A Simple Nomogram for Predicting Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke
The purpose of this study was to develop a prediction model for stroke-associated pneumonia (SAP) based on risk factors for SAP and to suggest nursing interventions to prevent SAP. In addition, a nomogram was developed to enhance its utility in nursing practice. The retrospective cohort study includ...
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| Veröffentlicht in: | Healthcare (Basel) 2023-11, Vol.11 (23), p.3015 |
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| creator | Lee, Youn-Jung Jang, Hee Jung |
| description | The purpose of this study was to develop a prediction model for stroke-associated pneumonia (SAP) based on risk factors for SAP and to suggest nursing interventions to prevent SAP. In addition, a nomogram was developed to enhance its utility in nursing practice. The retrospective cohort study included 551 patients hospitalized for acute ischemic stroke at a university hospital in South Korea. Data were collected through a structured questionnaire and a review of the electronic medical record (EMR). In the development of a predictive model for SAP, multivariate logistic regression analysis showed that independent risk factors for SAP were age ≥ 65 years, National Institute of Health Stroke Scale (NIHSS) score ≥ 7, nasogastric tube feeding, and C-reactive protein (CRP) ≥ 5.0 mg/dL. The logit model was used to construct the SAP prediction nomogram, and the area under the curve (AUC) of the nomogram was 0.94. Furthermore, the slope of the calibration plot was close to the 45-degree line, indicating that the developed nomogram may be useful for predicting SAP. It is necessary to monitor the age, NIHSS score, nasogastric tube feeding status, and CRP level of stroke patients and identify high-risk groups using the developed nomogram to provide active nursing interventions to prevent SAP. |
| doi_str_mv | 10.3390/healthcare11233015 |
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In addition, a nomogram was developed to enhance its utility in nursing practice. The retrospective cohort study included 551 patients hospitalized for acute ischemic stroke at a university hospital in South Korea. Data were collected through a structured questionnaire and a review of the electronic medical record (EMR). In the development of a predictive model for SAP, multivariate logistic regression analysis showed that independent risk factors for SAP were age ≥ 65 years, National Institute of Health Stroke Scale (NIHSS) score ≥ 7, nasogastric tube feeding, and C-reactive protein (CRP) ≥ 5.0 mg/dL. The logit model was used to construct the SAP prediction nomogram, and the area under the curve (AUC) of the nomogram was 0.94. Furthermore, the slope of the calibration plot was close to the 45-degree line, indicating that the developed nomogram may be useful for predicting SAP. It is necessary to monitor the age, NIHSS score, nasogastric tube feeding status, and CRP level of stroke patients and identify high-risk groups using the developed nomogram to provide active nursing interventions to prevent SAP.</description><identifier>ISSN: 2227-9032</identifier><identifier>EISSN: 2227-9032</identifier><identifier>DOI: 10.3390/healthcare11233015</identifier><identifier>PMID: 38063586</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Accuracy ; Bacterial pneumonia ; Brain research ; Cardiovascular disease ; Care and treatment ; Data analysis ; Data collection ; Diabetes ; Diagnosis ; Dysarthria ; Dysphagia ; Hospitalization ; Hospitals ; Ischemia ; Medical laboratories ; Medical records ; Nomograms ; Nursing ; Obesity ; Pneumonia ; Questionnaires ; Regression analysis ; Risk factors ; Sociodemographics ; Stroke ; Stroke (Disease) ; Variables</subject><ispartof>Healthcare (Basel), 2023-11, Vol.11 (23), p.3015</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 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><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c442t-e2062438de0848cf4125b127a7f364f093a947356ad80934c4f239025116a3223</citedby><cites>FETCH-LOGICAL-c442t-e2062438de0848cf4125b127a7f364f093a947356ad80934c4f239025116a3223</cites><orcidid>0009-0003-1672-5479 ; 0000-0002-5764-0020</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38063586$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Youn-Jung</creatorcontrib><creatorcontrib>Jang, Hee Jung</creatorcontrib><title>A Simple Nomogram for Predicting Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke</title><title>Healthcare (Basel)</title><addtitle>Healthcare (Basel)</addtitle><description>The purpose of this study was to develop a prediction model for stroke-associated pneumonia (SAP) based on risk factors for SAP and to suggest nursing interventions to prevent SAP. In addition, a nomogram was developed to enhance its utility in nursing practice. The retrospective cohort study included 551 patients hospitalized for acute ischemic stroke at a university hospital in South Korea. Data were collected through a structured questionnaire and a review of the electronic medical record (EMR). In the development of a predictive model for SAP, multivariate logistic regression analysis showed that independent risk factors for SAP were age ≥ 65 years, National Institute of Health Stroke Scale (NIHSS) score ≥ 7, nasogastric tube feeding, and C-reactive protein (CRP) ≥ 5.0 mg/dL. The logit model was used to construct the SAP prediction nomogram, and the area under the curve (AUC) of the nomogram was 0.94. Furthermore, the slope of the calibration plot was close to the 45-degree line, indicating that the developed nomogram may be useful for predicting SAP. It is necessary to monitor the age, NIHSS score, nasogastric tube feeding status, and CRP level of stroke patients and identify high-risk groups using the developed nomogram to provide active nursing interventions to prevent SAP.