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BACKGROUND: Automated radiologic analysis using computer-aided detection software (CAD) could facilitate chest X-ray (CXR) use in tuberculosis diagnosis. There is little to no evidence on the accuracy of commercially available deep learning-based CAD in different populations, including patients with smear-negative tuberculosis and people living with human immunodeficiency virus (HIV, PLWH). METHODS: We collected CXRs and individual patient data (IPD) from studies evaluating CAD in patients self-referring for tuberculosis symptoms with culture or nucleic acid amplification testing as the reference. We reanalyzed CXRs with three CAD programs (CAD4TB version (v) 6, Lunit v3.1.0.0, and qXR v2). We estimated sensitivity and specificity within each study and pooled using IPD meta-analysis. We used multivariable meta-regression to identify characteristics modifying accuracy. RESULTS: We included CXRs and IPD of 3727/3967 participants from 4/7 eligible studies. 17% (621/3727) were PLWH. 17% (645/3727) had microbiologically confirmed tuberculosis. Despite using the same threshold score for classifying CXR in every study, sensitivity and specificity varied from study to study. The software had similar unadjusted accuracy (at 90% pooled sensitivity, pooled specificities were: CAD4TBv6, 56.9% [95% confidence interval {CI}: 51.7-61.9]; Lunit, 54.1% [95% CI: 44.6-63.3]; qXRv2, 60.5% [95% CI: 51.7-68.6]). Adjusted absolute differences in pooled sensitivity between PLWH and HIV-uninfected participants were: CAD4TBv6, -13.4% [-21.1, -6.9]; Lunit, +2.2% [-3.6, +6.3]; qXRv2: -13.4% [-21.5, -6.6]; between smear-negative and smear-positive tuberculosis was: were CAD4TBv6, -12.3% [-19.5, -6.1]; Lunit, -17.2% [-24.6, -10.5]; qXRv2, -16.6% [-24.4, -9.9]. Accuracy was similar to human readers. CONCLUSIONS: For CAD CXR analysis to be implemented as a high-sensitivity tuberculosis rule-out test, users will need threshold scores identified from their own patient populations and stratified by HIV and smear status.
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Aprendizaje Profundo , Infecciones por VIH , Tuberculosis Pulmonar , Tuberculosis , Infecciones por VIH/complicaciones , Humanos , Sensibilidad y Especificidad , Programas Informáticos , Triaje , Tuberculosis Pulmonar/diagnóstico por imagen , Tuberculosis Pulmonar/microbiología , Rayos XRESUMEN
BACKGROUND: The antimicrobial concentration required to kill all the bacteria in a biofilm, known as the minimum biofilm eradication concentration (MBEC), is typically determined in vitro by exposing the biofilm to serial concentrations of antimicrobials for 24 hours or less. Local delivery is expected to cause high local levels for longer than 24 hours. It is unknown if longer antimicrobial exposures require the same concentration to eradicate bacteria in biofilm. Questions/purposes Does MBEC change with increased antimicrobial exposure time? METHODS: Biofilms were grown for 24 hours using five pathogens (methicillin-sensitive Staphylococcus aureus, methicillin-resistant Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, and Pseudomonas aeruginosa) and then exposed to four antimicrobials regimens: tobramycin, vancomycin, and tobramycin combined with vancomycin in 3:1 and 1:1 ratios by weight in concentrations of 62.5, 125, 250, 500, 1000, 2000, 4000, and 8000 µg/mL for three durations, 1, 3, and 5 days, in triplicate. MBEC was measured as the lowest concentration that killed all bacteria in the biofilm determined by 21-day subculture. RESULTS: MBEC was lower when antimicrobial exposure time was longer. For the staphylococcus species, the MBEC was lower when exposure time was 5 days than 1 day in 11 of 12 antimicrobial/microorganism pairs. The MBEC range for these 11 pairs on Day 1 was 4000 to > 8000 µg/mL and on Day 5 was < 250 to 8000 µg/mL. MBEC for tobramycin/P. aeruginosa was 2000 µg/mL on Day 1 and ≤ 250 µg/mL on Day 5, and for E. coli, 125 µg/mL on Day 1 and ≤ 62.5 on Day 5. CONCLUSIONS: Although antimicrobial susceptibility was lower for longer exposure times in the microorganisms we studied, confirmation is required for other pathogens. Clinical Relevance One-day MBEC assays may overestimate the local antimicrobial levels needed to kill organisms in biofilm if local levels are sustained at MBEC or above for longer than 24 hours. Future studies are needed to confirm that antimicrobial levels achieved clinically from local delivery are above the MBEC at relevant time points and to confirm that MBEC for in vitro microorganisms accurately represents MBEC of in vivo organisms in an clinical infection.
