CORRECTION article

Front. Aging Neurosci., 08 December 2022

Sec. Neuroinflammation and Neuropathy

Volume 14 - 2022 | https://doi.org/10.3389/fnagi.2022.1101574

Corrigendum: Systemic-immune-inflammation index as a promising biomarker for predicting perioperative ischemic stroke in older patients who underwent non-cardiac surgery

  • 1. Anesthesia and Operation Center, The First Medical Center, Chinese PLA General Hospital, Beijing, China

  • 2. Department of Neurology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou Medical University, Xuzhou, China

  • 3. Department of Pain Medicine, The First Medical Center, Chinese PLA General Hospital, Beijing, China

In the original article, there was a mistake in Figure 1 as published. “ASA physical status V” should be “ASA physical status ≥ IV.” In addition the corresponding n number was give as 391, but should be 1,091. In addition, the corresponding n number for “Missing data for any confounder” was 3,144 but should be 2,444. The revised Figure 1 appears below.

Figure 1

There was also an error in Materials and methods, “Inclusion and exclusion criteria,” Paragraph 1. “Patients who presented with an American Society of Anesthesiologists (ASA) classification of V” should be “Patients who presented with an American Society of Anesthesiologists (ASA) classification of ≥IV.” The corrected paragraph appears below:

“Patients who underwent non-cardiac surgery between January 2008 and August 2019 at Chinese PLA General Hospital were initially screened from a perioperative retrospective database. The inclusion criteria were as follows: (1) aged 65 yr or older; (2) underwent non-cardiac surgery; (3) received general anesthesia; and (4) were with duration of surgery > 60 min. Patients who presented with an American Society of Anesthesiologists (ASA) classification of ≥IV, were performed under regional anesthesia, or had missing clinical data were excluded. Among patients who underwent multiple surgeries during the study period, only the first eligible surgery was considered. A flow diagram of the patient selection process is displayed in Figure 1.” In the original article, there was also a mistake in the Abstract, “Conclusion” as published. The Abstract conclusion stated, “after non-cardiac surgery in elderly older patients.” This should be “after non-cardiac surgery in older patients.” The corrected paragraph appears below:

Conclusion: Preoperative SII, which includes neutrophil, platelet, and lymphocyte counts obtained from routine blood analysis, was a potential prognostic biomarker for predicting perioperative ischemic stroke after non-cardiac surgery in older patients. An elevated SII, based on an optimal cut-off value of 583, was an independent risk factor for perioperative ischemic stroke.”

In the original article, there was also an error in Table 1 and Supplementary Tables 2–4. The covariates previously stated “Class III and IV” and “Arterial fibrillation.” The corrected covariates are “Class III” and “Atrial fibrillation or VHD.” The corrected Table 1 appears below. The corrected Supplementary Tables 2–4 appear in the Supplementary Material of the original article.

