<?xml version="1.0" encoding="utf-8"?>
<journal>
<title>Journal of Community  Health Research</title>
<title_fa>مجله تحقیقات سلامت</title_fa>
<short_title>JCHR</short_title>
<subject>Medical Sciences</subject>
<web_url>http://jhr.ssu.ac.ir</web_url>
<journal_hbi_system_id>1</journal_hbi_system_id>
<journal_hbi_system_user>admin</journal_hbi_system_user>
<journal_id_issn>2322-5688</journal_id_issn>
<journal_id_issn_online>2345-2609</journal_id_issn_online>
<journal_id_pii></journal_id_pii>
<journal_id_doi></journal_id_doi>
<journal_id_iranmedex></journal_id_iranmedex>
<journal_id_magiran></journal_id_magiran>
<journal_id_sid>27545</journal_id_sid>
<journal_id_nlai></journal_id_nlai>
<journal_id_science>12727</journal_id_science>
<language>en</language>
<pubdate>
	<type>jalali</type>
	<year>1403</year>
	<month>10</month>
	<day>1</day>
</pubdate>
<pubdate>
	<type>gregorian</type>
	<year>2025</year>
	<month>1</month>
	<day>1</day>
</pubdate>
<volume>14</volume>
<number>1</number>
<publish_type>online</publish_type>
<publish_edition>1</publish_edition>
<article_type>fulltext</article_type>
<articleset>
	<article>


	<language>en</language>
	<article_id_doi></article_id_doi>
	<title_fa></title_fa>
	<title>Tutorial on Comorbidity Indices in Medical Research</title>
	<subject_fa>اپیدمیولوژی</subject_fa>
	<subject>Epidemiology</subject>
	<content_type_fa>مروری</content_type_fa>
	<content_type>Review</content_type>
	<abstract_fa>&lt;br&gt;
&amp;nbsp;</abstract_fa>
	<abstract>&lt;div style=&quot;text-align: justify;&quot;&gt;&lt;span style=&quot;font-size:12px;&quot;&gt;&lt;span style=&quot;font-family:Times New Roman;&quot;&gt;&lt;span style=&quot;line-height:150%&quot;&gt;&lt;b&gt;&lt;span style=&quot;line-height:150%&quot;&gt;Background:&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;line-height:150%&quot;&gt; Comorbidity indices, such as Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Measure (ECM), are essential tools for assessing the influence of comorbid health conditions on patient outcomes. This study aims to review comorbidity indices by assigning weighted scores to a spectrum of comorbidities; these instruments play a critical role in predicting mortality rates and evaluating healthcare resource utilization.&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;line-height:150%&quot;&gt;&lt;b&gt;&lt;span style=&quot;line-height:150%&quot;&gt;Methods:&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;line-height:150%&quot;&gt; In this narrative review study, we reviewed all comorbidity indices and important points were mentioned.&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;line-height:150%&quot;&gt;&lt;b&gt;&lt;span style=&quot;line-height:150%&quot;&gt;Results:&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;line-height:150%&quot;&gt; CCIand ECIhave proven to be highly effective tools for predicting mortality and healthcare outcomes across a wide range of patient populations. This review examines four comorbidity indices: CCI, ECI, Acute Myeloid Leukemia (AML), and the Chronic Disease Index (CDI).&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;line-height:150%&quot;&gt;&lt;b&gt;&lt;span style=&quot;line-height:150%&quot;&gt;Conclusion:&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;line-height:150%&quot;&gt; Among four types, CCI and ECM were the most applied, and the researcher should know different types of comorbidity indices to use in research. &lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;br&gt;
&amp;nbsp;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;</abstract>
	<keyword_fa></keyword_fa>
	<keyword>CCI (Comorbidity by Charlson Index), ECI (Elixhauser comorbidity index, AML (Acute myeloid leukemia), CDI (Chronic disease index), Indices, Research</keyword>
	<start_page>134</start_page>
	<end_page>139</end_page>
	<web_url>http://jhr.ssu.ac.ir/browse.php?a_code=A-10-1445-5&amp;slc_lang=en&amp;sid=1</web_url>


<author_list>
	<author>
	<first_name>Muhammad</first_name>
	<middle_name></middle_name>
	<last_name>Ajmal Dina</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>ajmaljhl@gmail.com</email>
	<code></code>
	<orcid>0000-0003-2034-5084</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Farzan</first_name>
	<middle_name></middle_name>
	<last_name>Madidadizadeh</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>statlearningeasy@gmail.com</email>
	<code></code>
	<orcid>0000-0002-5757-182X</orcid>
	<coreauthor>Yes
</coreauthor>
	<affiliation>Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Anam</first_name>
	<middle_name></middle_name>
	<last_name>Arshed</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>anamarshed574@gmail.com</email>
	<code></code>
	<orcid>0000-0009-4907-8814</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Rahbar Medical and Dental College, Lahore Pakistan</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


</author_list>


	</article>
</articleset>
</journal>
