SGLT2 inhibitors: Beyond glycemic control.

Multiple randomized controlled trials have extensively examined the therapeutic effectiveness of sodium-glucose cotransporter 2 (SGLT2) inhibitors, ushering in a transformative approach to treating individuals with type 2 diabetes mellitus (DM). Notably, emerging reports have drawn attention to the potential positive impacts of SGLT2 inhibitors in nondiabetic patients. In an effort to delve into this phenomenon, a comprehensive systematic literature review spanning PubMed (NLM), Medline (Ovid), and Cochrane Library, covering publications from 2000 to 2024 was undertaken. This systematic review encompassed twenty-six randomized control trials (RCTs) involving 35,317 participants. The findings unveiled a multifaceted role for SGLT2 inhibitors, showcasing their ability to enhance metabolic control and yield cardioprotective effects through a reduction in cardiovascular death (CVD) and hospitalization related to heart failure (HF). Additionally, a renalprotective effect was observed, evidenced by a slowdown in chronic kidney disease (CKD) progression and a decrease in albuminuria. Importantly, these benefits were coupled with an acceptable safety profile. The literature also points to various biological plausibility and underlying mechanistic pathways, offering insights into the association between SGLT2 inhibitors and these positive outcomes in nondiabetic individuals. Current research trends indicate a continual exploration of additional role for SGLT2 inhibitors in. Nevertheless, further research is imperative to fully elucidate the mechanisms and long-term outcomes associated with the nondiabetic use of SGLT2 inhibitors.

Performance of Existing and Novel Symptom- and Antigen Testing-Based COVID-19 Case Definitions in a Community Setting.

Point-of-care antigen tests are an important tool for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection, yet are less clinically sensitive than real-time reverse-transcription polymerase chain reaction (RT-PCR), affecting their efficacy as screening procedures. Our goal in this analysis was to see whether we could improve this sensitivity by considering antigen test results in combination with other relevant information, namely exposure status and reported symptoms. In November 2020, we collected 3,419 paired upper respiratory specimens tested by RT-PCR and the Abbott BinaxNOW (Abbott Laboratories, Abbott Park, Illinois) antigen test at 2 community testing sites in Pima County, Arizona. We used symptom, exposure, and antigen-testing data to evaluate the sensitivity and specificity of various symptom definitions in predicting RT-PCR positivity. Our analysis yielded 6 novel multisymptom case definitions with and without antigen test results, the best of which overall achieved a Youden's J index of 0.66, as compared with 0.53 for antigen testing alone. Using a random forest as a guide, we show that this definition, along with our others, does not lose the ability to generalize well to new data despite achieving optimal performance in our sample. Our methodology is broadly applicable, and our code is publicly available to aid public health practitioners in developing or fine-tuning their own case definitions.

Menstrual irregularities and vaginal bleeding after COVID-19 vaccination reported to v-safe active surveillance, USA in December, 2020-January, 2022: an observational cohort study.

BACKGROUND: Anecdotal reports of menstrual irregularities after receiving COVID-19 vaccines have been observed in post-authorisation and post-licensure monitoring. We aimed to identify and classify reports of menstrual irregularities and vaginal bleeding after COVID-19 vaccination submitted to a voluntary active surveillance system. METHODS: This observational cohort study included recipients of a COVID-19 vaccine who were aged 18 years and older and reported their health experiences to v-safe, a voluntary smartphone-based active surveillance system for monitoring COVID-19 vaccine safety in the USA, from Dec 14, 2020, to Jan 9, 2022. Responses to survey questions on reactions after vaccination were extracted, and a pre-trained natural language inference model was used to identify and classify free-text comments related to menstruation and vaginal bleeding in response to an open-ended prompt about any symptoms at intervals after vaccination. Related responses were further categorised into themes of timing, severity, perimenopausal and postmenopausal bleeding, resumption of menses, and other responses. We examined associations between symptom theme and respondent characteristics, including vaccine type and dose number received, solicited local and systemic reactions reported, and health care sought. FINDINGS: 63 815 respondents reported on menstrual irregularities or vaginal bleeding, which included 62 679 female respondents (1·0% of 5 975 363 female respondents aged ≥18 years). Common themes identified included timing of menstruation (70 981 [83·6%] responses) and severity of menstrual symptoms (56 890 [67·0%] responses). Other themes included menopausal bleeding (3439 [4·0%] responses) and resumption of menses (2378 [2·8%] responses). Respondents submitting reports related to menopausal bleeding were more likely to seek health care than were those submitting reports related to other menstruation and vaginal bleeding themes. INTERPRETATION: Reports of heterogeneous symptoms related to menstruation or vaginal bleeding after COVID-19 vaccination are being submitted to v-safe, although this study is unable to characterise the relationship of these symptoms to COVID-19 vaccination. Methods that leverage pretrained models to interpret and classify unsolicited signs and symptoms in free-text reports offer promise in the initial evaluation of unexpected adverse events potentially associated with use of newly authorised or licensed vaccines. FUNDING: Centers for Disease Control and Prevention.

