Inflammatory and Metabolic Predictors of Mortality in Pulmonary Thromboembolism: A Focus on the Triglyceride-Glucose Index and Pan-Immune Inflammation Value
: We aimed to evaluate the importance of metabolic and inflammatory markers, specifically the Triglyceride-Glucose Index (TGI) and pan-immune inflammation value (PIV), in predicting mortality among patients diagnosed with pulmonary thromboembolism (PTE). : A total of 450 patients diagnosed with PTE...
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description | : We aimed to evaluate the importance of metabolic and inflammatory markers, specifically the Triglyceride-Glucose Index (TGI) and pan-immune inflammation value (PIV), in predicting mortality among patients diagnosed with pulmonary thromboembolism (PTE).
: A total of 450 patients diagnosed with PTE between December 2018 and December 2023 were included in his study. The diagnosis of PTE was confirmed by clinical presentation, laboratory tests, and imaging studies such as computed tomography pulmonary angiography (CTPA). Data were obtained from medical records, including demographic information, medical history, laboratory results, and clinical outcomes.
: In terms of age, non-survivors were older on average (66.1 ± 11.8 years) compared to survivors (58.3 ± 12.4 years) (
= 0.03). In terms of gender, 55% of non-survivors and 45% of survivors were male (
= 0.111). Non-survivors had higher BMIs (28.3 ± 5.1) than survivors (25.7 ± 4.5) (
= 0.04). In terms of hypertension, 40% of non-survivors and 30% of survivors had hypertension (
= 0.041). In terms of diabetes, 35% of those who did not survive and 20% of those who survived had diabetes (
= 0.001). In terms of smoking, 25% of non-survivors and 15% of survivors smoke (
= 0.022). In terms of TGI, non-survivors had higher TGI values (12.1 ± 1.5) than survivors (5.9 ± 1.2) (
< 0.001). In terms of PIV, non-survivors had significantly higher PIV (878.2 ± 85.4) than survivors (254.5 ± 61.1) (
< 0.001). The risk factors found to be significantly associated with differentiation in the multiple logistic regression analysis included age, BMI, TGI, and PIV (
= 0.005,
= 0.002,
= 0.013, and 0.022, respectively). As a result, according to ROC analysis for patients who are non-survivors, age, BMI, TGI, and PIV were significant prognostic factors. The cut-off points for these values were >60, >27, >10, and >500, respectively.
: the TGI and PIV are strong markers for predicting mortality in PTE patients. The independent predictive value of age and BMI further demonstrates their role in risk stratification. We think that high TGI values and PIVs reflect underlying metabolic and inflammatory disorders that may contribute to worse outcomes in these patients. |
doi_str_mv | 10.3390/jcm13196008 |
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: A total of 450 patients diagnosed with PTE between December 2018 and December 2023 were included in his study. The diagnosis of PTE was confirmed by clinical presentation, laboratory tests, and imaging studies such as computed tomography pulmonary angiography (CTPA). Data were obtained from medical records, including demographic information, medical history, laboratory results, and clinical outcomes.
: In terms of age, non-survivors were older on average (66.1 ± 11.8 years) compared to survivors (58.3 ± 12.4 years) (
= 0.03). In terms of gender, 55% of non-survivors and 45% of survivors were male (
= 0.111). Non-survivors had higher BMIs (28.3 ± 5.1) than survivors (25.7 ± 4.5) (
= 0.04). In terms of hypertension, 40% of non-survivors and 30% of survivors had hypertension (
= 0.041). In terms of diabetes, 35% of those who did not survive and 20% of those who survived had diabetes (
= 0.001). In terms of smoking, 25% of non-survivors and 15% of survivors smoke (
= 0.022). In terms of TGI, non-survivors had higher TGI values (12.1 ± 1.5) than survivors (5.9 ± 1.2) (
< 0.001). In terms of PIV, non-survivors had significantly higher PIV (878.2 ± 85.4) than survivors (254.5 ± 61.1) (
< 0.001). The risk factors found to be significantly associated with differentiation in the multiple logistic regression analysis included age, BMI, TGI, and PIV (
= 0.005,
= 0.002,
= 0.013, and 0.022, respectively). As a result, according to ROC analysis for patients who are non-survivors, age, BMI, TGI, and PIV were significant prognostic factors. The cut-off points for these values were >60, >27, >10, and >500, respectively.
