A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

How accurately do nephrologists predict the need for dialysis within one year? | LitMetric

How accurately do nephrologists predict the need for dialysis within one year?

Nephron Clin Pract

Vascular Research Group, Salford Royal Hospital, Manchester Academic Health Sciences Centre, Manchester, UK.

Published: February 2014

Background/aims: Knowing when patients with chronic kidney disease will need dialysis can improve patient counselling and timing of vascular access. We aimed to assess the accuracy of clinician judgement in predicting the need for dialysis within 12 months.

Methods: We asked the nephrologists in a dedicated pre-dialysis clinic to predict the time until initiation of dialysis for patients. We compared predicted with actual time to dialysis and the accuracy of predictions made by different grades of clinician. Multivariate logistic regression compared clinical parameters that correlated with predicted and actual time to dialysis.

Results: One hundred and eighty-four patients were included. The sensitivity of clinician judgement as a predictor of dialysis within 12 months was 95% and the specificity was 62%. Consultants were correct in 71% of cases and trainees in 68% of cases. Estimated glomerular filtration rate (eGFR) was the only independent correlate of predicted time to dialysis [odds ratio (OR) = 1.6 per 1 ml/min/1.73 m(2) reduction, p < 0.001]. eGFR was also associated with actual time to dialysis (OR = 1.6 per 1 ml/min/1.73 m(2), p < 0.001) along with age (OR = 0.94 per year increase, p = 0.005) and itch (OR = 3.7, p = 0.048).

Conclusion: Clinical judgement is sensitive but not specific in predicting the need for dialysis. Educating the clinicians may improve the specificity of judgement and improve the accuracy of prognostic information given to patients.

Download full-text PDF

Source
http://dx.doi.org/10.1159/000350730DOI Listing

Publication Analysis

Top Keywords

actual time
12
time dialysis
12
dialysis
9
clinician judgement
8
predicting dialysis
8
predicted actual
8
time
5
accurately nephrologists
4
nephrologists predict
4
predict dialysis
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!