Using Machine Learning Techniques and National Tuberculosis Surveillance Data to Predict Excess Growth in Genotyped Tuberculosis Clusters.

The early identification of clusters of persons with tuberculosis (TB) that will grow to become outbreaks creates an opportunity for intervention in preventing future TB cases. We used surveillance data (2009-2018) from the United States, statistically derived definitions of unexpected growth, and machine-learning techniques to predict which clusters of genotype-matched TB cases are most likely to continue accumulating cases above expected growth within a 1-year follow-up period. We developed a model to predict which clusters are likely to grow on a training and testing data set that was generalizable to a validation data set. Our model showed that characteristics of clusters were more important than the social, demographic, and clinical characteristics of the patients in those clusters. For instance, the time between cases before unexpected growth was identified as the most important of our predictors. A faster accumulation of cases increased the probability of excess growth being predicted during the follow-up period. We have demonstrated that combining the characteristics of clusters and cases with machine learning can add to existing tools to help prioritize which clusters may benefit most from public health interventions. For example, consideration of an entire cluster, not only an individual patient, may assist in interrupting ongoing transmission.

Performance of existing and novel surveillance case definitions for COVID-19 in household contacts of PCR-confirmed COVID-19.

BACKGROUND: Optimized symptom-based COVID-19 case definitions that guide public health surveillance and individual patient management in the community may assist pandemic control. METHODS: We assessed diagnostic performance of existing cases definitions (e.g. influenza-like illness, COVID-like illness) using symptoms reported from 185 household contacts to a PCR-confirmed case of COVID-19 in Wisconsin and Utah, United States. We stratified analyses between adults and children. We also constructed novel case definitions for comparison. RESULTS: Existing COVID-19 case definitions generally showed high sensitivity (86-96%) but low positive predictive value (PPV) (36-49%; F-1 score 52-63) in this community cohort. Top performing novel symptom combinations included taste or smell dysfunction and improved the balance of sensitivity and PPV (F-1 score 78-80). Performance indicators were generally lower for children (< 18 years of age). CONCLUSIONS: Existing COVID-19 case definitions appropriately screened in household contacts with COVID-19. Novel symptom combinations incorporating taste or smell dysfunction as a primary component improved accuracy. Case definitions tailored for children versus adults should be further explored.

Optimizing drug inventory management with a web-based information system: The TBTC Study 31/ACTG A5349 experience.

INTRODUCTION: Efficient management of study drug inventory shipments is critical to keep research sites enrolling into multisite clinical treatment trials. A standard manual drug-management process used by the Tuberculosis Trials Consortium (TBTC), did not accommodate import permit approval timelines, shipment transit-times and time-zone differences. We compared a new web-based solution with the manual process, during an international 34-site clinical trial conducted by the TBTC and the AIDS Clinical Trials Group (ACTG); TBTC Study 31/ACTG A5349. MATERIAL AND METHODS: We developed and implemented a technological solution by integrating logistical and regulatory requirements for drug importation with statistical simulations that estimated stock-out times in an online Drug Management Module (DMM). We measured the average shipment-related drug stock-outs and time to drug availability, to assess the efficiency of the DMM compared to the manual approach. RESULTS: An Interrupted Time-Series (ITS) analysis showed a 15.4% [p-value = 0.03; 95% C.I. (-28.8%, -2.0%)] reduction in average shipment-related study drug stock-out after DMM implementation. The DMM streamlined the restocking process at study sites, reducing median transit-time for sites associated with a depot by 2 days [95% C.I. (-3.0, -1.0)]. Under the DMM, study drugs were available for treatment assignment on the day received, compared to one day after receipt under the manual process. DISCUSSION: The DMM provided TBTC's Data and Coordinating Center and site staff with more efficient procedures to manage and consistently maintain study drug inventory at enrolling sites. This DMM framework can improve efficiency in future multicenter clinical trials. TRIAL REGISTRATION: This trial was registered with ClinicalTrials.gov (Identifier: NCT02410772) on April 8, 2015.

