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Estimating End-of-Life for Hospitalized Patients

The Hospitalist. 2012 July;2012(07):

Susan Kreimer is a freelance medical writer based in New York.

Helpful End-of-Life Prediction Tools

APACHE II (Acute Physiology and Chronic Health Evaluation II)

A severity-of-disease classification system and one of several ICU scoring systems, it is applied within 24 hours of patient admission. An integer score from 0 to 71 is computed based on several measurements; higher scores correspond to more severe disease and a higher risk of death. https://clincalc.com/IcuMortality/APACHEII.aspx

SOFA (Sequential Organ Failure Assessment)

SOFA tracks a patient’s status during an ICU stay. This scoring system determines the extent of a person’s organ function or rate of failure. The overall score is based on scores of the respiratory, cardiovascular, hepatic, coagulation, renal, and neurological systems. https://www.sfar.org/scores2/sofa2.html

The Karnofsky Performance Scale Index

This tool allows patients to be classified by functional impairment. It compares effectiveness of different therapies and assesses the prognosis in individual patients. The lower the Karnofsky score, the worse the survival outlook for most serious illnesses. https://www.hospicepatients.org/karnofsky.html

PPS (Palliative Performance Scale) 

First introduced in 1996 as a tool for performance status in palliative care, the PPS uses five observer-rated domains correlated to the Karnofsky index (100-0). PPS is used in many countries and is translated into many languages. https://supportforhome.wordpress.com/2011/06/15/palliative-performance-scale/

The BODE Index

BODE helps predict mortality from chronic obstructive pulmonary disease (COPD) after diagnosis. Presumably, a higher BODE score correlates with an increased risk of death. https://copd.about.com/od/copdbasics/a/BODEIndex.htm

The Charlson Comorbidity Index

This index predicts the 10-year mortality for a patient who might have a range of comorbid conditions, such as heart disease, AIDS, or cancer (a total of 22 conditions). Each condition is assigned a score, depending on the risk of dying associated with the condition. https://www.medal.org/OnlineCalculators/ch1/ch1.13/ch1.13.01.php

Hemodialysis Mortality Predictor

This online calculator estimates prognosis in end-stage renal disease patients using an integrated model that incorporates the patient age, serum albumin, comorbidities, and clinician assessment of the patient’s likelihood of being dead within a year. https://touchcalc.com/calculators/sq

—Susan Kreimer

References

  1. Walling AM, Asch SM, Lorenz KA, et al. The quality of care provided to hospitalized patients at the end of life. Arch Intern Med. 2010;170(12):1057-1063.
  2. Yourman LC, Lee SJ, Schonberg MA, Widera EW, Smith AK. Prognostic indices for older adults: a systematic review. JAMA. 2012;307(2):182-192.
  3. Grudzen C, Grady D. Improving care at the end of life. Arch Intern Med. 2011;171(13):1202.
  4. Grudzen C. At the end of life, sometimes less is more. Arch Intern Med. 2011;171(13):1201.
  5. Bale PW. Honoring patients’ wishes for less health care. Arch Intern Med. 2011;171(13):1200.