The Possible Role of PM2.5 Chronic Exposure on 5-Year Survival in Patients with Left Ventricular Dysfunction Following Coronary Artery Bypass Grafting
Abstract
1. Introduction
2. Materials and Methods
2.1. Air Pollution Exposure Methodology
2.2. Statistical Analysis
2.3. Bioethics Committee
3. Results
3.1. Logistic Regression Analysis
3.2. Group 1
3.3. Group 2
3.4. Group 3
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Rajagopalan, S.; Al-Kindi, S.G.; Brook, R.D. Air Pollution and Cardiovascular Disease: JACC State-of-the-Art Review. J. Am. Coll. Cardiol. 2018, 72, 2054–2070. [Google Scholar] [CrossRef]
- Liu, J.; Varghese, B.M.; Hansen, A.; Zhang, Y.; Driscoll, T.; Morgan, G.; Dear, K.; Gourley, M.; Capon, A.; Bi, P. Heat exposure and cardiovascular health outcomes: A systematic review and meta-analysis. Lancet Planet Health 2022, 6, e484–e495. [Google Scholar] [CrossRef]
- Urbanowicz, T.; Skotak, K.; Olasińska-Wiśniewska, A.; Filipiak, K.J.; Bratkowski, J.; Wyrwa, M.; Sikora, J.; Tyburski, P.; Krasińska, B.; Krasiński, Z.; et al. Long-Term Exposure to PM10 Air Pollution Exaggerates Progression of Coronary Artery Disease. Atmosphere 2024, 15, 216. [Google Scholar] [CrossRef]
- Urbanowicz, T.K.; Skotak, K.; Lesiak, M.; Olasińska-Wiśniewska, A.; Filipiak, K.J.; Bratkowski, J.; Szczepański, K.; Grodecki, K.; Tykarski, A.; Jemielity, M. Coronary artery culprit lesions progression and ambient temperature exposure—Personalised analysis. Postępy Kardiol. Interwencyjnej 2024, 20, 139–147. [Google Scholar] [CrossRef]
- Bharmal, M.; Kern, M.J.; Kumar, G.; Seto, A.H. Physiologic Lesion Assessment to Optimize Multivessel Disease. Curr. Cardiol. Rep. 2022, 24, 541–550. [Google Scholar] [CrossRef]
- Granger, C.B.; Krychtiuk, K.A.; Gersh, B.J. Personalizing Choice of CABG vs. PCI for Multivessel Disease: Predictive Model Falls Short. J. Am. Coll. Cardiol. 2022, 79, 1474–1476. [Google Scholar] [CrossRef] [PubMed]
- Formica, F.; Gallingani, A.; Tuttolomondo, D.; Hernandez-Vaquero, D.; Singh, G.; Pattuzzi, C.; Maestri, F.; Niccoli, G.; Ceccato, E.; Lorusso, R.; et al. Long-Term Outcomes Comparison between Surgical and Percutaneous Coronary Revascularization in Patients with Multivessel Coronary Disease or Left Main Disease: A Systematic Review and Study Level Meta-Analysis of Randomized Trials. Curr. Probl. Cardiol. 2023, 48, 101699. [Google Scholar] [CrossRef] [PubMed]
- Quin, J.A.; Wagner, T.H.; Hattler, B.; Carr, B.M.; Collins, J.; Almassi, G.H.; Grover, F.L.; Shroyer, A.L. Ten-Year Outcomes of Off-Pump vs. On-Pump Coronary Artery Bypass Grafting in the Department of Veterans Affairs: A Randomized Clinical Trial. JAMA Surg. 2022, 157, 303–310. [Google Scholar]