</description><subject>Accuracy</subject><subject>Bacterial pneumonia</subject><subject>Brain research</subject><subject>Cardiovascular disease</subject><subject>Care and treatment</subject><subject>Data analysis</subject><subject>Data collection</subject><subject>Diabetes</subject><subject>Diagnosis</subject><subject>Dysarthria</subject><subject>Dysphagia</subject><subject>Hospitalization</subject><subject>Hospitals</subject><subject>Ischemia</subject><subject>Medical laboratories</subject><subject>Medical records</subject><subject>Nomograms</subject><subject>Nursing</subject><subject>Obesity</subject><subject>Pneumonia</subject><subject>Questionnaires</subject><subject>Regression analysis</subject><subject>Risk factors</subject><subject>Sociodemographics</subject><subject>Stroke</subject><subject>Stroke (Disease)</subject><subject>Variables</subject><issn>2227-9032</issn><issn>2227-9032</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkUtr3DAURk1paUKaP9BFEXTTjVNJV7alpQl9BEI7kHYtFPlqRqktTSWZ0H9fDZm-Ky304JzL5X5N85zRCwBFX-_QzGVnTULGOABl3aPmlHM-tIoCf_zb_aQ5z_mO1qUYSOieNicgaQ-d7E8bO5Ibv-xnJB_iErfJLMTFRDYJJ2-LD1tyU1L8gu2Yc7TeFJzIJuC6xOAN8YFsTPEYSib3vuzIaNeC5CrbHS7eHt1nzRNn5oznx_Os-fz2zafL9-31x3dXl-N1a4XgpUVOey5ATkilkNYJxrtbxgczOOiFowqMEgN0vZlkfQgrHK-T4B1jvQHO4ax59VB3n-LXFXPRi88W59kEjGvWvMKqhx5YRV_-hd7FNYXaneZSKZBSAv1Fbc2M2gcXSzL2UFSPw9BJqYZOVeriP1Td02EGMaDz9f8PgT8INsWcEzq9T34x6ZtmVB_C1f-GW6UXx47X2wWnn8qPKOE7RH6eYQ</recordid><startdate>20231122</startdate><enddate>20231122</enddate><creator>Lee, Youn-Jung</creator><creator>Jang, Hee Jung</creator><general>MDPI AG</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7XB</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>KB0</scope><scope>M2O</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0009-0003-1672-5479</orcidid><orcidid>https://orcid.org/0000-0002-5764-0020</orcidid></search><sort><creationdate>20231122</creationdate><title>A Simple Nomogram for Predicting Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke</title><author>Lee, Youn-Jung ; Jang, Hee Jung</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c442t-e2062438de0848cf4125b127a7f364f093a947356ad80934c4f239025116a3223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Accuracy</topic><topic>Bacterial pneumonia</topic><topic>Brain research</topic><topic>Cardiovascular disease</topic><topic>Care and treatment</topic><topic>Data analysis</topic><topic>Data collection</topic><topic>Diabetes</topic><topic>Diagnosis</topic><topic>Dysarthria</topic><topic>Dysphagia</topic><topic>Hospitalization</topic><topic>Hospitals</topic><topic>Ischemia</topic><topic>Medical laboratories</topic><topic>Medical records</topic><topic>Nomograms</topic><topic>Nursing</topic><topic>Obesity</topic><topic>Pneumonia</topic><topic>Questionnaires</topic><topic>Regression analysis</topic><topic>Risk factors</topic><topic>Sociodemographics</topic><topic>Stroke</topic><topic>Stroke (Disease)</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Youn-Jung</creatorcontrib><creatorcontrib>Jang, Hee Jung</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</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>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</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 Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Healthcare (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Youn-Jung</au><au>Jang, Hee Jung</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Simple Nomogram for Predicting Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke</atitle><jtitle>Healthcare (Basel)</jtitle><addtitle>Healthcare (Basel)</addtitle><date>2023-11-22</date><risdate>2023</risdate><volume>11</volume><issue>23</issue><spage>3015</spage><pages>3015-</pages><issn>2227-9032</issn><eissn>2227-9032</eissn><abstract>The purpose of this study was to develop a prediction model for stroke-associated pneumonia (SAP) based on risk factors for SAP and to suggest nursing interventions to prevent SAP. 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| subjects | Accuracy Bacterial pneumonia Brain research Cardiovascular disease Care and treatment Data analysis Data collection Diabetes Diagnosis Dysarthria Dysphagia Hospitalization Hospitals Ischemia Medical laboratories Medical records Nomograms Nursing Obesity Pneumonia Questionnaires Regression analysis Risk factors Sociodemographics Stroke Stroke (Disease) Variables |
| title | A Simple Nomogram for Predicting Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke |
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