: the TGI and PIV are strong markers for predicting mortality in PTE patients. The independent predictive value of age and BMI further demonstrates their role in risk stratification. We think that high TGI values and PIVs reflect underlying metabolic and inflammatory disorders that may contribute to worse outcomes in these patients.</description><identifier>ISSN: 2077-0383</identifier><identifier>EISSN: 2077-0383</identifier><identifier>DOI: 10.3390/jcm13196008</identifier><identifier>PMID: 39408068</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Age ; Anticoagulants ; Biological markers ; Blood clots ; Blood sugar monitoring ; Cardiovascular disease ; Catheters ; Chi-square test ; Clinical outcomes ; Complications and side effects ; Diabetes ; Diagnosis ; Glucose ; Hypertension ; Immune system ; Inflammation ; Medical prognosis ; Medical research ; Medicine, Experimental ; Metabolic diseases ; Metabolism ; Mortality ; Neutrophils ; Patient outcomes ; Patients ; Prognosis ; Pulmonary arteries ; Pulmonary embolism ; Regression analysis ; Testing ; Thromboembolism</subject><ispartof>Journal of clinical medicine, 2024-10, Vol.13 (19), p.6008</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 by the authors. 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c365t-a501507f6112c02134f023b7ae49ce04997d1c8ad7405893f55c75a0704f745c3</cites><orcidid>0000-0001-6837-3477</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11477710/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11477710/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27922,27923,53789,53791</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39408068$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bilgin, Murat</creatorcontrib><creatorcontrib>Akkaya, Emre</creatorcontrib><creatorcontrib>Dokuyucu, Recep</creatorcontrib><title>Inflammatory and Metabolic Predictors of Mortality in Pulmonary Thromboembolism: A Focus on the Triglyceride-Glucose Index and Pan-Immune Inflammation Value</title><title>Journal of clinical medicine</title><addtitle>J Clin Med</addtitle><description>: We aimed to evaluate the importance of metabolic and inflammatory markers, specifically the Triglyceride-Glucose Index (TGI) and pan-immune inflammation value (PIV), in predicting mortality among patients diagnosed with pulmonary thromboembolism (PTE).
: A total of 450 patients diagnosed with PTE between December 2018 and December 2023 were included in his study. The diagnosis of PTE was confirmed by clinical presentation, laboratory tests, and imaging studies such as computed tomography pulmonary angiography (CTPA). Data were obtained from medical records, including demographic information, medical history, laboratory results, and clinical outcomes.
: In terms of age, non-survivors were older on average (66.1 ± 11.8 years) compared to survivors (58.3 ± 12.4 years) (
= 0.03). In terms of gender, 55% of non-survivors and 45% of survivors were male (
= 0.111). Non-survivors had higher BMIs (28.3 ± 5.1) than survivors (25.7 ± 4.5) (
= 0.04). In terms of hypertension, 40% of non-survivors and 30% of survivors had hypertension (
= 0.041). In terms of diabetes, 35% of those who did not survive and 20% of those who survived had diabetes (
= 0.001). In terms of smoking, 25% of non-survivors and 15% of survivors smoke (
= 0.022). In terms of TGI, non-survivors had higher TGI values (12.1 ± 1.5) than survivors (5.9 ± 1.2) (
< 0.001). In terms of PIV, non-survivors had significantly higher PIV (878.2 ± 85.4) than survivors (254.5 ± 61.1) (
< 0.001). The risk factors found to be significantly associated with differentiation in the multiple logistic regression analysis included age, BMI, TGI, and PIV (
= 0.005,
= 0.002,
= 0.013, and 0.022, respectively). As a result, according to ROC analysis for patients who are non-survivors, age, BMI, TGI, and PIV were significant prognostic factors. The cut-off points for these values were >60, >27, >10, and >500, respectively.