- Dominici, C.; Salsano, A.; Nenna, A.; Spadaccio, C.; Mariscalco, G.; Santini, F.; Chello, M. On-pump beating-heart coronary artery bypass grafting in high-risk patients: A systematic review and meta-analysis. J. Card. Surg. 2020, 35, 1958–1978. [Google Scholar] [CrossRef] [PubMed]
- Farina, P.; Gaudino, M.; Angelini, G.D. Off-pump coronary artery bypass surgery: The long and winding road. Int. J. Cardiol. 2019, 279, 51–55. [Google Scholar] [CrossRef] [PubMed]
- Aksut, B.; Starling, R.; Kapadia, S. Stable coronary artery disease and left ventricular dysfunction: The role of revascularization. Catheter. Cardiovasc. Interv. 2017, 90, 777–783. [Google Scholar] [CrossRef] [PubMed]
- Kosmala, W.; Marwick, T.H. Asymptomatic Left Ventricular Diastolic Dysfunction: Predicting Progression to Symptomatic Heart Failure. JACC Cardiovasc. Imaging 2020, 13, 215–227. [Google Scholar] [CrossRef] [PubMed]
- Zuo, B.; Fan, X.; Xu, D.; Zhao, L.; Zhang, B.; Li, X. Deciphering the mitochondria-inflammation axis: Insights and therapeutic strategies for heart failure. Int. Immunopharmacol. 2024, 139, 112697. [Google Scholar] [CrossRef] [PubMed]
- Lanas, F.; Saavedra, N.; Saavedra, K.; Hevia, M.; Seron, P.; Salazar, L.A. Effect of intermediate-term firewood smoke air pollution on cardiometabolic risk factors and inflammatory markers. Front. Cardiovasc. Med. 2023, 10, 1252542. [Google Scholar] [CrossRef] [PubMed]
- Urbanowicz, T.; Skotak, K.; Filipiak, K.J.; Olasińska-Wiśniewska, A.; Szczepański, K.; Wyrwa, M.; Sikora, J.; Tykarski, A.; Jemielity, M. Long-Term Exposure of Nitrogen Oxides Air Pollution (NO2) Impact for Coronary Artery Lesion Progression-Pilot Study. J. Pers. Med. 2023, 13, 1376. [Google Scholar] [CrossRef]
- Available online: https://www.kobize.pl/en/article/national-database-on-greenhouse-gases-and-other-substances-emissions/id/1232/general-information (accessed on 27 March 2024).
- European Air Quality, Copernicus, Atmosphere Monitoring Service. Available online: https://www.regional-evaluation.atmosphere.copernicus.eu/ (accessed on 27 March 2024).
- Braunwald, E. Air pollution: Challenges and opportunities for cardiology. Eur. Heart J. 2023, 44, 1679–1681. [Google Scholar] [CrossRef]
- US Preventive Services Task Force; Mangione, C.M.; Barry, M.J.; Nicholson, W.K.; Cabana, M.; Chelmow, D.; Coker, T.R.; Davis, E.M.; Donahue, K.E.; Jaén, C.R.; et al. Statin Use for the Primary Prevention of Cardiovascular Disease in Adults: US Preventive Services Task Force Recommendation Statement. JAMA 2022, 328, 746–753. [Google Scholar] [CrossRef]