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Antibacterianos/farmacología , Biopelículas/efectos de los fármacos , Escherichia coli/efectos de los fármacos , Pseudomonas aeruginosa/efectos de los fármacos , Staphylococcus/efectos de los fármacos , Tobramicina/farmacología , Vancomicina/farmacología , Biopelículas/crecimiento & desarrollo , Relación Dosis-Respuesta a Droga , Escherichia coli/crecimiento & desarrollo , Staphylococcus aureus Resistente a Meticilina/efectos de los fármacos , Staphylococcus aureus Resistente a Meticilina/crecimiento & desarrollo , Pruebas de Sensibilidad Microbiana , Viabilidad Microbiana/efectos de los fármacos , Pseudomonas aeruginosa/crecimiento & desarrollo , Staphylococcus/crecimiento & desarrollo , Staphylococcus epidermidis/efectos de los fármacos , Staphylococcus epidermidis/crecimiento & desarrollo , Factores de TiempoRESUMEN
BACKGROUND: Programmed cell death ligand-1 (PD-L1) expression on tumor cells, evaluated by immunohistochemistry, guides the use of immunotherapy in advanced non-small cell lung cancer (NSCLC). RESEARCH QUESTION: What is the sensitivity and specificity of PD-L1 testing performed in cytologic vs paired histologic specimens in patients with NSCLC? STUDY DESIGN AND METHODS: The MEDLINE, Embase, Web of Science, and Cochrane Library databases were searched through June 1, 2021. The primary outcome was pooled sensitivity and specificity of PD-L1 testing performed on cytologic specimens compared with the reference standard of histologic specimens, analyzed at the PD-L1 expression cutoffs (tumor proportion score) ≥ 1% and ≥ 50%. Pooled sensitivity and specificity, and associated 95% CIs, were estimated using bivariate generalized linear mixed models. RESULTS: Twenty-six articles were included, encompassing a total of 1,064 pairs of histology specimens and cytology cell blocks, and 267 pairs of histology specimens and direct smears. Among these, 946 paired specimens were acquired without interval treatment between the collection of histology and cytology samples. The pooled sensitivity and specificity of cytology specimens compared with paired histology specimens at the PD-L1 expression cutoff ≥ 1% were 0.84 (95% CI, 0.77-0.89) and 0.88 (95% CI, 0.82-0.93), respectively, whereas the pooled sensitivity and specificity at cutoff ≥ 50% were 0.78 (95% CI, 0.69-0.86) and 0.94 (95% CI, 0.91-0.96), respectively. When only paired specimens acquired without interval treatment were considered, the pooled sensitivity and specificity of cytology specimens at PD-L1 expression cutoff ≥ 1% were 0.84 (95% CI, 0.76-0.90) and 0.89 (95% CI, 0.82-0.94), respectively, whereas the pooled sensitivity and specificity at cutoff ≥ 50% were 0.80 (95% CI, 0.71-0.89) and 0.94 (95% CI, 0.91-0.96), respectively. INTERPRETATION: Cytologic specimens provide an accurate assessment of PD-L1 expression in most patients with NSCLC, at both ≥ 1% and ≥ 50% cutoffs, when compared with histologic specimens. TRIAL REGISTRATION: PROSPERO; No.: CRD42020153279; URL: https://www.crd.york.ac.uk/prospero/.