: the TGI and PIV are strong markers for predicting mortality in PTE patients. The independent predictive value of age and BMI further demonstrates their role in risk stratification. We think that high TGI values and PIVs reflect underlying metabolic and inflammatory disorders that may contribute to worse outcomes in these patients.</description><subject>Age</subject><subject>Anticoagulants</subject><subject>Biological markers</subject><subject>Blood clots</subject><subject>Blood sugar monitoring</subject><subject>Cardiovascular disease</subject><subject>Catheters</subject><subject>Chi-square test</subject><subject>Clinical outcomes</subject><subject>Complications and side effects</subject><subject>Diabetes</subject><subject>Diagnosis</subject><subject>Glucose</subject><subject>Hypertension</subject><subject>Immune system</subject><subject>Inflammation</subject><subject>Medical prognosis</subject><subject>Medical research</subject><subject>Medicine, Experimental</subject><subject>Metabolic diseases</subject><subject>Metabolism</subject><subject>Mortality</subject><subject>Neutrophils</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>Prognosis</subject><subject>Pulmonary arteries</subject><subject>Pulmonary embolism</subject><subject>Regression analysis</subject><subject>Testing</subject><subject>Thromboembolism</subject><issn>2077-0383</issn><issn>2077-0383</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNptkk1vEzEQhlcIRKvSE3dkiQsS2jJee9e7XFBU0RKpFTkErpbjnU0c-aPYu4j8F34sDg0lRdgHWzPP-47HmqJ4SeGCsQ7ebbWjjHYNQPukOK1AiBJYy54e3U-K85S2kFfb8oqK58UJ6zi00LSnxc-5H6xyTo0h7ojyPbnFUa2CNZosIvZG50QiYSC3IY7KmnFHjCeLybrgVZYsNzG4VUC31yT3nszIVdBTlngybpAso1nbncZoeiyv7aRDQjL3Pf74XW2hfDl3bvL74OElJku_Kjvhi-LZoGzC88N5Vny5-ri8_FTefL6eX85uSs2aeixVDbQGMTSUVhoqyvgAFVsJhbzTCLzrRE91q3rBoW47NtS1FrUCAXwQvNbsrPhw73s3rRz2Gv0YlZV30bjcogzKyMcZbzZyHb5LSrkQgkJ2eHNwiOHbhGmUziSN1iqPYUqSUSpANJyLjL7-B92GKfrc355qmpq2ovtLrZVFafwQcmG9N5WzllYNrTmwTF38h8q7R2d08DiYHH8keHsv0DGkFHF4aJKC3A-UPBqoTL86_pcH9s_4sF__gMYA</recordid><startdate>20241009</startdate><enddate>20241009</enddate><creator>Bilgin, Murat</creator><creator>Akkaya, Emre</creator><creator>Dokuyucu, Recep</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-6837-3477</orcidid></search><sort><creationdate>20241009</creationdate><title>Inflammatory and Metabolic Predictors of Mortality in Pulmonary Thromboembolism: A Focus on the Triglyceride-Glucose Index and Pan-Immune Inflammation Value</title><author>Bilgin, Murat ; Akkaya, Emre ; Dokuyucu, Recep</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c365t-a501507f6112c02134f023b7ae49ce04997d1c8ad7405893f55c75a0704f745c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Age</topic><topic>Anticoagulants</topic><topic>Biological markers</topic><topic>Blood clots</topic><topic>Blood sugar monitoring</topic><topic>Cardiovascular disease</topic><topic>Catheters</topic><topic>Chi-square test</topic><topic>Clinical outcomes</topic><topic>Complications and side effects</topic><topic>Diabetes</topic><topic>Diagnosis</topic><topic>Glucose</topic><topic>Hypertension</topic><topic>Immune system</topic><topic>Inflammation</topic><topic>Medical prognosis</topic><topic>Medical research</topic><topic>Medicine, Experimental</topic><topic>Metabolic diseases</topic><topic>Metabolism</topic><topic>Mortality</topic><topic>Neutrophils</topic><topic>Patient outcomes</topic><topic>Patients</topic><topic>Prognosis</topic><topic>Pulmonary arteries</topic><topic>Pulmonary embolism</topic><topic>Regression analysis</topic><topic>Testing</topic><topic>Thromboembolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bilgin, Murat</creatorcontrib><creatorcontrib>Akkaya, Emre</creatorcontrib><creatorcontrib>Dokuyucu, Recep</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of