- Wang, L.; Cheng, C.K.; Yi, M.; Lui, K.O.; Huang, Y. Targeting endothelial dysfunction and inflammation. J. Mol. Cell Cardiol. 2022, 168, 58–67. [Google Scholar] [CrossRef]
- Xiang, Q.; Tian, F.; Xu, J.; Du, X.; Zhang, S.; Liu, L. New insight into dyslipidemia-induced cellular senescence in atherosclerosis. Biol. Rev. Camb. Philos Soc. 2022, 97, 1844–1867. [Google Scholar] [CrossRef]
- Prasad, K. Current Status of Primary, Secondary, and Tertiary Prevention of Coronary Artery Disease. Int. J. Angiol. 2021, 30, 177–186. [Google Scholar] [CrossRef]
- Writing Committee; Lloyd-Jones, D.M.; Morris, P.B.; Ballantyne, C.M.; Birtcher, K.K.; Covington, A.M.; DePalma, S.M.; Minissian, M.B.; Orringer, C.E.; Smith, S.C., Jr.; et al. 2022 ACC Expert Consensus Decision Pathway on the Role of Nonstatin Therapies for LDL-Cholesterol Lowering in the Management of Atherosclerotic Cardiovascular Disease Risk: A Report of the American College of Cardiology Solution Set Oversight Committee. J. Am. Coll. Cardiol. 2022, 80, 1366–1418. [Google Scholar]
- Urbanowicz, T.K.; Olasińska-Wiśniewska, A.; Michalak, M.; Gąsecka, A.; Rodzki, M.; Perek, B.; Jemielity, M. Cardioprotective Effect of Low Level of LDL Cholesterol on Perioperative Myocardial Injury in Off-Pump Coronary Artery Bypass Grafting. Medicina 2021, 57, 875. [Google Scholar] [CrossRef]
- Lim, K.; Wong, C.H.M.; Lee, A.L.Y.; Fujikawa, T.; Wong, R.H.L. Influence of cholesterol level on long-term survival and cardiac events after surgical coronary revascularization. JTCVS Open 2022, 10, 195–203. [Google Scholar] [CrossRef]
- Hanna, A.; Frangogiannis, N.G. Inflammatory Cytokines and Chemokines as Therapeutic Targets in Heart Failure. Cardiovasc. Drugs Ther. 2020, 34, 849–863. [Google Scholar] [CrossRef]
- Urbanowicz, T.; Michalak, M.; Al-Imam, A.; Olasińska-Wiśniewska, A.; Rodzki, M.; Witkowska, A.; Haneya, A.; Buczkowski, P.; Perek, B.; Jemielity, M. The Significance of Systemic Immune-Inflammatory Index for Mortality Prediction in Diabetic Patients Treated with Off-Pump Coronary Artery Bypass Surgery. Diagnostics 2022, 12, 634. [Google Scholar] [CrossRef]
- Abu Khadija, H.; Gandelman, G.; Ayyad, O.; Poles, L.; Jonas, M.; Paz, O.; Goland, S.; Shimoni, S.; Meledin, V.; George, J.; et al. Comparative Analysis of the Kinetic Behavior of Systemic Inflammatory Markers in Patients with Depressed versus Preserved Left Ventricular Function Undergoing Transcatheter Aortic Valve Implantation. J. Clin. Med. 2021, 10, 4148. [Google Scholar] [CrossRef]
- Ridker, P.M.; Everett, B.M.; Thuren, T.; MacFadyen, J.G.; Chang, W.H.; Ballantyne, C.; Fonseca, F.; Nicolau, J.; Koenig, W.; Anker, S.D.; et al. Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease. N. Engl. J. Med. 2017, 377, 1119–1131. [Google Scholar] [CrossRef]