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Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Humanos , Carcinoma de Pulmón de Células no Pequeñas/patología , Neoplasias Pulmonares/patología , Antígeno B7-H1/metabolismo , Ligandos , Biomarcadores de Tumor/análisis , ApoptosisRESUMEN
BACKGROUND: Computer-aided detection (CAD) software packages quantify tuberculosis-compatible chest X-ray (CXR) abnormality as continuous scores. In practice, a threshold value is selected for binary CXR classification. We assessed the diagnostic accuracy of an alternative approach to applying CAD for tuberculosis triage: incorporating CAD scores in multivariable modelling. METHODS: We pooled individual patient data from four studies. Separately for two commercial CAD, we used logistic regression to model microbiologically-confirmed tuberculosis. Models included CAD score, study site, age, sex, HIV status, and prior tuberculosis. We compared specificity at target sensitivities ≥90% between the multivariable model and the current threshold-based approach for CAD use. RESULTS: We included 4733/5640 (84%) participants with complete covariate data (median age 36 years; 45% female; 22% with prior tuberculosis; 22% people living with HIV). A total of 805 (17%) had tuberculosis. Multivariable models demonstrated excellent performance (areas under the receiver operating characteristic curve (95%CI): software A, 0.91 (0.90-0.93); software B, 0.92 (0.91-0.93)). Compared to threshold scores, multivariable models increased specificity (e.g. at 90% sensitivity, threshold vs model specificity (95%CI): software A, 71% (68%-74%) vs. 75% (74%-77%); software B, 69% (63%-75%) vs. 75% (74%-77%)). CONCLUSIONS: Using CAD scores in multivariable models outperformed the current practice of CAD-threshold-based CXR classification for tuberculosis diagnosis.
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Objectives: We applied computer-aided detection (CAD) software for chest X-ray (CXR) analysis to determine if diabetes affects the radiographic presentation of tuberculosis. Methods: From March 2017-July 2018, we consecutively enrolled adults being evaluated for pulmonary tuberculosis in Karachi, Pakistan. Participants had same-day CXR, two sputum mycobacterial cultures, and random blood glucose measurement. We identified diabetes through self-report or glucose >11.1mMol/L. We included participants with culture-confirmed tuberculosis for this analysis. We used linear regression to estimate associations between CAD-reported tuberculosis abnormality score (range 0.00 to 1.00) and diabetes, adjusting for age, body mass index, sputum smear-status, and prior tuberculosis. We also compared radiographic abnormalities between participants with and without diabetes. Results: 63/272 (23%) of included participants had diabetes. After adjustment, diabetes was associated with higher CAD tuberculosis abnormality scores (p < 0.001). Diabetes was not associated with frequency of CAD-reported radiographic abnormalities apart from cavitary disease; participants with diabetes were more likely to have cavitary disease (74.6% vs 61.2% p = 0.07), particularly non-upper zone cavitary disease (17% vs 7.8%, p = 0.09). Conclusions: CAD analysis of CXR suggests diabetes is associated with more extensive radiographic abnormalities and with greater likelihood of cavities outside upper lung zones.
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BACKGROUND: Few evaluations of computer-aided detection (CAD) software for analyzing chest radiographs for tuberculosis have used mycobacterial culture as the reference standard. METHODS: Using data from a prospective study of symptomatic adults and household contacts of persons with tuberculosis who were seeking care in Karachi, we evaluated the accuracy of LUNIT INSIGHT version 3.1.0.0 (LUNIT, South Korea) for detecting pulmonary tuberculosis in the triage use case. The reference standard was liquid culture. We estimated the diagnostic accuracy using three developer-recommended threshold scores for tuberculosis: 15, 30, and 45. RESULTS: A total 269 of 2190 (12%) participants had culture-confirmed pulmonary tuberculosis. LUNIT-reported abnormalities of nodule, consolidation, fibrosis, and pleural effusion were more common with culture-confirmed tuberculosis. At the tuberculosis threshold score of 30, sensitivity and specificity were, respectively, 87.7% [95% CI: 83.2-91.4%] and 64.3% [62.1-66.4%]. Sensitivity was similar at scores of 15, 88.1% [95% CI: 83.6-91.7%] and 45, 86.6% [82.0 - 90.5%]; and specificity was 57.9% [55.7-60.2%] and 69.9% [67.8-71.9%], respectively. Sensitivity was lower for smear-negative disease, and specificity was lower with increasing age, previous tuberculosis, and decreasing body mass index. Diabetes and tobacco smoking did not modify accuracy. CONCLUSION: In a population where most tuberculosis was smear-positive, LUNIT-reported radiographic abnormalities were associated with culture-confirmed disease. Manufacturer-recommended threshold scores had limited sensitivity.