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.

Predictors of disease severity and outcome of hospitalized renal transplant recipients with COVID-19 infection: a systematic review of a globally representative sample.

Introduction. COVID-19 presents a special challenge to the kidney transplant population.Methods. A systematic review of articles that examined COVID-19 in kidney transplant recipients was performed. Patients' demographics, clinical, laboratory and radiological presentations, immunosuppression modification, and COVID-19 specific management were abstracted and analyzed. COVID-19 severity was classified into mild, moderate, and severe. Disease outcome was classified by whether the patient was discharged, still hospitalized, or died.Results. 44 articles reporting individual data and 13 articles reporting aggregated data on 149 and 561 kidney transplant recipients respectively with COVID-19 from Asia, Europe and America fulfilled all inclusion and exclusion criteria. Among studies reporting case specific data, 76% of cases had severe disease. Compared to patients with mild/moderate disease, patients with severe disease had higher CRP, LDH, Ferritin, D-dimer and were more likely to have bilateral lung involvement at presentation and longer time since transplantation (P < 0.05 for all). Recipients' age, gender and comorbidities did not impact disease severity. Patients with severe disease had a more aggressive CNI reduction and more antiviral medications utilization. Outcome was reported on 145 cases, of those 34 (23%) died all with severe disease. Longer duration from transplant to disease diagnosis, hypoxia and higher LDH were associated with mortality (P < 0.05). Different immunosuppression reduction strategies, high dose parenteral corticosteroids use and various antiviral combinations did not demonstrate survival advantage. Similar finding was observed for studies reporting aggregated data.Conclusion. COVID-19 in kidney transplant patients is associated with high rate of disease severity and fatality. Higher LDH and longer time since transplantation predicted both disease severity and mortality. None of the COVID-19 specific treatment correlated with, or improved disease outcome in kidney transplant recipients.

Mycobacterium tuberculosis bloodstream infection prevalence, diagnosis, and mortality risk in seriously ill adults with HIV: a systematic review and meta-analysis of individual patient data

BACKGROUND: The clinical and epidemiological significance of HIV-associated Mycobacterium tuberculosis bloodstream infection (BSI) is incompletely understood. We hypothesised that M tuberculosis BSI prevalence has been underestimated, that it independently predicts death, and that sputum Xpert MTB/RIF has suboptimal diagnostic yield for M tuberculosis BSI. METHODS: We did a systematic review and individual patient data (IPD) meta-analysis of studies performing routine mycobacterial blood culture in a prospectively defined patient population of people with HIV aged 13 years or older. Studies were identified through searching PubMed and Scopus up to Nov 10, 2018, without language or date restrictions and through manual review of reference lists. Risk of bias in the included studies was assessed with an adapted QUADAS-2 framework. IPD were requested for all identified studies and subject to harmonised inclusion criteria: age 13 years or older, HIV positivity, available CD4 cell count, a valid mycobacterial blood culture result (excluding patients with missing data from lost or contaminated blood cultures), and meeting WHO definitions for suspected tuberculosis (presence of screening symptom). Predicted probabilities of M tuberculosis BSI from mixed-effects modelling were used to estimate prevalence. Estimates of diagnostic yield of sputum testing with Xpert (or culture if Xpert was unavailable) and of urine lipoarabinomannan (LAM) testing for M tuberculosis BSI were obtained by two-level random-effect meta-analysis. Estimates of mortality associated with M tuberculosis BSI were obtained by mixed-effect Cox proportional-hazard modelling and of effect of treatment delay on mortality by propensity-score analysis. This study is registered with PROSPERO, number 42016050022. FINDINGS:We identified 23 datasets for inclusion (20 published and three unpublished at time of search) and obtained IPD from 20, representing 96·2% of eligible IPD. Risk of bias for the included studies was assessed to be generally low except for on the patient selection domain, which was moderate in most studies. 5751 patients met harmonised IPD-level inclusion criteria. Technical factors such as number of blood cultures done, timing of blood cultures relative to blood sampling, and patient factors such as inpatient setting and CD4 cell count, explained significant heterogeneity between primary studies. The predicted probability of M tuberculosis BSI in hospital inpatients with HIV-associated tuberculosis, WHO danger signs, and a CD4 count of 76 cells per µL (the median for the cohort) was 45% (95% CI 38­52). The diagnostic yield of sputum in patients with M tuberculosis BSI was 77% (95% CI 63­87), increasing to 89% (80­94) when combined with urine LAM testing. Presence of M tuberculosis BSI compared with its absence in patients with HIV-associated tuberculosis increased risk of death before 30 days (adjusted hazard ratio 2·48, 95% CI 2·05­3·08) but not after 30 days (1·25, 0·84­2·49). In a propensity-score matched cohort of participants with HIV-associated tuberculosis (n=630), mortality increased in patients with M tuberculosis BSI who had a delay in anti-tuberculosis treatment of longer than 4 days compared with those who had no delay (odds ratio 3·15, 95% CI 1·16­8·84). INTERPRETATION:In critically ill adults with HIV-tuberculosis, M tuberculosis BSI is a frequent manifestation of tuberculosis and predicts mortality within 30 days. Improved diagnostic yield in patients with M tuberculosis BSI could be achieved through combined use of sputum Xpert and urine LAM. Anti-tuberculosis treatment delay might increase the risk of mortality in these patients