Table 1

CharacteristicUnadjusted sample
(n = 40,670)
PSM adjusted (1:1)
(n = 21,652)
SII < 583SII ≥583P-valueSMDSII < 583SII ≥583P-valueSMD
(n = 29,060)(n = 11,610)(n = 10,826)(n = 10,826)
Demographics
Age, y70.0 (67.0,73.0)70.0 (67.0,75.0)0.1260.15270.0 (67.0,74.0)70.0 (67.0,74.0)0.5560.004
Female (%)13651 (47.0)4683 (40.3)< 0.0010.1344458 (41.2)4427 (40.9)0.6790.006
BMI, kg/m224.5 (22.3,26.9)23.7 (21.5,26.0)0.0890.23324.0 (21.6,26.4)23.8 (21.5,26.0)0.1360.097
ASA classification (%)
Class I741 (2.5)234 (2.0)< 0.0010.197261 (2.4)230 (2.1)0.3560.022
Class II22885 (78.8)8255 (71.1)7826 (72.3)7793 (72.0)
Class III5434 (18.7)3121 (26.9)2739 (25.3)2803 (25.9)
Previous medical history
Hypertension (%)10874 (37.4)4685 (40.4)< 0.0010.0604211 (38.9)4360 (40.3)0.2570.021
Diabetes mellitus (%)6096 (21.0)2756 (23.7)< 0.0010.0662436 (22.5)2554 (23.6)0.1780.076
Prior ischemic stroke (%)1552 (5.3)847 (7.3)< 0.0010.080682 (6.3)765 (7.1)0.2280.068
Coronary heart disease (%)2879 (9.9)1231 (10.6)0.0370.0231070 (9.9)1146(10.6)0.0930.023
Atrial fibrillation or VHD (%)454 (1.6)202 (1.7)0.2150.014165 (1.5)180 (1.7)0.4470.011
Peripheral vascular disease (%)1996 (6.9)892 (7.7)0.0040.031811 (7.5)802 (7.4)0.8360.003
Renal dysfunction (%)*338 (1.2)234 (2.0)< 0.0010.068191 (1.8)205 (1.9)0.4560.047
β-blockers medication (%)2051 (7.1)999 (8.6)< 0.0010.058869 (8.2)931 (8.6)0.1670.065
Aspirin medication (%)2553 (8.8)1174 (10.1)< 0.0010.0451024 (9.5)1086 (10.0)0.2930.043
Preoperative laboratory data
Hemoglobin, g/L132.0 (122.0,142.0)125.0 (111.0,138.0)< 0.0010.437128.0 (114.0,140.0)127.0 (113.0,139.0)0.1560.083
Albumin, g/L40.3 (38.1,42.5)40.5 (38.2,43.0)0.2230.48138.9 (36.2,41.4)38.8 (36.0,41.7)0.8370.005
Total bilirubin, μmol/L10.9 (8.4,14.2)10.6 (7.8,15.6)< 0.0010.29110.7 (8.3,14.6)10.6 (7.7,14.9)0.2020.093
Prothrombin time, s13.1 (12.6,13.6)13.2 (12.7,13.9)0.1230.17613.2 (12.7,13.8)13.2 (12.7,13.8)0.6000.028
Surgical and anesthetic factors
Preoperative MAP, mmHg95.7 (88.7,103.0)95.0 (87.3,102.3)0.0980.07095.0 (87.3,102.3)95.0 (88.0,102.7)0.1690.024
Surgical procedures (%)
Trauma surgery433 (1.5)602 (5.2)< 0.0010.352404 (3.7)353 (3.3)
Spine2751 (9.5)715 (6.2)758 (7.0)711 (6.6)0.2580.041
Intra-abdominal surgery9652 (33.2)5159 (44.4)4688 (43.3)4690 (43.3)
Joint arthroplasty3726 (12.8)1031 (8.9)987 (9.1)1027 (9.5)
Urologic or gynecologic3972 (13.7)1219 (10.5)1138 (10.6)1209 (11.1)
Neurosurgery1380 (4.7)523 (4.5)516 (4.8)515 (4.8)
Thoracic or vascular3362 (11.6)1225 (10.5)1172 (10.8)1199 (11.1)
Other (plastic surgery, etc.)3784 (13.0)1136 (9.8)1163 (10.7)1122 (10.3)
Duration of procedures, min155.0 (110.0,215.0)170.0 (120.0.0,235.0)< 0.0010.162168.0 (118.0,231.0)170.0 (120.0,235.0)0.3560.076
Estimated blood loss, mL100.0 (50.0,200.0)150.0 (50.0,300.0)< 0.0010.083140.0 (90.0,280.0)145.7 (100.0,300.0)0.1670.096
MAP ≤ 65 mmHg (%)12600 (43.4)5749 (49.5)< 0.0010.0705125 (47.3)5285 (48.8)0.2340.072
Crystalloid infusion, ml/kg/h8.6 (6.5,11.4)8.9 (6.6,11.8)0.1670.0738.8 (6.6,11.7)8.8 (6.5,11.7)0.8450.006
Colloid infusion, ml/kg/h2.9 (1.3,4.3)3.1 (1.8,4.5)< 0.0010.1233.0 (1.6,4.4)3.0 (1.8,4.5)0.1110.066
Blood transfusion (%)3902 (13.4)2322 (20.0)< 0.0010.1771998 (18.5)2082 (19.2)0.1890.052
NSAIDs (%)20502 (70.6)8366 (72.1)0.0030.0337667 (70.8)7709 (71.2)0.5390.009
Glucocorticoid (%)23749 (81.7)9557 (82.3)0.1650.0158905 (82.3)8932 (82.5)0.6430.007
Opioid dose, mg120.0 (9.0,150.0)135.0 (105.0,165.0)< 0.0010.081135.0 (100.0,150.0)135.0 (105.0,165.0)0.2560.047
Volatile anesthetic (%)27098 (93.2)10819 (93.2)0.8400.00210097 (93.3)10110 (93.4)0.7440.005
Preoperative NLR
< 327796 (95.7)4098 (35.3)< 0.0011.64310215 (94.4)3951 (36.5)< 0.0011.583
≥31264 (4.3)7512 (64.7)611 (5.6)6875 (63.5)
Preoperative PLR
< 11918897 (65.0)959 (8.3)< 0.0011.4586821 (63.0)914 (8.4)< 0.0011.385
≥11910163 (35.0)10651 (91.7)4005 (37.0)9912 (91.6)
Perioperative ischemic stroke (%)126 (0.434)111 (0.956)< 0.0010.85649 (0.453)107 (0.988)< 0.0010.939

