Data KeGFR

Patient demographic data available upon application from the New South Wales (Australia) Health South Eastern Sydney Local Health District Human Research Ethics Committee (HREC

Prediction of DGF using KeGFR versus the clinical model.

<p>Model enhancement was analysed by calculation of the IDI. The clinical base model was derived from recipient-, donor- and transplant related factors (reference [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125669#pone.0125669.ref008" target="_blank">8</a>]). There is no KeGFRpCysC at 0–4h since no 0h pCysC data were available.</p><p>Key:</p><p>^a: metrics are not calculable for baseline model alone</p><p>^b: p < 0.05 vs. base model; IDI: integrated discrimination improvement.</p><p>Prediction of DGF using KeGFR versus the clinical model.</p

Kinetic Estimation of GFR Improves Prediction of Dialysis and Recovery after Kidney Transplantation

<div><p>Background</p><p>The early prediction of delayed graft function (DGF) would facilitate patient management after kidney transplantation.</p><p>Methods</p><p>In a single-centre retrospective analysis, we investigated kinetic estimated GFR under non-steady-state conditions, KeGFR, in prediction of DGF. KeGFR_sCr was calculated at 4h, 8h and 12h in 56 recipients of deceased donor kidneys from initial serum creatinine (sCr) concentrations, estimated creatinine production rate, volume of distribution, and the difference between consecutive sCr values. The utility of KeGFR_sCr for DGF prediction was compared with, sCr, plasma cystatin C (pCysC), and KeGFR_pCysC similarly derived from pCysC concentrations.</p><p>Results</p><p>At 4h, the KeGFR_sCr area under the receiver operator characteristic curve (AUC) for DGF prediction was 0.69 (95% CI: 0.56–0.83), while sCr was not useful (AUC 0.56, (CI: 0.41–0.72). Integrated discrimination improvement analysis showed that the KeGFR_sCr improved a validated clinical prediction model at 4h, 8h, and 12h, increasing the AUC from 0.68 (0.52–0.83) to 0.88 (0.78–0.99) at 12h (p = 0.01). KeGFR_pCysC also improved DGF prediction. In contrast, sCr provided no improvement at any time point.</p><p>Conclusions</p><p>Calculation of KeGFR from sCr facilitates early prediction of DGF within 4 hours of renal transplantation.</p></div

Clinical model enhancement by measured and calculated variables at 12h.

<p>A: serum creatinine (sCr), B: estimated GFR using sCr (KeGFR_sCr) C: plasma Cystatin C (pCysC), D: estimated GFR using pCysC (KeGFR_pCysC).</p

KeGFR versus eGFR, and KeGFR_sCr vs. KeGFR_pCysC.

<p>A—C: Unadjusted eGFR_sCr and KeGFR_sCr values stratified for DGF (red) or Non-DGF (black) at 4h (A), 8h (B), and 12h (C). D: Bland-Altman Plot comparing eGFR and KeGFR at 4h (blue triangles), 8h (open squares), and 12h (red circles) after kidney transplantation. Dotted line represents bias (mean difference between parameters); dashed lines represent 95% limits of agreement. E and F: Values for each patient of eGFR_pCysC and KeGFR_pCysC stratified for DGF or Non-DGF at 8h (E) and 12h (F) G: Bland-Altman Plot comparing eGFR and KeGFR at 8h and 12h after kidney transplantation. H: Bland-Altman Plot comparing KeGFR_sCr and KeGFR_pCysC at 8h and 12h after kidney transplantation. There was no KeGFR_pCysC determined at 4h since no 0h pCysC data were available. #: p ≥ 0.05, * p < 0.05.</p

Baseline characteristics of transplant recipients and donors.

<p>Key:</p><p>^a: all others peritoneal dialysis</p><p>^b: all others rabbit anti-thymocyte globulin</p><p>^c: No donor contributed a kidney to more than one recipient within the cohort</p><p>DGF: Delayed Graft Function, Non-DGF: Non-Delayed Graft Function,</p><p>ESKD: End Stage Kidney Disease; ECD: Expanded Criteria Donor; sCr: serum creatinine.</p><p>Baseline characteristics of transplant recipients and donors.</p

Serum creatinine, plasma cystatin C, unadjusted eGFR and kinetic estimated GFR for each patient.

<p>Values for each patient of (A) serum creatinine (sCr), (B) unadjusted estimate of GFR using sCr (eGFR_sCr), (C) kinetic estimate of GFR using sCr (KeGFR_sCr), (D) plasma cystatin C (pCysC), (E) unadjusted estimate of GFR using pCysC (eGFR_pCysC), and (F) kinetic estimate of GFR using pCysC (KeGFR_pCysC). Results are stratified for patients developed delayed graft function, i.e. dialysis requirement within 7 days (red) and those who did not (black). Red squares represent patients who were dialysed before the next timepoint. There is no KeGFR_pCysC at 0–4h since no 0h pCysC data were available.</p

Accidental pharmacological poisonings in young children: population-based study in three settings

<p><b>Introduction:</b> Pharmacological poisonings in young children are avoidable. Previous studies report calls to poisons centres, presentations to emergency departments (ED) or hospital admissions. There are limited data assessing concurrent management of poisonings across all three settings. We aimed to describe accidental pharmacological poisonings in young children across our Poisons Information Centre (PIC), EDs and hospitals.</p> <p><b>Methods:</b> A population-based study in New South Wales, Australia, of PIC calls, ED presentations and hospital admissions for accidental pharmacological poisoning in children aged <5 years, 2007–2013. We examined trends, medicines responsible and subsequent management. Medicines were coded using ICD10-AM diagnosis codes (T36-50).</p> <p><b>Results:</b> Over 2007–2013, pharmacological poisonings accounted for 67,816 PIC calls, 7739 ED presentations and 2082 admissions. Rates (per 10,000 children) of PIC calls declined from 220 to 178; ED presentations were stable (∼22–24), with a decrease in emergency cases offset by an increase in semi- or non-urgent presentations; hospital admissions declined (8–5). Most PIC calls related to “non-opioid analgesics” (25%), and “topical agents” (18%). Nearly every day, one child aged <5 years was admitted to hospital for poisoning. “Benzodiazepines”, “other and unspecified antidepressants”, “uncategorised antihypertensives”, and “4-aminophenol derivatives” accounted for over one-third of all admissions. Most PIC calls (90%) were advised to stay home, 6% referred to hospital. One-quarter of ED presentations resulted in admission.</p> <p><b>Conclusions:</b> Poisonings reported to PIC and hospitals declined, however, non-urgent ED presentations increased. Strategies to reduce therapeutic errors and access to medicines, and education campaigns to improve Poisons Centre call rates to prevent unnecessary ED presentations are needed.</p

Characteristics of the snakebite victims who responded to the invitation and non-responders.

<p>NS – not significant.</p

Correlation with post-traumatic stress disorder symptom (PTSD) score.

<p>**Correlation is significant at the 0.01 level.</p