- Goossens, J.; Jonckheere, A.C.; Seys, S.F.; Dilissen, E.; Decaesteker, T.; Goossens, C.; Peers, K.; Vanbelle, V.; Stappers, J.; Aertgeerts, S.; et al. Activation of epithelial and inflammatory pathways in adolescent elite athletes exposed to intense exercise and air pollution. Thorax 2023, 78, 775–783. [Google Scholar] [CrossRef]
- Marchini, T. Redox and inflammatory mechanisms linking air pollution particulate matter with cardiometabolic derangements. Free Radic. Biol. Med. 2023, 209, 320–341. [Google Scholar] [CrossRef]
- Su, R.; Jin, X.; Li, H.; Huang, L.; Li, Z. The mechanisms of PM2.5 and its main components penetrate into HUVEC cells and effects on cell organelles. Chemosphere 2020, 241, 125127. [Google Scholar] [CrossRef]
- Xu, Z.; Xu, X.; Zhong, M.; Hotchkiss, I.P.; Lewandowski, R.P.; Wagner, J.G.; Bramble, L.A.; Yang, Y.; Wang, A.; Harkema, J.R.; et al. Ambient particulate air pollution induces oxidative stress and alterations of mitochondria and gene expression in brown and white adipose tissues. Part. Fibre Toxicol. 2011, 8, 20–34. [Google Scholar] [CrossRef]
- Vieira, J.L.; Guimaraes, G.V.; de Andre, P.A.; Cruz, F.D.; Saldiva, P.H.; Bocchi, E.A. Respiratory Filter Reduces the Cardiovascular Effects Associated with Diesel Exhaust Exposure: A Randomized, Prospective, Double-Blind, Controlled Study of Heart Failure: The FILTER-HF Trial. JACC Heart Fail. 2016, 4, 55–64. [Google Scholar] [CrossRef]
- Eze, U.U.; Eke, I.G.; Anakwue, R.C.; Oguejiofor, C.F.; Onyejekwe, O.B.; Udeani, I.J.; Onunze, C.J.; Obed, U.J.; Eze, A.A.; Anaga, A.O.; et al. Effects of Controlled Generator Fume Emissions on the Levels of Troponin I, C-Reactive Protein and Oxidative Stress Markers in Dogs: Exploring Air Pollution-Induced Cardiovascular Disease in a Low-Resource Country. Cardiovasc. Toxicol. 2021, 21, 1019–1032. [Google Scholar] [CrossRef]
- Chaulin, A.M.; Sergeev, A.K. The Role of Fine Particles (PM 2.5) in the Genesis of Atherosclerosis and Myocardial Damage: Emphasis on Clinical and Epidemiological Data, and Pathophysiological Mechanisms. Cardiol. Res. 2022, 13, 268–282. [Google Scholar] [CrossRef]
- Liu, Y.; Yan, M. Trends in all causes and cause specific mortality attributable to ambient particulate matter pollution in China from 1990 to 2019: A secondary data analysis study. PLoS ONE 2023, 18, e0291262. [Google Scholar] [CrossRef]
- Krittanawong, C.; Qadeer, Y.K.; Hayes, R.B.; Wang, Z.; Thurston, G.D.; Virani, S.; Lavie, C.J. PM2.5 and cardiovascular diseases: State-of-the-Art review. Int. J. Cardiol. Cardiovasc. Risk Prev. 2023, 19, 200217. [Google Scholar] [CrossRef]
