Longitudinal associations between socioeconomic position and overall health of children with chronic kidney disease and their carers.

BACKGROUND: Disadvantaged socioeconomic position (SEP) is an important predictor of poor health in children with chronic kidney disease (CKD). The time course over which SEP influences the health of children with CKD and their carers is unknown. METHODS: This prospective longitudinal study included 377 children, aged 6-18 years with CKD (stages I-V, dialysis, and transplant), and their primary carers. Mixed effects ordinal regression was performed to assess the association between SEP and carer-rated child health and carer self-rated health over a 4-year follow-up. RESULTS: Adjusted for CKD stage, higher family household income (adjusted odds ratio (OR) (95% CI) 3.3, 1.8-6.0), employed status of primary carers (1.7, 0.9-3.0), higher carer-perceived financial status (2.6, 1.4-4.8), and carer home ownership (2.2, 1.2-4.0) were associated with better carer-rated child health. Household income also had a differential effect on the carer's self-rated health over time (p = 0.005). The predicted probabilities for carers' overall health being 'very good' among lower income groups at 0, 2, and 4 years were 0.43 (0.28-0.60), 0.34 (0.20-0.51), and 0.25 (0.12-0.44), respectively, and 0.81 (0.69-0.88), 0.84 (0.74-0.91), and 0.88 (0.76-0.94) for carers within the higher income group. CONCLUSIONS: Carers and their children with CKD in higher SEP report better overall child and carer health compared with those in lower SEP. Carers of children with CKD in low-income households had poorer self-rated health compared with carers in higher-income households at baseline, and this worsened over time. These cumulative effects may contribute to health inequities between higher and lower SEP groups over time. Graphical abstract A higher resolution version of the Graphical abstract is available as Supplementary information.

The effectiveness of contact investigation among contacts of tuberculosis patients: a systematic review and meta-analysis.

BACKGROUND: We aimed to evaluate the effectiveness of contact investigation in comparison with passive case detection alone, and estimate the yield of co-prevalent and incident tuberculosis (TB) and latent TB infection (LTBI) among contacts of patients with TB. METHODS: A systematic search was undertaken of studies published between 1 January 2011 and 1 October 2019 in the English language. The proportion of contacts diagnosed with co-prevalent TB, incident TB and/or LTBI was estimated. Evaluation of the effectiveness of contact investigation included randomised trials, while the yield of contact investigation (co-prevalent/incident TB and LTBI) was assessed in nonrandomised studies. RESULTS: Data were extracted from 244 studies, of which 187 studies measured the proportion of contacts diagnosed with TB disease and 135 studies measured LTBI prevalence. Individual randomised trials demonstrated that contact investigation increased TB case notification (relative risk 2.5, 95% CI 2.0-3.2) and TB case detection (OR 1.34, 95% CI 0.43-4.24) and decreased mortality (relative risk 0.6, 95% CI 0.4-0.8) and population TB prevalence (risk ratio 0.82, 95% CI 0.64-1.04). The overall pooled prevalence of TB was 3.6% (95% CI 3.3-4.0%; I2=98.9%, 181 studies). The pooled prevalence of microbiologically confirmed TB was 3.2% (95% CI 2.6-3.7%; I2=99.5%, 106 studies). The pooled incidence of TB was highest in the first year after exposure to index patients (2.0%, 95% CI 1.1-3.3%; I2=96.2%, 14 studies) and substantially lower 5 years after exposure to index patients (0.5%, 95% CI 0.3-0.9%; one study). The pooled prevalence of LTBI among contacts was 42.4% (95% CI 38.5-46.4%; I2=99.8%, 135 studies). CONCLUSIONS: This systematic review and meta-analysis found that contact investigation was effective in high-burden settings. The higher pooled prevalence estimates of microbiologically confirmed TB compared with previous reviews suggests newer rapid molecular diagnostics contribute to increased case detection.

Assessing the accuracy of two Bayesian forecasting programs in estimating vancomycin drug exposure.