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Aprendizaje Profundo , Mycobacterium tuberculosis , Tuberculosis Pulmonar , Tuberculosis , Adulto , Humanos , Estudios Prospectivos , Sensibilidad y Especificidad , Programas Informáticos , Tuberculosis Pulmonar/diagnóstico por imagen , Tuberculosis Pulmonar/epidemiología , Rayos XRESUMEN
Background: Before August 2021, the only regimen recommended by the World Health Organization (WHO) to treat pediatric drug-susceptible tuberculous meningitis was a 12-month regimen consisting of isoniazid, rifampicin, ethambutol, and pyrazinamide (2HRZE/10HR). The comparative effectiveness of shorter regimens is unknown. Methods: To inform a WHO guideline update, we undertook a systematic review and meta-analysis to evaluate outcomes from regimens of 6- to less than 12-months' duration that included, at a minimum, isoniazid, rifampicin, and pyrazinamide. We included studies that applied rigorous diagnostic criteria and reported outcomes for ≥10 children or adolescents. Using generalized linear mixed models, we estimated the random effects pooled proportions of patients with key outcomes. Results: Of 7 included studies, none compared regimens head-to-head. Three studies (724 patients) used a 6-month intensive regimen, which includes isoniazid and rifampicin at higher doses, pyrazinamide, and ethionamide instead of ethambutol (6HRZEto). Outcomes for this versus the 12-month regimen (282 patients, 3 studies) were, respectively, as follows: death, 5.5% (95% confidence interval [CI], 2.1%-13.4%) vs 23.9% (95% CI, 17.5%-31.7%); treatment success (survival with or without sequelae), 94.6% (95% CI, 73.9%-99.1%) vs 75.4% (95% CI, 68.7%-81.1%); and neurological sequelae among survivors, 66.0% (95% CI, 55.3%-75.3%) vs 36.3% (95% CI, 30.1%-43.0%). Relapse did not occur among 148 patients followed-up for 2 years after completing the 6-month intensive regimen. Conclusions: Our findings are limited by the small number of studies and substantial potential for confounding. Nonetheless, the 6HRZEto regimen was associated with high treatment success and is now recommended by WHO as an alternative to the 12-month regimen.
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BACKGROUND: Deep learning-based radiological image analysis could facilitate use of chest x-rays as triage tests for pulmonary tuberculosis in resource-limited settings. We sought to determine whether commercially available chest x-ray analysis software meet WHO recommendations for minimal sensitivity and specificity as pulmonary tuberculosis triage tests. METHODS: We recruited symptomatic adults at the Indus Hospital, Karachi, Pakistan. We compared two software, qXR version 2.0 (qXRv2) and CAD4TB version 6.0 (CAD4TBv6), with a reference of mycobacterial culture of two sputa. We assessed qXRv2 using its manufacturer prespecified threshold score for chest x-ray classification as tuberculosis present versus not present. For CAD4TBv6, we used a data-derived threshold, because it does not have a prespecified one. We tested for non-inferiority to preset WHO recommendations (0·90 for sensitivity, 0·70 for specificity) using a non-inferiority limit of 0·05. We identified factors associated with accuracy by stratification and logistic regression. FINDINGS: We included 2198 (92·7%) of 2370 enrolled participants. 2187 (99·5%) of 2198 were HIV-negative, and 272 (12·4%) had culture-confirmed pulmonary tuberculosis. For both software, accuracy was non-inferior to WHO-recommended minimum values (qXRv2 sensitivity 0·93 [95% CI 0·89-0·95], non-inferiority p=0·0002; CAD4TBv6 sensitivity 0·93 [0·90-0·96], p<0·0001; qXRv2 specificity 0·75 [0·73-0·77], p<0·0001; CAD4TBv6 specificity 0·69 [0·67-0·71], p=0·0003). Sensitivity was lower in smear-negative pulmonary tuberculosis for both software, and in women for CAD4TBv6. Specificity was lower in men and in those with previous tuberculosis, and reduced with increasing age and decreasing body mass index. Smoking and diabetes did not affect accuracy. INTERPRETATION: In an HIV-negative population, these software met WHO-recommended minimal accuracy for pulmonary tuberculosis triage tests. Sensitivity will be lower when smear-negative pulmonary tuberculosis is more prevalent. FUNDING: Canadian Institutes of Health Research.
