control and prevention of drug-resistant TB in other settings. In this study, we used whole genome sequencing and dating analysis to determine if XDR-TB had emerged recently or had ancient antecedents. METHODS AND FINDINGS: We performed whole genome sequencing and drug susceptibility testing on 337 clinical isolates of Mycobacterium tuberculosis collected in KwaZulu-Natal from 2008 to 2013, in addition to three historical isolates, collected from patients in the same province and including an isolate from the 2005 Tugela Ferry XDR outbreak, a multidrug-resistant (MDR) isolate from 1994, and a pansusceptible isolate from 1995. We utilized an array of whole genome comparative techniques to assess the relatedness among strains, to establish the order of acquisition of drug resistance mutations, including the timing of acquisitions leading to XDR-TB in the LAM4 spoligotype, and to calculate the number of independent evolutionary emergences of MDR and XDR. Our sequencing and analysis revealed a 50-member clone of XDR M. tuberculosis that was highly related to the Tugela Ferry XDR outbreak strain. We estimated that mutations conferring isoniazid and streptomycin resistance in this clone were acquired 50 y prior to the Tugela Ferry outbreak (katG S315T [isoniazid]; gidB 130 bp deletion [streptomycin]; 1957 [95% highest posterior density (HPD): 1937-1971]), with the subsequent emergence of MDR and XDR occurring 20 y (rpoB L452P [rifampicin]; pncA 1 bp insertion [pyrazinamide]; 1984 [95% HPD: 1974-1992]) and 10 y (rpoB D435G [rifampicin]; rrs 1400 [kanamycin]; gyrA A90V [ofloxacin]; 1995 [95% HPD: 1988-1999]) prior to the outbreak, respectively. We observed frequent de novo evolution of MDR and XDR, with 56 and nine independent evolutionary events, respectively. Isoniazid resistance evolved before rifampicin resistance 46 times, whereas rifampicin resistance evolved prior to isoniazid only twice. We identified additional putative compensatory mutations to rifampicin in this dataset. One major limitation of this study is that the conclusions with respect to ordering and timing of acquisition of mutations may not represent universal patterns of drug resistance emergence in other areas of the globe. CONCLUSIONS: In the first whole genome-based analysis of the emergence of drug resistance among clinical isolates of M. tuberculosis, we show that the ancestral precursor of the LAM4 XDR outbreak strain in Tugela Ferry gained mutations to first-line drugs at the beginning of the antibiotic era. Subsequent accumulation of stepwise resistance mutations, occurring over decades and prior to the explosion of HIV in this region, yielded MDR and XDR, permitting the emergence of compensatory mutations. Our results suggest that drug-resistant strains circulating today reflect not only vulnerabilities of current TB control efforts but also those that date back 50 y. In drug-resistant TB, isoniazid resistance was overwhelmingly the initial resistance mutation to be acquired, which would not be detected by current rapid molecular diagnostics employed in South Africa that assess only rifampicin resistance.

A Novel Reporter Phage To Detect Tuberculosis and Rifampin Resistance in a High-HIV-Burden Population.