BACKGROUND: Current guidelines for intravenous vancomycin identify drug exposure (as indicated by the AUC) as the best pharmacokinetic (PK) indicator of therapeutic outcome. OBJECTIVES: To assess the accuracy of two Bayesian forecasting programs in estimating vancomycin AUC0-∞ in adults with limited blood concentration sampling. METHODS: The application of seven vancomycin population PK models in two Bayesian forecasting programs was examined in non-obese adults (n = 22) with stable renal function. Patients were intensively sampled following a single (1000 mg or 15 mg/kg) dose. For each patient, AUC was calculated by fitting all vancomycin concentrations to a two-compartment model (defined as AUCTRUE). AUCTRUE was then compared with the Bayesian-estimated AUC0-∞ values using a single vancomycin concentration sampled at various times post-infusion. RESULTS: Optimal sampling times varied across different models. AUCTRUE was generally overestimated at earlier sampling times and underestimated at sampling times after 4 h post-infusion. The models by Goti et al. (Ther Drug Monit 2018. 40: 212-21) and Thomson et al. (J Antimicrob Chemother 2009. 63: 1050-7) had precise and unbiased sampling times (defined as mean imprecision <25% and <38 mg·h/L, with 95% CI for mean bias containing zero) between 1.5 and 6 h and between 0.75 and 2 h post-infusion, respectively. Precise but biased sampling times for Thomson et al. were between 4 and 6 h post-infusion. CONCLUSIONS: When using a single vancomycin concentration for Bayesian estimation of vancomycin drug exposure (AUC), the predictive performance was generally most accurate with sample collection between 1.5 and 6 h after infusion, though optimal sampling times varied across different population PK models.

Relative survival and quality of life benefits of pancreas-kidney transplantation, deceased kidney transplantation and dialysis in type 1 diabetes mellitus-a probabilistic simulation model.

For patients with type 1 diabetes mellitus who progress to the point of requiring renal replacement therapy, the relative benefits of simultaneous pancreas and kidney transplantation (SPK) and deceased donor kidney transplantation across different age categories compared to dialysis are uncertain. Using Australian and New Zealand registry data from 2006 to 2016, a probabilistic Markov model (n = 10 000) was built comparing patient survival between SPK and deceased donor kidney transplantation with dialysis. Compared to dialysis, the average life years saved (LYS) and quality-adjusted life years (QALY) for SPK and deceased donor kidney transplantation were 5.48 [95% CI 5.47, 5.49] LYS and 6.48 [6.47, 6.49] QALY, and 3.38 [3.36, 3.40] LYS and 2.46 [2.45, 2.47] QALY, respectively. For recipients aged 50 years or younger, receiving a deceased donor kidney, the average incremental gains compared to dialysis were 4.13 [4.10, 4.16] LYS and 2.99 [2.97, 3.01] QALY, and for recipients older than 50 years, 3.05 [3.02, 3.08] LYS and 2.25 [2.23, 2.27] QALY. Compared to dialysis, SPK transplantation incurs the greatest benefits in LYS and QALY for patients with type 1 diabetes requiring renal replacement therapy. Patients older than 50 years still experience survival benefits from deceased donor kidney transplantation compared to dialysis.

Comparison of the Area Under the Curve for Vancomycin Estimated Using Compartmental and Noncompartmental Methods in Adult Patients With Normal Renal Function.

BACKGROUND: Vancomycin pharmacokinetics are best described using a 2-compartment model. However, 1-compartment population models are commonly used as the basis for dose prediction software. Therefore, the validity of using a 1-compartment model to guide vancomycin drug dosing was examined. METHODS: Published plasma concentration-time data from adult subjects (n = 30) with stable renal function administered a single intravenous infusion of vancomycin were extracted from previous studies. The vancomycin area under the curve (AUC0-∞) was calculated for each subject using noncompartmental methods (AUCNCA) and by fitting 1- (AUC1CMT), 2- (AUC2CMT), and 3- (AUC3CMT) compartment infusion models. The optimal model fit was determined using the Akaike information criterion and visual inspection of the residual plots. The individual compartmental AUC0-∞ values from the 1- and 2-compartment models were compared with AUCNCA values using one-way repeated measures analysis of variance. RESULTS: The mean (±SD) AUC estimates were similar for the different methods: AUCNCA 180 ± 86 mg·h/L, AUC1CMT 167 ± 79 mg·h/L, and AUC2CMT 183 ± 88 mg·h/L. Despite the overlapping AUC values, AUC2CMT and AUCNCA were significantly greater than AUC1CMT (P < 0.05). The 3-compartment model was excluded from the analysis because of the failure to converge in some instances. CONCLUSIONS: Dose prediction software using a 1-compartment model as the basis for Bayesian forecasting underestimates drug exposure (estimated as the AUC) by less than 10%. This is unlikely to be clinically significant with respect to dose adjustment. Therefore, a 1-compartment model may be sufficient to guide vancomycin dosing in adult patients with stable renal function.