Liberation from Dialysis Dependence in a Patient with HIV-Associated Nephropathy (HIVAN) after Combined Antiretroviral Therapy (cART).

Prior to the advent of combined antiretroviral therapy (cART), human immunodeficiency virus-associated nephropathy (HIVAN) was inevitably associated with rapidly progressive renal failure and dialysis dependence. HIV-1 seropositive patients often met with untimely deaths due to complications of end-stage renal disease (ESRD), opportunistic infections, or other HIV-related end-organ failure. Although the association between cART and improved outcomes in HIVAN has been recognized for over 20 years, no randomized trials have specifically examined this effect to date. In terms of reversal of dialysis-dependent renal failure after cART initiation, only a handful of case reports exist. The authors report a case of a 44-year-old Latino male requiring thrice-weekly haemodialysis in the setting of biopsy-proven HIVAN who was able to stop dialysis in 7 months after being initiated on cART.

Mycobacterium tuberculosis bloodstream infection prevalence, diagnosis, and mortality risk in seriously ill adults with HIV: a systematic review and meta-analysis of individual patient data.

BACKGROUND: The clinical and epidemiological significance of HIV-associated Mycobacterium tuberculosis bloodstream infection (BSI) is incompletely understood. We hypothesised that M tuberculosis BSI prevalence has been underestimated, that it independently predicts death, and that sputum Xpert MTB/RIF has suboptimal diagnostic yield for M tuberculosis BSI. METHODS: We did a systematic review and individual patient data (IPD) meta-analysis of studies performing routine mycobacterial blood culture in a prospectively defined patient population of people with HIV aged 13 years or older. Studies were identified through searching PubMed and Scopus up to Nov 10, 2018, without language or date restrictions and through manual review of reference lists. Risk of bias in the included studies was assessed with an adapted QUADAS-2 framework. IPD were requested for all identified studies and subject to harmonised inclusion criteria: age 13 years or older, HIV positivity, available CD4 cell count, a valid mycobacterial blood culture result (excluding patients with missing data from lost or contaminated blood cultures), and meeting WHO definitions for suspected tuberculosis (presence of screening symptom). Predicted probabilities of M tuberculosis BSI from mixed-effects modelling were used to estimate prevalence. Estimates of diagnostic yield of sputum testing with Xpert (or culture if Xpert was unavailable) and of urine lipoarabinomannan (LAM) testing for M tuberculosis BSI were obtained by two-level random-effect meta-analysis. Estimates of mortality associated with M tuberculosis BSI were obtained by mixed-effect Cox proportional-hazard modelling and of effect of treatment delay on mortality by propensity-score analysis. This study is registered with PROSPERO, number 42016050022. FINDINGS: We identified 23 datasets for inclusion (20 published and three unpublished at time of search) and obtained IPD from 20, representing 96·2% of eligible IPD. Risk of bias for the included studies was assessed to be generally low except for on the patient selection domain, which was moderate in most studies. 5751 patients met harmonised IPD-level inclusion criteria. Technical factors such as number of blood cultures done, timing of blood cultures relative to blood sampling, and patient factors such as inpatient setting and CD4 cell count, explained significant heterogeneity between primary studies. The predicted probability of M tuberculosis BSI in hospital inpatients with HIV-associated tuberculosis, WHO danger signs, and a CD4 count of 76 cells per µL (the median for the cohort) was 45% (95% CI 38-52). The diagnostic yield of sputum in patients with M tuberculosis BSI was 77% (95% CI 63-87), increasing to 89% (80-94) when combined with urine LAM testing. Presence of M tuberculosis BSI compared with its absence in patients with HIV-associated tuberculosis increased risk of death before 30 days (adjusted hazard ratio 2·48, 95% CI 2·05-3·08) but not after 30 days (1·25, 0·84-2·49). In a propensity-score matched cohort of participants with HIV-associated tuberculosis (n=630), mortality increased in patients with M tuberculosis BSI who had a delay in anti-tuberculosis treatment of longer than 4 days compared with those who had no delay (odds ratio 3·15, 95% CI 1·16-8·84). INTERPRETATION: In critically ill adults with HIV-tuberculosis, M tuberculosis BSI is a frequent manifestation of tuberculosis and predicts mortality within 30 days. Improved diagnostic yield in patients with M tuberculosis BSI could be achieved through combined use of sputum Xpert and urine LAM. Anti-tuberculosis treatment delay might increase the risk of mortality in these patients. FUNDING: This study was supported by Wellcome fellowships 109105Z/15/A and 105165/Z/14/A.