Parameters | Group 1 | Group 2 | Group 3 | p | p | p |
---|---|---|---|---|---|---|
LVEF ≥ 50% | LVEF 41–49% | LVEF ≤ 40% | Group 1 vs. Group 2 | Group 1 vs. Group 3 | Group 2 vs. Group 3 | |
n = 169 | n = 61 | n = 53 | ||||
Demographical | ||||||
Age (years) (median (Q1–Q3) | 64 (60–72) | 64 (58–69) | 64 (59–68) | 0.322 | 0.186 | 0.795 |
Sex (male (%)) | 142 (84) | 52 (85) | 49 (92) | 0.627 | 0.124 | 0.324 |
BMI (median (Q1–Q3) | 28.4 (26.6–30.9) | 28.4 (26.3–31.0) | 28.7 (26.6–31.5) | 0.624 | 0.74 | 0.532 |
Co-morbidities | ||||||
Arterial hypertension (n, %) | 128 (76) | 49 (80) | 45 (85) | 0.349 | 0 | 0.302 |
Dyslipidemia (n, %) | 89 (53) | 30 (49) | 30 (57) | 0.724 | 0.457 | 0.639 |
Diabetes mellitus (n, %) | 57 (34) | 21 (34) | 19 (36) | 0.859 | 0.778 | 0.928 |
PAD (n, %) | 18 (11) | 5 (8) | 4 (8) | 0.61 | 0.512 | 0.883 |
CAD diagnosis: | ||||||
Left main disease (n, %) | 51 (30) | 19 (31) | 14 (26) | 0.873 | 0.73 | 0.68 |
Two-vessel disease (n, %) | 49 (29) | 18 (30) | 14 26) | 1 | 0.862 | 0.835 |
Three-vessel disease (n, %) | 69 (41) | 24 (39) | 25 (47) | 0.88 | 0.43 | 0.451 |
Parameters | Group 1 | Group 2 | Group 3 | p | p | p |
---|---|---|---|---|---|---|
LVEF ≥ 50% | LVEF 41–49% | LVEF ≤ 40% | Group 1 vs. Group 2 | Group 1 vs. Group 3 | Group 2 vs. Group 3 | |
n = 169 | n = 61 | n = 53 | ||||
Preoperative laboratory results: | ||||||
WBC (×109/L) (median (Q1–Q3)) | 7.70 (6.47–8.93) | 7.84 (6.41–8.83) | 7.44 (6.59–8.51) | 0.612 | 0.738 | 0.716 |
Hb (mmol/L) (median (Q1–Q3)) | 8.8 (8.2–9.3) | 8.7 (8.2–9.15) | 8.90 (8.40–9.30) | 0.972 | 0.699 | 0.416 |
Plt (×109/L) (median (Q1–Q3)) | 219 (187–259) | 225 (188–262) | 222 (182–263) | 0.896 | 0.961 | 0.863 |
Creatinine (μmol/L) (median (Q1–Q3)) | 98 (79–114) | 93 (74–108) | 95 (89–107) | 0.578 | 0.685 | 0.893 |
CRP (mg/L) (median (Q1–Q3)) | 6 (5–8) | 6 (3–8) | 6 (5–8) | 0.64 | 0.934 | 0.756 |
Preoperative echocardiography: | ||||||
LVED (mm) (median (Q1–Q3)) | 50 (44–55) | 57 (53–60) | 61 (57–64) | <0.001 | <0.001 | <0.001 |
LVEF (%) (median (Q1–Q3)) | 53 (50–57) | 40 (38–43) | 31 (27–34) | <0.001 | <0.001 | <0.001 |
Off-pump surgery: | ||||||
Skin-to-skin time (min) (median (Q1–Q3)) | 132 (119–167) | 139 (121–170) | 161 (120–182) | 0.289 | 0.116 | 0.189 |
Number of grafts (n, mean (SD)) | 2.2 (0.8) | 2.4 (0.7) | 3.0 (0.8) | 0.148 | 0.047 | 0.563 |
Troponin max (ng/mL) (median (Q1–Q3)) | 1.698 (0.789–4.334) | 1.47 (0.603–3.416) | 2.37 (0.942–4.125) | 0.452 | 0.453 | 0.187 |
Overall hospitalization: (days) (mean (SD)) | 10 (2) | 11 (3) | 14 (3) | 0.608 | 0.043 | 0.278 |
Complications: | ||||||
Bleeding (n, (%)) | 2 (1) | 1 (2) | 1 (2) | 1 | 1 | 0.561 |
