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Predictors2 app for iPhone and iPad


4.5 ( 4215 ratings )
Education Medical
Developer: TouchCalc
1.99 USD
Current version: 1, last update: 7 years ago
First release : 26 Mar 2013
App size: 267.79 Kb

Over 500,000 patients in the USA are on dialysis therapy. Many can resume a reasonably active lifestyle, but for some the burdens of dialysis on the patient and their family outweigh the potential for a decent quality of life.

Three models, the Surprise Question 1, the Charlson Co-morbidity Index2 and the Karnofsky Score 3can give patients, their families and their physicians a rough idea of how well the patient will be able to adapt to dialysis and do well. These predictive models are each based on clinical studies, and take into account the patients preexisting clinical condition and co-morbidities.

The answer to the question ”Would your doctor be shocked if you died?” when coupled with age, the serum albumin level, dementia and peripheral vascular disease gives a rough estimate of a six and 18 month survival rate. The more negative factors that are present, the worse the outcome.

The Charlson co-morbidity index uses an algorithm based upon the patient’s age, serum albumin level, and other factors should as the co-existence of liver or lung disease, the presence of a stroke or malignancy, or whether or not a patient has AIDS or metastatic cancer to generate a score that relates to the one and two year survival rate.

The Karnofsky score looks at the patient’s level of independence to assess a prediction of how will he will do when on dialysis care.

They are useful tools for the physician to use in patients with advanced kidney disease when helping them and their families make an informed decision about what course of action to take should dialysis become necessary.

Never should one rely on tools alone, as each case must be individualized. One should always work with a physician or other suitable provider when planning future therapy.

References



1Moss, A. H. et al. Utility of the "surprise" question to identify dialysis patients with high mortality. Clin J Am Soc Nephrol 3, 1379-1384, doi:10.2215/CJN.00940208 (2008).
2Miskulin, D. C. et al. Predicting 1 year mortality in an outpatient haemodialysis population: a comparison of comorbidity instruments. Nephrol Dial Transplant 19, 413-420 (2004).
3Karnofsky, D. A. Determining the extent of the cancer and clinical planning for cure. Cancer 22, 730-734 (1968).