Tuberculosis disease and infection among household contacts of bacteriologically confirmed and non-confirmed tuberculosis patients.

OBJECTIVE: To compare the prevalence of tuberculosis infection and disease in household contacts of patients with bacteriologically confirmed tuberculosis disease and contacts of non-bacteriologically confirmed disease in western Kenya. METHODS: We enrolled newly diagnosed index patients and their household contacts from March 2014 to June 2016. All contacts were evaluated with a symptom questionnaire, tuberculin skin test (TST) and HIV test. Clinical evaluation and sputum testing were performed for those with symptoms, positive TST result or HIV infection. RESULTS: We enrolled 1155 contacts of 330 index patients with bacteriologically confirmed tuberculosis and 192 contacts of 55 index patients with non-bacteriologically confirmed tuberculosis. 3.5% of contacts of patients with bacteriologically confirmed tuberculosis were diagnosed with tuberculosis, whereas no contacts of index patients with non-bacteriologically confirmed tuberculosis were. Of those diagnosed with tuberculosis disease, 58.5% reported symptoms, 34.1% reported no symptoms but had positive TST results, and 7.3% had neither symptoms nor positive TST but were HIV-positive. Among 872 contacts with a TST result, 50.9% of contacts of index patients with bacteriologically confirmed tuberculosis and 41.0% of contacts of index patients with non-bacteriologically confirmed tuberculosis had a positive result (prevalence ratio = 1.16, 95% confidence interval 0.92-1.48). CONCLUSION: In a high-burden setting, tuberculosis disease was more prevalent among contacts of patients with bacteriologically confirmed tuberculosis than contacts of patients with non-bacteriologically confirmed disease. TST was feasible to perform and helped to detect cases that would have been missed had only symptomatic contacts been evaluated.

OBJECTIF: Comparer la prévalence de l'infection et de la maladie tuberculeuses chez les contacts familiaux des patients atteints de tuberculose confirmée bactériologiquement et les contacts de maladies non bactériologiquement confirmées dans l'ouest du Kenya. MÉTHODES: Nous avons recruté des patients indice nouvellement diagnostiqués et leurs contacts familiaux de mars 2014 à juin 2016. Tous les contacts ont été évalués à l'aide d'un questionnaire sur les symptômes, le test cutané à la tuberculine (TCT) et le test VIH. Une évaluation clinique et des tests d'expectoration ont été effectués pour les personnes présentant des symptômes, un résultat positif au TCT ou une infection par le VIH. RÉSULTATS: Nous avons recruté 1.155 contacts de 330 patients index avec une tuberculose confirmée bactériologiquement et 192 contacts de 55 patients indice avec une tuberculose non confirmée bactériologiquement. 3,5% des contacts des patients atteints de tuberculose confirmée bactériologiquement ont été diagnostiqués avec la tuberculose, alors qu'aucun contact des patients indice avec une tuberculose non bactériologiquement confirmée ne l'a été. Parmi les personnes diagnostiquées avec une tuberculose, 58,5% ont signalé des symptômes, 34,1% n'ont signalé aucun symptôme mais avaient des résultats positifs au TCT, et 7,3% n'avaient ni symptômes ni TCT positifs mais étaient VIH positifs. Parmi 872 contacts avec un résultat TCT, 50,9% des contacts des patients indice avec une tuberculose confirmée bactériologiquement et 41,0% des contacts des patients indice avec une tuberculose non bactériologiquement confirmée avaient un résultat positif (rapport de prévalence = 1,16, intervalle de confiance à 95%: 0,92-1,48 ). CONCLUSION: Dans un contexte de charge élevée, la maladie tuberculose était plus fréquente chez les contacts des patients atteints de tuberculose confirmée bactériologiquement que chez les contacts des patients atteints de la maladie non bactériologiquement confirmée. Le TCT était réalisable et a aidé à détecter les cas qui auraient été ratés si seuls les contacts symptomatiques avaient été évalués.