Baseline characteristics of unadjusted sample and propensity score-matched sample (patients from 2008–2019).

The data are presented as the median (inter-quartile range), mean (standard deviation) or n (%).

*

Creatinine > 177 μm/l.

Variables included in the propensity score.

Including those prescribed intraoperatively and postoperatively (until 7 days after surgery).

SII, systemic-immune-inflammation index; PSM, propensity score matching; SMD, standardized mean difference; BMI, body mass index; ASA, American Society of Anesthesiologists; VHD, valvular heart disease; MAP, mean arterial pressure; NSAIDs, non-steroid anti-inflammatory drugs; NLR, neutrophil-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio.

In the original article there was also an error in Materials and methods, “Clinical outcome.” The definition of perioperative ischemic stroke was incomplete. The following information was not provided: “Diagnoses of stroke are confirmed by a combination of neuroimaging and clinical evidence of cerebrovascular ischemia during hospital stay.” The corrected paragraph appears below:

“The primary outcome of interest was perioperative ischemic stroke, defined as an episode of neurological dysfunction, such as motor, sensory, or cognitive dysfunction, caused by focal cerebral, spinal, or retinal infarction within 30 postoperative days (Sacco et al., 2013). Diagnoses of stroke are confirmed by a combination of neuroimaging and clinical evidence of cerebrovascular ischemia during hospital stay. In our study, perioperative ischemic stroke patients were identified if discharge records included at least 1 ICD-9-CM/ICD-10-CM diagnosis code for stroke (Supplementary Table 1).”

We apologize for these errors and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Statements

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

  • 1

    SaccoR. L.KasnerS. E.BroderickJ. P.CaplanL. R.ConnorsJ. J.CulebrasA.et al. (2013). An updated definition of stroke for the 21st century: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke44, 20642089. 10.1161/STR.0b013e318296aeca

Summary

Keywords

systemic-immune-inflammation index (SII), perioperative stroke, postoperative complication, inflammation, older patients, biomarker

Citation

Zhang F, Niu M, Wang L, Liu Y, Shi L, Cao J, Mi W, Ma Y and Liu J (2022) Corrigendum: Systemic-immune-inflammation index as a promising biomarker for predicting perioperative ischemic stroke in older patients who underwent non-cardiac surgery. Front. Aging Neurosci. 14:1101574. doi: 10.3389/fnagi.2022.1101574

Received

18 November 2022

Accepted

28 November 2022

Published

08 December 2022

Volume

14 - 2022

Edited and reviewed by

Yujie Chen, Army Medical University, China

Updates

Copyright

*Correspondence: Yulong Ma Jing Liu

†These authors have contributed equally to this work

This article was submitted to Neuroinflammation and Neuropathy, a section of the journal Frontiers in Aging Neuroscience

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Outline

Figures

Cite article

Copy to clipboard


Export citation file


Share article

Article metrics