Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment
Background: Hyperglycaemia is thought to be connected to worse functional outcomes after ischaemic stroke. However, the association between hyperglycaemia and acute kidney injury (AKI) after endovascular treatment (EVT) remains elusive. The purpose of this study was to investigate the influence of g...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Journal of Clinical Medicine |
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| Online Access: | https://www.mdpi.com/2077-0383/11/13/3865 |
| _version_ | 1797434170661666816 |
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| author | Chengfang Liu Xiaohui Li Zhaohan Xu Yishan Wang Teng Jiang Meng Wang Qiwen Deng Junshan Zhou |
| author_facet | Chengfang Liu Xiaohui Li Zhaohan Xu Yishan Wang Teng Jiang Meng Wang Qiwen Deng Junshan Zhou |
| author_sort | Chengfang Liu |
| collection | DOAJ |
| description | Background: Hyperglycaemia is thought to be connected to worse functional outcomes after ischaemic stroke. However, the association between hyperglycaemia and acute kidney injury (AKI) after endovascular treatment (EVT) remains elusive. The purpose of this study was to investigate the influence of glycaemic on AKI after EVT. Methods: We retrospectively collected the clinical information of patients who underwent EVT from April 2015 to August 2021. Blood glucose after EVT was recorded as acute glycaemia. Chronic glucose levels were estimated by glycosylated haemoglobin (HbA<sub>1c</sub>) using the following formula: chronic glucose levels (mg/dL) = 28.7 × HbA<sub>1c</sub> (%) − 46.7. AKI was defined as an increase in maximum serum creatinine to ≥1.5 baseline. We evaluated the association of AKI with blood glucose. A nomogram was established to predict the risk of AKI, and its diagnostic efficiency was determined by decision curve analysis. Results: We enrolled 717 acute ischaemic stroke patients who underwent EVT. Of them, 205 (28.6%) experienced AKI. Acute glycaemia (OR: 1.007, 95% CI: 1.003–1.011, <i>p</i> < 0.001), the acute/chronic glycaemic ratio (OR: 4.455, 95% CI: 2.237–8.871, <i>p</i> < 0.001) and the difference between acute and chronic glycaemia (Δ<sub>A-C</sub>) (OR: 1.008, 95% CI: 1.004–1.013, <i>p</i> < 0.001) were associated with the incidence of AKI. Additionally, age, atrial fibrillation, ASITN/SIR collateral grading, postoperative mTICI scale, and admission NIHSS were also significantly correlated with AKI. We then created a glycaemia-based nomogram, and its concordance index was 0.743. The net benefit of the nomogram was further confirmed by decision curve analysis. Conclusions: The glycaemia-based nomogram may be used to predict AKI in ischaemic stroke patients receiving EVT. |
| first_indexed | 2024-03-09T10:27:23Z |
| format | Article |
| id | doaj.art-9742364004024da8a0d954c786adab09 |
| institution | Directory Open Access Journal |
| issn | 2077-0383 |
| language | English |
| last_indexed | 2024-03-09T10:27:23Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Clinical Medicine |
| spelling | doaj.art-9742364004024da8a0d954c786adab092023-12-01T21:33:09ZengMDPI AGJournal of Clinical Medicine2077-03832022-07-011113386510.3390/jcm11133865Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular TreatmentChengfang Liu0Xiaohui Li1Zhaohan Xu2Yishan Wang3Teng Jiang4Meng Wang5Qiwen Deng6Junshan Zhou7Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, ChinaDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, ChinaDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, ChinaDepartment of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, ChinaDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, ChinaDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, ChinaDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, ChinaDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, ChinaBackground: Hyperglycaemia is thought to be connected to worse functional outcomes after ischaemic stroke. However, the association between hyperglycaemia and acute kidney injury (AKI) after endovascular treatment (EVT) remains elusive. The purpose of this study was to investigate the influence of glycaemic on AKI after EVT. Methods: We retrospectively collected the clinical information of patients who underwent EVT from April 2015 to August 2021. Blood glucose after EVT was recorded as acute glycaemia. Chronic glucose levels were estimated by glycosylated haemoglobin (HbA<sub>1c</sub>) using the following formula: chronic glucose levels (mg/dL) = 28.7 × HbA<sub>1c</sub> (%) − 46.7. AKI was defined as an increase in maximum serum creatinine to ≥1.5 baseline. We evaluated the association of AKI with blood glucose. A nomogram was established to predict the risk of AKI, and its diagnostic efficiency was determined by decision curve analysis. Results: We enrolled 717 acute ischaemic stroke patients who underwent EVT. Of them, 205 (28.6%) experienced AKI. Acute glycaemia (OR: 1.007, 95% CI: 1.003–1.011, <i>p</i> < 0.001), the acute/chronic glycaemic ratio (OR: 4.455, 95% CI: 2.237–8.871, <i>p</i> < 0.001) and the difference between acute and chronic glycaemia (Δ<sub>A-C</sub>) (OR: 1.008, 95% CI: 1.004–1.013, <i>p</i> < 0.001) were associated with the incidence of AKI. Additionally, age, atrial fibrillation, ASITN/SIR collateral grading, postoperative mTICI scale, and admission NIHSS were also significantly correlated with AKI. We then created a glycaemia-based nomogram, and its concordance index was 0.743. The net benefit of the nomogram was further confirmed by decision curve analysis. Conclusions: The glycaemia-based nomogram may be used to predict AKI in ischaemic stroke patients receiving EVT.https://www.mdpi.com/2077-0383/11/13/3865acute kidney injuryendovascular treatmentglycaemianomogramischaemic stroke |
| spellingShingle | Chengfang Liu Xiaohui Li Zhaohan Xu Yishan Wang Teng Jiang Meng Wang Qiwen Deng Junshan Zhou Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment Journal of Clinical Medicine acute kidney injury endovascular treatment glycaemia nomogram ischaemic stroke |
| title | Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment |
| title_full | Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment |
| title_fullStr | Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment |
| title_full_unstemmed | Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment |
| title_short | Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment |
| title_sort | construction of a glycaemia based signature for predicting acute kidney injury in ischaemic stroke patients after endovascular treatment |
| topic | acute kidney injury endovascular treatment glycaemia nomogram ischaemic stroke |
| url | https://www.mdpi.com/2077-0383/11/13/3865 |
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