Wound infection (n, (%)) | 3 (2) | 2 (3) | 1 (2) | 0.61 | 1 | 1 |
Parameters | Group 1 | Group 2 | Group 3 | p | p | p |
---|---|---|---|---|---|---|
LVEF ≥ 50% | LVEF 41–49% | LVEF ≤ 40% | Group 1 vs. Group 2 | Group 1 vs. Group 3 | Group 2 vs. Group 3 | |
n = 169 | n = 61 | n = 53 | ||||
Mean follow-up time (years) (mean (SD) | 5.3 (1.1) | 5.5 (1.1) | 5.4 (1.1) | 0.919 | 0.814 | 0.818 |
Follow–up laboratory results: | ||||||
WBC (×109/L) (median (Q1–Q3)) | 8.32 (7.04–9.73) | 8.6 (6.96–10.31) | 8.91 (7.68–10.49) | 0.797 | 0.152 | 0.535 |
Hb (mmol/L) (median (Q1–Q3)) | 7.0 (6.6–7.4) | 6.8 (6.5–7.45) | 6.9 (6.5–7.5) | 0.915 | 0.767 | 0.709 |
Plt (×109/L) (median (Q1–Q3)) | 264 (211–322) | 258 (220–303) | 272 (222–354) | 0.988 | 0.509 | 0.502 |
Creatinine (μmol/L) (median (Q1–Q3)) | 92 (79–104) | 94 (75–105) | 93 (81.5–100.6) | 0.589 | 0.847 | 0.892 |
Uric acid (μmol/L) (median (Q1–Q3)) | 5.72 (4.85–6.99) | 5.94 (5.01–6.63) | 6.00 (4.98–7.64) | 0.961 | 0.346 | 0.946 |
Hb1Ac (%) (median (Q1–Q3)) | 6.4 (6.0–6.9) | 6.5 (6.1–7.1) | 6.4 (6.0–7.0) | 0.928 | 0.879 | 0.945 |
Lipidogram: | ||||||
Total cholesterol (mmol/L) (median (Q1–Q3)) | 4.0 (3.3–4.7) | 3.7 (3.1–4.2) | 3.8 (3.5–4.2) | 0.131 | 0.212 | 0.441 |
LDL (mmol/L) (median (Q1–Q3)) | 2.2 (1.6–2.9) | 1.7 (1.3–2.4) | 2.1 (1.6–2.3) | 0.034 | 0.145 | 0.123 |
HDL (mmol/L) (median (Q1–Q3)) | 1.2 (0.9–1.5) | 1.0 (0.9–1.3) | 1.1 (1.0–1.2) | 0.11 | 0.48 | 0.423 |
TG (mmol/L) (median (Q1–Q3)) | 1.4 (1.1–1.8) | 1.5 (1.0–1.9) | 1.5 (1.0–1.5) | 0.324 | 0.052 | 0.365 |
Follow-up echocardiography | ||||||
LVED (mm) (median) (Q1–Q3) | 48 (42–52) | 55 (51–58) | 57 (53–61) | <0.001 | <0.001 | <0.001 |
LVEF (%) (median (Q1–Q3) | 55 (50–60) | 44 (41–47) | 33 (30–37) | <0.001 | <0.001 | <0.001 |
Postoperative pharmacotherapy: | ||||||
B-blockers (n (%)) | 169 (100) | 61 (100) | 53 (100) | 1 | 1 | 1 |
ACE-I (n (%)) | 151 (89) | 56 (92) | 21 (40) | 1 | <0.001 | <0.001 |
ARNI (n (%)) | 14 (8) | 3 (5) | 32 (60) | 0.768 | <0.001 | <0.001 |
Diuretics (n (%)) | 29 (17) | 17 (28) | 34 (64) | 0.092 | <0.001 | <0.001 |
SGLT2 inhibitors (n (%)) | 2 (1) | 3 (5) | 15 (28) | 0.09 | <0.001 | 0.004 |
Statins (n (%)) | 164 (97) | 61 (100) | 53 (100) | 0.566 | 1 | 1 |
MRA (n (%)) | 3 (18) | 5 (8) | 45 (85) | 0.034 | <0.001 | <0.001 |
ASA (n (%)) | 169 (100) | 61 (100) | 53 (100) | 1 | 1 | 1 |
Insulin (n (%)) | 31 (18) | 6 (10) | 10 (19) | 0.218 | 0.838 | 0.187 |
Metformin (n (%)) | 26 (15) | 15 (25) | 43 (81) | 0.12 | <0.001 | <0.001 |
Ambient air pollution | ||||||
PM2.5 (μg/m3) (median (Q1–Q3) | 18.9 (16.9–22.4) | 20.6 (17.8–23.0) | 18.9 (15.4–21.8) | 0.152 | 0.614 | 0.108 |
