Feature

Q&A: Model predicts 6-month mortality in older adults hospitalized for heart attack

Photo of Sarwat Chaudhry
Sarwat I. Chaudhry

Professional cardiology and geriatrics societies have expressed a need for risk-stratification tools specific to older adults, and researchers have now developed a model to predict 6-month mortality in seniors hospitalized for acute myocardial infarction.

To develop the model, researchers evaluated data from 3,006 patients aged 75 years and older who were discharged alive after hospitalization for acute MI.

Fifteen risk factors were included in the final model, including four that had not been used in previous risk models for acute MI: hearing impairment, mobility impairment, weight loss and low patient-reported health status.

Researchers said the model has “had good discriminatory ability.”

Healio Primary Care spoke with Sarwat I. Chaudhry, MD, an associate professor of medicine at Yale School of Medicine, about why the model is needed, the variables her team included in it, and how the model can be implemented in practice. – by Erin Michael

Doctor with depressed elderly patient 
Professional cardiology and geriatrics societies have expressed a need for risk-stratification tools specific to older adults, and researchers have now developed a model to predict 6-month mortality in seniors hospitalized for acute myocardial infarction.
Source: Adobe Stock

Q: Why is there a need for risk-stratification tools specific to older adults?

A: Risk stratification tools are endorsed by major professional groups and clinical guidelines because they can assist with clinical decision-making by informing prognosis. Current risk stratification tools available for use in patients with heart attack were developed in younger patients and may not be as applicable in older patients who often have functional impairments — including those in mobility, hearing and vision. In fact, a recent scientific statement from cardiology professional societies emphasized the need for risk tools relevant for older adults.

Q: What is the importance of including information on functional impairment in the model?

A: The inclusion of functional impairments significantly improved the model’s ability to correctly predict which patients survive and which patients do not. When we look at the individual patient, we see an important change in risk depending on the functional impairments. We can consider two hypothetical patients, with the same age, race and gender, and even identical clinical characteristics — including type of heart attack, kidney function and blood count. If the first patient reports that hearing interferes with activities “a lot,” has fair health status, has slow gait (Timed Up and Go greater than 25 seconds) and reports unintentional weight loss of more than 10 pounds in the past year, the predicted risk for death within 6 months is 22% using the SILVER-AMI model. Conversely, if the second patient reports that hearing interferes with activities “a little,” has good health status, has a Timed Up and Go of 15 seconds or less and denies unintentional weight loss of more than 10 pounds in the past year, the predicted risk for death within 6 months is 5% using the SILVER-AMI model.

Q: Is it feasible to implement this model in hospitals across the United States? What are the challenges of doing so?

A: We recognize that our model includes information about functional impairments, which are not typically assessed as part of routine care for patients hospitalized for heart attack. This is part of the reason we verified that the impairments make an important improvement in the risk model’s performance. Based on our experience performing these assessments in over 3,000 acute MI patients at nearly 100 hospitals across the United States, we estimate that the assessments required for our model should take less than 10 minutes to complete. None of the assessments are protected by copyright, so they are all freely available. And we’ve made our model freely available as well. It is online at silverscore.org, and there is a free app.

Reference:

Dodson JA, et al. Ann Intern Med. 2019;doi:10.7326/M19-097.

Disclosures: Chaudhry reports no relevant financial disclosures. Please see study for all other authors’ relevant financial disclosures.

Photo of Sarwat Chaudhry
Sarwat I. Chaudhry

Professional cardiology and geriatrics societies have expressed a need for risk-stratification tools specific to older adults, and researchers have now developed a model to predict 6-month mortality in seniors hospitalized for acute myocardial infarction.

To develop the model, researchers evaluated data from 3,006 patients aged 75 years and older who were discharged alive after hospitalization for acute MI.

Fifteen risk factors were included in the final model, including four that had not been used in previous risk models for acute MI: hearing impairment, mobility impairment, weight loss and low patient-reported health status.

Researchers said the model has “had good discriminatory ability.”

Healio Primary Care spoke with Sarwat I. Chaudhry, MD, an associate professor of medicine at Yale School of Medicine, about why the model is needed, the variables her team included in it, and how the model can be implemented in practice. – by Erin Michael

Doctor with depressed elderly patient 
Professional cardiology and geriatrics societies have expressed a need for risk-stratification tools specific to older adults, and researchers have now developed a model to predict 6-month mortality in seniors hospitalized for acute myocardial infarction.
Source: Adobe Stock

Q: Why is there a need for risk-stratification tools specific to older adults?

A: Risk stratification tools are endorsed by major professional groups and clinical guidelines because they can assist with clinical decision-making by informing prognosis. Current risk stratification tools available for use in patients with heart attack were developed in younger patients and may not be as applicable in older patients who often have functional impairments — including those in mobility, hearing and vision. In fact, a recent scientific statement from cardiology professional societies emphasized the need for risk tools relevant for older adults.

Q: What is the importance of including information on functional impairment in the model?

A: The inclusion of functional impairments significantly improved the model’s ability to correctly predict which patients survive and which patients do not. When we look at the individual patient, we see an important change in risk depending on the functional impairments. We can consider two hypothetical patients, with the same age, race and gender, and even identical clinical characteristics — including type of heart attack, kidney function and blood count. If the first patient reports that hearing interferes with activities “a lot,” has fair health status, has slow gait (Timed Up and Go greater than 25 seconds) and reports unintentional weight loss of more than 10 pounds in the past year, the predicted risk for death within 6 months is 22% using the SILVER-AMI model. Conversely, if the second patient reports that hearing interferes with activities “a little,” has good health status, has a Timed Up and Go of 15 seconds or less and denies unintentional weight loss of more than 10 pounds in the past year, the predicted risk for death within 6 months is 5% using the SILVER-AMI model.

PAGE BREAK

Q: Is it feasible to implement this model in hospitals across the United States? What are the challenges of doing so?

A: We recognize that our model includes information about functional impairments, which are not typically assessed as part of routine care for patients hospitalized for heart attack. This is part of the reason we verified that the impairments make an important improvement in the risk model’s performance. Based on our experience performing these assessments in over 3,000 acute MI patients at nearly 100 hospitals across the United States, we estimate that the assessments required for our model should take less than 10 minutes to complete. None of the assessments are protected by copyright, so they are all freely available. And we’ve made our model freely available as well. It is online at silverscore.org, and there is a free app.

Reference:

Dodson JA, et al. Ann Intern Med. 2019;doi:10.7326/M19-097.

Disclosures: Chaudhry reports no relevant financial disclosures. Please see study for all other authors’ relevant financial disclosures.