High-dose rifapentine with or without moxifloxacin for shortening treatment of pulmonary tuberculosis: Study protocol for TBTC study 31/ACTG A5349 phase 3 clinical trial.

INTRODUCTION: Phase 2 clinical trials of tuberculosis treatment have shown that once-daily regimens in which rifampin is replaced by high dose rifapentine have potent antimicrobial activity that may be sufficient to shorten overall treatment duration. Herein we describe the design of an ongoing phase 3 clinical trial testing the hypothesis that once-daily regimens containing high dose rifapentine in combination with other anti-tuberculosis drugs administered for four months can achieve cure rates not worse than the conventional six-month treatment regimen. METHODS/DESIGN: S31/A5349 is a multicenter randomized controlled phase 3 non-inferiority trial that compares two four-month regimens with the standard six-month regimen for treating drug-susceptible pulmonary tuberculosis in HIV-negative and HIV-positive patients. Both of the four-month regimens contain high-dose rifapentine instead of rifampin, with ethambutol replaced by moxifloxacin in one regimen. All drugs are administered seven days per week, and under direct observation at least five days per week. The primary outcome is tuberculosis disease-free survival at twelve months after study treatment assignment. A total of 2500 participants will be randomized; this gives 90% power to show non-inferiority with a 6.6% margin of non-inferiority. DISCUSSION: This phase 3 trial formally tests the hypothesis that augmentation of rifamycin exposures can shorten tuberculosis treatment to four months. Trial design and standardized implementation optimize the likelihood of obtaining valid results. Results of this trial may have important implications for clinical management of tuberculosis at both individual and programmatic levels. TRIAL REGISTRATION: NCT02410772. Registered 8 April 2015,https://www.clinicaltrials.gov/ct2/show/NCT02410772?term=02410772&rank=1.

High yield of new HIV diagnoses during active case-finding for tuberculosis.

OBJECTIVE: To evaluate the utility of a broad and nonspecific symptom screen for identifying people with undiagnosed HIV infection. DESIGN: Secondary analysis of operational data collected during implementation of a cluster-randomized trial for tuberculosis case detection. METHODS: As part of the trial, adults reporting cough, fever, night sweats, weight loss, or difficulty breathing for any duration in the past month were identified in health facilities and community-based mobile screening units in western Kenya. Adults reporting any symptom were offered HIV testing. We analysed the HIV testing data from this study, using modified Poisson regression, to identify predictors of new HIV diagnoses among adults with symptoms and initially unknown HIV status. RESULTS: We identified 3818 symptomatic adults, referred 1424 (37%) for testing, of whom 1065 (75%) accepted, and 107 (10%) were newly diagnosed with HIV. The prevalence of new HIV diagnoses was 21% [95% confidence interval (CI) 17-25%] among those tested in health facilities and 5% (95% CI 4-7%) among those tested in mobile units. More men were diagnosed with HIV than women, despite fewer men being screened. People who reported 4-5 symptoms were over twice as likely to be diagnosed with HIV compared to those reporting 1-3 symptoms (adjusted prevalence ratio in health facilities = 2.58, 95% CI 1.65-4.05; adjusted prevalence ratio in mobile units = 2.63, 95% CI 1.37-5.03). CONCLUSION: We observed a high yield of new HIV diagnoses among adults identified by active application of a broad symptom screen. Use of integrated tuberculosis and HIV screening could help close the detection gap for both conditions.

Effect of race and ethnicity on renal transplant referral
.

