Background: Nontuberculous mycobacteria (NTM) are ubiquitous in the environment and a well-known cause of lymphadenitis, skin and soft tissue infections. The aim of this study was to evaluate the epidemiology of extrapulmonary pediatric NTM infections occurring from 2000 to 2017 in Queensland, Australia. Methods: All cases of NTM and TB are notifiable under the Queensland Public Health Act (2005) and associated regulations (2005). Data from 2000 to 2017 inclusive was collected from the Notifiable Conditions Database, a laboratory based notification system that covers private and public laboratory systems. Pediatric population demographic data were obtained from the Australian Bureau of Statistics by researching the number of children 0–14 years of age in Queensland from 2000 to 2017; both annual and averaged population was determined. The statistical software SPSS and Tableau was used for analysis. Results: The mean age of diagnosis was 2.5 years with a majority of the cohort being women. Mycobacterium avium was the most commonly diagnosed pathogen. Geographic regions with the highest numbers of cases were predominantly tropical and coastal areas. M. haemophilum emerged as a more common pathogen from 2011 following a period of major flooding. Conclusion: Characteristics of the cohort of children susceptible to NTM disease appears consistent with previous reports. However, changes in the epidemiology of NTM infection (such as incidence, species, and geographic distribution) in children may be linked to environmental and weather factors.

BackgroundClinically significant CKD following surgery for kidney cancer is associated with increased morbidity and mortality, but identifying patients at increased CKD risk remains difficult. Simple methods to stratify risk of clinically significant CKD after nephrectomy are needed.MethodsTo develop a tool for stratifying patients’ risk of CKD arising after surgery for kidney cancer, we tested models in a population-based cohort of 699 patients with kidney cancer in Queensland, Australia (2012–2013). We validated these models in a population-based cohort of 423 patients from Victoria, Australia, and in patient cohorts from single centers in Queensland, Scotland, and England. Eligible patients had two functioning kidneys and a preoperative eGFR ≥60 ml/min per 1.73 m2. The main outcome was incident eGFR <45 ml/min per 1.73 m2 at 12 months postnephrectomy. We used prespecified predictors—age ≥65 years old, diabetes mellitus, preoperative eGFR, and nephrectomy type (partial/radical)—to fit logistic regression models and grouped patients according to degree of risk of clinically significant CKD (negligible, low, moderate, or high risk).ResultsAbsolute risks of stage 3b or higher CKD were <2%, 3% to 14%, 21% to 26%, and 46% to 69% across the four strata of negligible, low, moderate, and high risk, respectively. The negative predictive value of the negligible risk category was 98.9% for clinically significant CKD. The c statistic for this score ranged from 0.84 to 0.88 across derivation and validation cohorts.ConclusionsOur simple scoring system can reproducibly stratify postnephrectomy CKD risk on the basis of readily available parameters. This clinical tool’s quantitative assessment of CKD risk may be weighed against other considerations when planning management of kidney tumors and help inform shared decision making between clinicians and patients.

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