Improved diagnostics and drug susceptibility testing for Mycobacterium tuberculosis are urgently needed. We developed a more powerful mycobacteriophage (Φ(2)GFP10) with a fluorescent reporter. Fluorescence-activated cell sorting (FACS) allows for rapid enumeration of metabolically active bacilli after phage infection. We compared the reporter phage assay to GeneXpert MTB/RIF for detection of M. tuberculosis and rifampin (RIF) resistance in sputum. Patients suspected to have tuberculosis were prospectively enrolled in Durban, South Africa. Sputum was incubated with Φ(2)GFP10, in the presence and absence of RIF, and bacilli were enumerated using FACS. Sensitivity and specificity were compared to those of GeneXpert MTB/RIF with an M. tuberculosis culture as the reference standard. A total of 158 patients were prospectively enrolled. Overall sensitivity for M. tuberculosis was 95.90% (95% confidence interval (CI), 90.69% to 98.64%), and specificity was 83.33% (95% CI, 67.18% to 93.59%). In acid-fast bacillus (AFB)-negative sputum, sensitivity was 88.89% (95% CI, 73.92% to 96.82%), and specificity was 83.33% (95% CI, 67.18% to 93.59%). Sensitivity for RIF-resistant M. tuberculosis in AFB-negative sputum was 90.00% (95% CI, 55.46% to 98.34%), and specificity was 91.94% (95% CI, 82.16% to 97.30%). Compared to GeneXpert, the reporter phage was more sensitive in AFB smear-negative sputum, but specificity was lower. The Φ(2)GFP10 reporter phage showed high sensitivity for detection of M. tuberculosis and RIF resistance, including in AFB-negative sputum, and has the potential to improve phenotypic testing for complex drug resistance, paucibacillary sputum, response to treatment, and detection of mixed infection in clinical specimens.

Racial and ethnic disparities post-hospitalization for COVID-19: barriers to access to care for survivors of COVID-19 acute respiratory distress syndrome.

Racial and ethnic health disparities in the incidence and severity of Coronavirus Disease 2019 (COVID-19) have been observed globally and in the United States. Research has focused on transmission, hospitalization, and mortality among racial and ethnic minorities, but Long COVID-19 health disparities research is limited. This study retrospectively evaluated 195 adults who survived COVID-19 associated acute respiratory distress syndrome (C-ARDS) in New York City from March-April 2020. Among survivors, 54% met the criteria for Long COVID syndrome. Hispanic/Latinx patients, were more likely to be uninsured (p = 0.027) and were less frequently discharged to rehabilitation facilities (p < 0.001). A cross-sectional telephone survey and interview were conducted with a subset of survivors (n = 69). Among these, 11% reported a lack of follow-up primary care post-discharge and 38% had subsequent emergency room visits. Notably, 38% reported poor treatment within the health care system, with 67% attributing this to racial or ethnic bias. Thematic analysis of interviews identified four perceived challenges: decline in functional status, discrimination during hospitalization, healthcare system inequities, and non-healthcare-related structural barriers. Sources of resilience included survivorship, faith, and family support. This study highlights structural and healthcare-related barriers rooted in perceived racism and poverty as factors impacting post-COVID-19 care.

COVID-19 immune signatures in Uganda persist in HIV co-infection and diverge by pandemic phase.

Little is known about the pathobiology of SARS-CoV-2 infection in sub-Saharan Africa, where severe COVID-19 fatality rates are among the highest in the world and the immunological landscape is unique. In a prospective cohort study of 306 adults encompassing the entire clinical spectrum of SARS-CoV-2 infection in Uganda, we profile the peripheral blood proteome and transcriptome to characterize the immunopathology of COVID-19 across multiple phases of the pandemic. Beyond the prognostic importance of myeloid cell-driven immune activation and lymphopenia, we show that multifaceted impairment of host protein synthesis and redox imbalance define core biological signatures of severe COVID-19, with central roles for IL-7, IL-15, and lymphotoxin-α in COVID-19 respiratory failure. While prognostic signatures are generally consistent in SARS-CoV-2/HIV-coinfection, type I interferon responses uniquely scale with COVID-19 severity in persons living with HIV. Throughout the pandemic, COVID-19 severity peaked during phases dominated by A.23/A.23.1 and Delta B.1.617.2/AY variants. Independent of clinical severity, Delta phase COVID-19 is distinguished by exaggerated pro-inflammatory myeloid cell and inflammasome activation, NK and CD8+ T cell depletion, and impaired host protein synthesis. Combining these analyses with a contemporary Ugandan cohort of adults hospitalized with influenza and other severe acute respiratory infections, we show that activation of epidermal and platelet-derived growth factor pathways are distinct features of COVID-19, deepening translational understanding of mechanisms potentially underlying SARS-CoV-2-associated pulmonary fibrosis. Collectively, our findings provide biological rationale for use of broad and targeted immunotherapies for severe COVID-19 in sub-Saharan Africa, illustrate the relevance of local viral and host factors to SARS-CoV-2 immunopathology, and highlight underemphasized yet therapeutically exploitable immune pathways driving COVID-19 severity.