BACKGROUND: Multiple studies have revealed disparity in renal healthcare access and outcomes in racial/ethnic minorities with the socioeconomic status explaining the majority but not all of the disparity. We wanted to determine if racial/ethnic disparities existed at the first step toward renal transplantation, the renal transplant referral process. MATERIALS AND METHODS: A cohort of 200 adult end-stage renal disease patients was followed retrospectively for 2 years from January 2016 to February 2018. The study exposure was based on self-declared race/ethnicity of the patients, who were categorized as Black, White, and Hispanic. The study outcome was based on medical team patient evaluation and consisted of the patients who refused referral, who were not referred, and who were referred for transplant. Medical and demographic factors collected were age, gender, socioeconomic status, hemoglobin A1c ≥ 7, body mass index ≥ 40, left ventricular ejection fraction ≤ 40%, the presence of coronary or peripheral arterial disease, albumin level, history of smoking, cirrhosis, and cancer. The data were analyzed using univariate analyses and multinomial logistic regression. RESULTS: In the adjusted analysis, there was no difference in the likelihood of transplant referral between Black and White patients (OR = 0.71, 95% CI 0.22 - 2.3, p = 0.56). However, both Black (OR = 16, 95% CI 3.3 - 77, p = 0.0006) and White (OR = 22, 95% CI 3.4 - 150, p = 0.0013) patients were more likely to be referred for transplant when compared with Hispanic patients. Odds of transplant refusal were not different across race/ethnic groups. CONCLUSION: Hispanic patients are disadvantaged in the referral for renal transplant when compared to Black and White patients for reasons unclear at this time.

A comparison of machine learning algorithms for the surveillance of autism spectrum disorder.

OBJECTIVE: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speeding up this process, but they lag behind human classification accuracy by about 5%. We explore whether more recently available document classification algorithms can close this gap. MATERIALS AND METHODS: Using data gathered from a single surveillance site, we applied 8 supervised learning algorithms to predict whether children meet the case definition for ASD based solely on the words in their evaluations. We compared the algorithms' performance across 10 random train-test splits of the data, using classification accuracy, F1 score, and number of positive calls to evaluate their potential use for surveillance. RESULTS: Across the 10 train-test cycles, the random forest and support vector machine with Naive Bayes features (NB-SVM) each achieved slightly more than 87% mean accuracy. The NB-SVM produced significantly more false negatives than false positives (P = 0.027), but the random forest did not, making its prevalence estimates very close to the true prevalence in the data. The best-performing neural network performed similarly to the random forest on both measures. DISCUSSION: The random forest performed as well as more recently available models like the NB-SVM and the neural network, and it also produced good prevalence estimates. NB-SVM may not be a good candidate for use in a fully-automated surveillance workflow due to increased false negatives. More sophisticated algorithms, like hierarchical convolutional neural networks, may not be feasible to train due to characteristics of the data. Current algorithms might perform better if the data are abstracted and processed differently and if they take into account information about the children in addition to their evaluations. CONCLUSION: Deep learning models performed similarly to traditional machine learning methods at predicting the clinician-assigned case status for CDC's autism surveillance system. While deep learning methods had limited benefit in this task, they may have applications in other surveillance systems.

Chief complaint classification with recurrent neural networks.

Syndromic surveillance detects and monitors individual and population health indicators through sources such as emergency department records. Automated classification of these records can improve outbreak detection speed and diagnosis accuracy. Current syndromic systems rely on hand-coded keyword-based methods to parse written fields and may benefit from the use of modern supervised-learning classifier models. In this paper, we implement two recurrent neural network models based on long short-term memory (LSTM) and gated recurrent unit (GRU) cells and compare them to two traditional bag-of-words classifiers: multinomial naïve Bayes (MNB) and a support vector machine (SVM). The MNB classifier is one of only two machine learning algorithms currently being used for syndromic surveillance. All four models are trained to predict diagnostic code groups as defined by Clinical Classification Software, first to predict from discharge diagnosis, and then from chief complaint fields. The classifiers are trained on 3.6 million de-identified emergency department records from a single United States jurisdiction. We compare performance of these models primarily using the F1 score, and we measure absolute model performance to determine which conditions are the most amenable to surveillance based on chief complaint alone. Using discharge diagnoses, the LSTM classifier performs best, though all models exhibit an F1 score above 96.00. Using chief complaints, the GRU performs best (F1 = 47.38), and MNB with bigrams performs worst (F1 = 39.40). We also note that certain syndrome types are easier to detect than others. For example, chief complaints using the GRU model predicts alcohol-related disorders well (F1 = 78.91) but predicts influenza poorly (F1 = 14.80). In all instances, the RNN models outperformed the bag-of-words classifiers suggesting deep learning models could substantially improve the automatic classification of unstructured text for syndromic surveillance.