clinical medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bilgin, Murat</au><au>Akkaya, Emre</au><au>Dokuyucu, Recep</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Inflammatory and Metabolic Predictors of Mortality in Pulmonary Thromboembolism: A Focus on the Triglyceride-Glucose Index and Pan-Immune Inflammation Value</atitle><jtitle>Journal of clinical medicine</jtitle><addtitle>J Clin Med</addtitle><date>2024-10-09</date><risdate>2024</risdate><volume>13</volume><issue>19</issue><spage>6008</spage><pages>6008-</pages><issn>2077-0383</issn><eissn>2077-0383</eissn><abstract>: We aimed to evaluate the importance of metabolic and inflammatory markers, specifically the Triglyceride-Glucose Index (TGI) and pan-immune inflammation value (PIV), in predicting mortality among patients diagnosed with pulmonary thromboembolism (PTE).
: A total of 450 patients diagnosed with PTE between December 2018 and December 2023 were included in his study. The diagnosis of PTE was confirmed by clinical presentation, laboratory tests, and imaging studies such as computed tomography pulmonary angiography (CTPA). Data were obtained from medical records, including demographic information, medical history, laboratory results, and clinical outcomes.
: In terms of age, non-survivors were older on average (66.1 ± 11.8 years) compared to survivors (58.3 ± 12.4 years) (
= 0.03). In terms of gender, 55% of non-survivors and 45% of survivors were male (
= 0.111). Non-survivors had higher BMIs (28.3 ± 5.1) than survivors (25.7 ± 4.5) (
= 0.04). In terms of hypertension, 40% of non-survivors and 30% of survivors had hypertension (
= 0.041). In terms of diabetes, 35% of those who did not survive and 20% of those who survived had diabetes (
= 0.001). In terms of smoking, 25% of non-survivors and 15% of survivors smoke (
= 0.022). In terms of TGI, non-survivors had higher TGI values (12.1 ± 1.5) than survivors (5.9 ± 1.2) (
< 0.001). In terms of PIV, non-survivors had significantly higher PIV (878.2 ± 85.4) than survivors (254.5 ± 61.1) (
< 0.001). The risk factors found to be significantly associated with differentiation in the multiple logistic regression analysis included age, BMI, TGI, and PIV (
= 0.005,
= 0.002,
= 0.013, and 0.022, respectively). As a result, according to ROC analysis for patients who are non-survivors, age, BMI, TGI, and PIV were significant prognostic factors. The cut-off points for these values were >60, >27, >10, and >500, respectively.
: the TGI and PIV are strong markers for predicting mortality in PTE patients. The independent predictive value of age and BMI further demonstrates their role in risk stratification. We think that high TGI values and PIVs reflect underlying metabolic and inflammatory disorders that may contribute to worse outcomes in these patients.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>39408068</pmid><doi>10.3390/jcm13196008</doi><orcidid>https://orcid.org/0000-0001-6837-3477</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Age Anticoagulants Biological markers Blood clots Blood sugar monitoring Cardiovascular disease Catheters Chi-square test Clinical outcomes Complications and side effects Diabetes Diagnosis Glucose Hypertension Immune system Inflammation Medical prognosis Medical research Medicine, Experimental Metabolic diseases Metabolism Mortality Neutrophils Patient outcomes Patients Prognosis Pulmonary arteries Pulmonary embolism Regression analysis Testing Thromboembolism |
title | Inflammatory and Metabolic Predictors of Mortality in Pulmonary Thromboembolism: A Focus on the Triglyceride-Glucose Index and Pan-Immune Inflammation Value |
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