Treatment outcomes for extensively drug-resistant tuberculosis and HIV co-infection.

High mortality rates have been reported for patients co-infected with extensively drug-resistant tuberculosis (XDR-TB) and HIV, but treatment outcomes have not been reported. We report treatment outcomes for adult XDR TB patients in KwaZulu-Natal Province, South Africa. Initial data were obtained retrospectively, and outcomes were obtained prospectively during 24 months of treatment. A total of 114 XDR TB patients were treated (median 6 drugs, range 3-9 drugs); 82 (73%) were HIV positive and 50 (61%) were receiving antiretroviral therapy. After receiving treatment for 24 months, 48 (42%) of 114 patients died, 25 (22%) were cured or successfully completed treatment, 19 (17%) withdrew from the study, and 22 (19%) showed treatment failure. A higher number of deaths occurred among HIV-positive patients not receiving antiretroviral therapy and among patients who did not show sputum culture conversion. Culture conversion was a major predictor of survival but was poorly predictive (51%) of successful treatment outcome.

Approach to the Physiologically Challenging Endotracheal Intubation in the Intensive Care Unit.

Endotracheal intubation for airway management is a common procedure in the ICU. Intubation may be difficult due to anatomic airway abnormalities but also due to physiologic derangements that predispose patients to cardiovascular collapse during the procedure. Results of studies demonstrate a high incidence of morbidity and mortality associated with airway management in the ICU. To reduce the likelihood of complications, medical teams must be well versed in the general principles of intubation and be prepared to manage physiologic derangements while securing the airway. In this review, we present relevant literature on the approach to endotracheal intubation in the ICU and provide pragmatic recommendations relevant to medical teams performing intubations in patients who are physiologically unstable.

Development of a Novel Clinicomolecular Risk Index to Enhance Mortality Prediction and Immunological Stratification of Adults Hospitalized with Sepsis in Sub-Saharan Africa: A Pilot Study from Uganda.

The global burden of sepsis is concentrated in sub-Saharan Africa (SSA), where epidemic HIV and unique pathogen diversity challenge the effective management of severe infections. In this context, patient stratification based on biomarkers of a dysregulated host response may identify subgroups more likely to respond to targeted immunomodulatory therapeutics. In a prospective cohort of adults hospitalized with suspected sepsis in Uganda, we applied machine learning methods to develop a prediction model for 30-day mortality that integrates physiology-based risk scores with soluble biomarkers reflective of key domains of sepsis immunopathology. After model evaluation and internal validation, whole-blood RNA sequencing data were analyzed to compare biological pathway enrichment and inferred immune cell profiles between patients assigned differential model-based risks of mortality. Of 260 eligible adults (median age, 32 years; interquartile range, 26-43 years; 59.2% female, 53.9% living with HIV), 62 (23.8%) died by 30 days after hospital discharge. Among 14 biomarkers, soluble tumor necrosis factor receptor 1 (sTNFR1) and angiopoietin 2 (Ang-2) demonstrated the greatest importance for mortality prediction in machine learning models. A clinicomolecular model integrating sTNFR1 and Ang-2 with the Universal Vital Assessment (UVA) risk score optimized 30-day mortality prediction across multiple performance metrics. Patients assigned to the high-risk, UVA-based clinicomolecular subgroup exhibited a transcriptional profile defined by proinflammatory innate immune and necroptotic pathway activation, T-cell exhaustion, and expansion of key immune cell subsets including regulatory and gamma-delta T cells. Clinicomolecular stratification of adults with suspected sepsis in Uganda enhanced 30-day mortality prediction and identified a high-risk subgroup with a therapeutically targetable immunological profile. Further studies are needed to advance pathobiologically informed sepsis management in SSA.