Opioid Prescribing Rates in Nonmetropolitan and Metropolitan Counties Among Primary Care Providers Using an Electronic Health Record System - United States, 2014-2017.

Drug overdose is the leading cause of unintentional injury-associated death in the United States. Among 70,237 fatal drug overdoses in 2017, prescription opioids were involved in 17,029 (24.2%) (1). Higher rates of opioid-related deaths have been recorded in nonmetropolitan (rural) areas (2). In 2017, 14 rural counties were among the 15 counties with the highest opioid prescribing rates.* Higher opioid prescribing rates put patients at risk for addiction and overdose (3). Using deidentified data from the Athenahealth electronic health record (EHR) system, opioid prescribing rates among 31,422 primary care providers† in the United States were analyzed to evaluate trends from January 2014 to March 2017. This analysis assessed how prescribing practices varied among six urban-rural classification categories of counties, before and after the March 2016 release of CDC's Guideline for Prescribing Opioids for Chronic Pain (Guideline) (4). Patients in noncore (the most rural) counties had an 87% higher chance of receiving an opioid prescription compared with persons in large central metropolitan counties during the study period. Across all six county groups, the odds of receiving an opioid prescription decreased significantly after March 2016. This decrease followed a flat trend during the preceding period in micropolitan and large central metropolitan county groups; in contrast, the decrease continued previous downward trends in the other four county groups. Data from EHRs can effectively supplement traditional surveillance methods for monitoring trends in opioid prescribing and other areas of public health importance, with minimal lag time under ideal conditions. As less densely populated areas appear to indicate both substantial progress in decreasing opioid prescribing and ongoing need for reduction, community health care practices and intervention programs must continue to be tailored to community characteristics.

A Unique Cause of Proteinuria in Pregnancy: Class II Lupus Nephritis with Concomitant Minimal Change Disease.

We report the case of a 22-year-old African American female who presented to another facility for routine follow-up in the 34th week of pregnancy with lower extremity swelling and nephrotic-range proteinuria. Although she was normotensive, it was initially thought that she had preeclampsia. She was monitored carefully and delivery was induced at 37 weeks of gestation. She was transferred to our hospital, where she was diagnosed with systemic lupus erythematosus (SLE) based on clinical and laboratory criteria. Renal biopsy revealed a surprising finding of minimal change disease (MCD) concomitant with class II lupus nephritis (LN). She was managed with pulses and then tapering doses of steroid therapy with dramatic resolution of the nephrotic syndrome. This case demonstrates not only the rare de novo occurrence of SLE in pregnancy, but the unique finding of MCD coexisting with class II LN. We propose that altered T cell activity may be the link between these seemingly distinct entities.

IFN-γ Release Assay Result Is Associated with Disease Site and Death in Active Tuberculosis.

RATIONALE: The IFN-γ release assays and tuberculin skin tests are used to support the diagnosis of both latent and active tuberculosis. However, we previously demonstrated that a negative tuberculin test in active tuberculosis is associated with disseminated disease and death. It is unknown whether the same associations exist for IFN-γ release assays. OBJECTIVES: To determine the association between these tests and site of tuberculosis and death among persons with active tuberculosis. METHODS: We analyzed IFN-γ release assays and tuberculin test results for all persons with culture-confirmed tuberculosis reported to the U.S. National Tuberculosis Surveillance System from 2010 to 2014. We used logistic regression to calculate the association between these tests and site of disease and death. MEASUREMENTS AND MAIN RESULTS: A total of 24,803 persons with culture-confirmed tuberculosis had either of these test results available for analysis. Persons with a positive tuberculin test had lower odds of disseminated disease (i.e., miliary or combined pulmonary and extrapulmonary disease), but there was no difference in the odds of disseminated disease with a positive IFN-γ release assay. However, persons who were positive to either of these tests had lower odds of death. An indeterminate IFN-γ release assay result was associated with greater odds of both disseminated disease and death. CONCLUSIONS: Despite perceived equivalence in clinical practice, IFN-γ release assays and tuberculin test results have different associations with tuberculosis site, yet similar associations with the risk of death. Furthermore, an indeterminate IFN-γ release assay result in a person with active tuberculosis is not unimportant, and rather carries greater odds of disseminated disease and death. Prospective study may improve our understanding of the underlying mechanisms by which these tests are associated with disease localization and death.