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Aprendizaje Profundo , Procesamiento de Imagen Asistido por Computador/métodos , Pulmón/patología , Radiología/métodos , Programas Informáticos , Triaje , Tuberculosis Pulmonar/diagnóstico , Adulto , Factores de Edad , Índice de Masa Corporal , Femenino , Infecciones por VIH , Humanos , Pulmón/diagnóstico por imagen , Pulmón/microbiología , Masculino , Persona de Mediana Edad , Mycobacterium tuberculosis/crecimiento & desarrollo , Pakistán , Estudios Prospectivos , Sensibilidad y Especificidad , Factores Sexuales , Esputo/microbiología , Tuberculosis Pulmonar/diagnóstico por imagen , Tuberculosis Pulmonar/microbiología , Rayos X , Adulto JovenRESUMEN
OBJECTIVE: To determine the diagnostic accuracy of serological tests for coronavirus disease-2019 (covid-19). DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline, bioRxiv, and medRxiv from 1 January to 30 April 2020, using subject headings or subheadings combined with text words for the concepts of covid-19 and serological tests for covid-19. ELIGIBILITY CRITERIA AND DATA ANALYSIS: Eligible studies measured sensitivity or specificity, or both of a covid-19 serological test compared with a reference standard of viral culture or reverse transcriptase polymerase chain reaction. Studies were excluded with fewer than five participants or samples. Risk of bias was assessed using quality assessment of diagnostic accuracy studies 2 (QUADAS-2). Pooled sensitivity and specificity were estimated using random effects bivariate meta-analyses. MAIN OUTCOME MEASURES: The primary outcome was overall sensitivity and specificity, stratified by method of serological testing (enzyme linked immunosorbent assays (ELISAs), lateral flow immunoassays (LFIAs), or chemiluminescent immunoassays (CLIAs)) and immunoglobulin class (IgG, IgM, or both). Secondary outcomes were stratum specific sensitivity and specificity within subgroups defined by study or participant characteristics, including time since symptom onset. RESULTS: 5016 references were identified and 40 studies included. 49 risk of bias assessments were carried out (one for each population and method evaluated). High risk of patient selection bias was found in 98% (48/49) of assessments and high or unclear risk of bias from performance or interpretation of the serological test in 73% (36/49). Only 10% (4/40) of studies included outpatients. Only two studies evaluated tests at the point of care. For each method of testing, pooled sensitivity and specificity were not associated with the immunoglobulin class measured. The pooled sensitivity of ELISAs measuring IgG or IgM was 84.3% (95% confidence interval 75.6% to 90.9%), of LFIAs was 66.0% (49.3% to 79.3%), and of CLIAs was 97.8% (46.2% to 100%). In all analyses, pooled sensitivity was lower for LFIAs, the potential point-of-care method. Pooled specificities ranged from 96.6% to 99.7%. Of the samples used for estimating specificity, 83% (10 465/12 547) were from populations tested before the epidemic or not suspected of having covid-19. Among LFIAs, pooled sensitivity of commercial kits (65.0%, 49.0% to 78.2%) was lower than that of non-commercial tests (88.2%, 83.6% to 91.3%). Heterogeneity was seen in all analyses. Sensitivity was higher at least three weeks after symptom onset (ranging from 69.9% to 98.9%) compared with within the first week (from 13.4% to 50.3%). CONCLUSION: Higher quality clinical studies assessing the diagnostic accuracy of serological tests for covid-19 are urgently needed. Currently, available evidence does not support the continued use of existing point-of-care serological tests. STUDY REGISTRATION: PROSPERO CRD42020179452.