Unexpected donor-derived infectious transmissions by kidney transplantation: A systematic review.

BACKGROUND: Unexpected donor-derived transmission of infections is rare, but is associated with significant morbidity and mortality. We aimed to provide an overview of published cases on unexpected infectious transmissions. METHODS: We systematically reviewed all published evidence describing any unexpected donor-derived viral, bacterial, fungal, and parasitic infections in kidney transplant recipients. RESULTS: In all, 119 studies (case reports [n = 36], case series [n = 78], cohort studies [n = 2], and case-control studies [n = 3]) involving 139 donors and 207 kidney recipients were included. Donor-derived viral (n = 116, 56.0%) infections were most prevalent, followed by bacterial (32, 15.5%), fungal (32, 15.5%), and parasitic (27, 13.0%) infections. The most commonly reported viral infections were human immunodeficiency virus (HIV) (n = 20, 9.7%), human T-cell lymphotrophic virus (HTLV) (n = 20, 9.7%), and West Nile virus (WNV) (n = 13, 6.3%). The most frequent bacterial infections were caused by Mycobacterium tuberculosis (10, 4.8%) and Pseudomonas aeruginosa (9, 4.3%). Candida species were the most frequent causes of fungal donor-derived infections (8, 3.9%). Toxoplasma gondii accounted for seven (3.4%) cases of transmitted parasitic infections. Patients with rabies experienced the highest probability of recipient death from virus-related complications at 90.0%, within a median time of 2.8 months after transplantation. CONCLUSION: The frequency of donor-derived infectious transmission appears low in kidney transplantation, with viral transmissions being most commonly reported overall.

Cutaneous Mucormycosis in an Immunocompetent Child following a Minor Skin Trauma.

Cutaneous mucormycosis is a rare infection by the Zygomycetes class of fungi, which carries significant morbidity and mortality. While typically associated in patients with underlying immunocompromise (especially in the current era of COVID-19), it may also be seen in immunocompetent patients. We report a case of a healthy 4-year-old girl with acute right leg cellulitis and abscess formation, who required surgical debridement following poor response to antibiotic therapy and initial incision and drainage. Tissue histopathology returned cutaneous zygomycosis despite negative tissue cultures. At four-week follow-up, her wound was healed well. Clinicians should maintain a high degree of clinical suspicion for cutaneous mucormycosis given its potential for rapidly progressive and disseminated disease. Currently, the mainstay of diagnostic investigations is tissue histopathology, with a growing role for tissue fungal PCR. Treatment involves multidisciplinary management between surgeons and Infectious Diseases team to guide the role for surgical debridement and antifungal therapy.

Survival outcomes for breast cancer patients who decline recommended treatment: a propensity score-matched analysis.

BACKGROUND: For patients with breast cancer who decline recommended treatments, available data examining survival outcomes are sparse. We compared overall survival and relapse-free survival outcomes between patients with breast cancer who declined recommended primary treatments and those who received recommended primary treatments. METHODS: Using data from the BreastSurgANZ Quality Audit database, a retrospective cohort study was performed for patients diagnosed with breast carcinoma (stage 0-IV) between 2001 and 2014 who were treated in our integrated cancer centre. A propensity score-matched analysis was performed to compare overall survival and relapse-free survival between patients who either declined or received the standard recommended treatment. RESULTS: A total of 56/912 (6.1%) patients declined one or more recommended therapies. Five-year overall survival for those who declined or received treatment as recommended was 81.8% versus 88.9% (P = 0.17), respectively. Ten-year survival was 61.3% versus 67.8% (P = 0.22), respectively. For patients who declined treatments, 5-year relapse-free survival was 72.4%, compared to 87.4% for those who received them (P = 0.005). Ten-year relapse-free survival was 61.0% versus 80.6% (P = 0.002), respectively. On adjusted Cox regression analysis, treatment refusal was associated with poorer relapse-free survival (adjusted hazard ratio 2.76 (95% confidence interval 1.52-5.00), P < 0.001). CONCLUSION: In conclusion, patients who declined recommended treatment for breast cancer had poorer relapse-free survival compared to those who received them. These data may help clinicians assist patients with breast cancer in their decision-making.