PM10 (μg/m3) (median (Q1–Q3) | 25.3 (22.4–29.6) | 26.7 (23.9–29.7) | 25.0 (21.2–28.3) | 0.237 | 0.37 | 0.053 |
NO2 (μg/m3) (median (Q1–Q3) | 12.2 (9.99–15.62) | 13.0 (10.1–15.1) | 11.2 (9.3–14.5) | 0.709 | 0.217 | 0.145 |
Five-year overall mortality (n, %) | 23 (14) | 9 (15) | 14 (26) | 0.831 | 0.036 | 0.161 |
Parameters | Univariable | Multivariable | ||||
---|---|---|---|---|---|---|
HR | 95% CI | p | HR | 95% CI | p | |
Demographical: | ||||||
Age | 0.976 | 0.828–1.151 | 0.775 | |||
Sex (male) | 0.755 | 0.135–2.606 | 0.49 | |||
BMI | 0.976 | 0.828–1.151 | 0.755 | |||
Clinical: | ||||||
Arterial hypertension | 2.411 | 0.465–12.512 | 0.295 | |||
Diabetes mellitus | 2.402 | 0.702–8.218 | 0.163 | |||
Hypercholesterolemia | 4.246 | 1.152–15.646 | 0.03 | 3.254 | 1.008–10.511 | 0.049 |
PAD | 1.145 | 1.044–3.871 | 0.437 | |||
Perioperative: | ||||||
Number of grafts (2) | 1.478 | 0.288–7.574 | 0.64 | |||
Number of grafts (3) | 1.579 | 0.309–8.078 | 0.583 | |||
Arterial revascularization | 0.91 | 0.567–1.245 | 0.592 | |||
Troponin max | 0.903 | 0.770–1.059 | 0.21 | |||
Postoperative: | ||||||
Creatinine | 0.995 | 0.970–1.022 | 0.726 | |||
Uric acid | 0.889 | 0.616–1.282 | 0.528 | |||
Air pollution exposure: | ||||||
PM2.5 | 0.979 | 0.688–1.392 | 0.906 | |||
PM10 | 0.955 | 0.723–1.370 | 0.977 | |||
NO2 | 1.012 | 0.871–1.175 | 0.879 |
Parameter | Univariable | Multivariable | ||||
---|---|---|---|---|---|---|
HR | 95% CI | p | HR | 95% CI | p | |
Demographical: | ||||||
Age | 0.82 | 0.521–1.291 | 0.39 | |||
Sex (male) | 0.047 | 0.01–4.086 | 0.18 | |||
BMI | 1.194 | 0.743–1.919 | 0.463 | |||
Clinical: | ||||||
Arterial hypertension | 4.366 | 0.280–10.672 | 0.196 | |||
Diabetes mellitus | 1.934 | 0.124–30.031 | 0.638 | |||
Hypercholesterolemia | 6.767 | 0.859–83.861 | 0.156 | 3.391 | 1.001–11.874 | 0.05 |
PAD | 1.04 | 0.103–5.764 | 0.241 | |||
Perioperative: | ||||||
Number of grafts (2) | 0.053 | 0.001–33.6700 | 0.226 | |||
Number of grafts (3) | 0.062 | 0.002–43.703 | 0.227 | |||
Arterial revascularization | 0.902 | 0.567– 1.674 | 0.997 | |||
Troponin max | 1.015 | 0.805–1.278 | 0.902 | |||
Postoperative: | ||||||
Creatinine | 0.997 | 0.943–1.054 | 0.913 | |||
Uric acid | 1.155 | 0.282–4.726 | 0.841 | |||
Air pollution exposure: | ||||||
PM2.5 | 2.084 | 0.849–5.114 | 0.109 | 1.327 | 1.085–1.625 | 0.006 |
PM10 | 1.009 | 0.122–1.250 | 0.113 | |||
NO2 | 1.429 | 0.829–2.464 | 0.199 |
Parameter | Univariable | Multivariable | ||||
---|---|---|---|---|---|---|
HR | 95% CI | p | HR | 95% CI | p | |
Demographical: | ||||||
Age | 1.032 | 0.868–1.228 | 0.719 | |||
Sex (male) | 4.061 | 0.681–10.603 | 0.996 | |||
BMI | 1.035 | 0.784–1.367 | 0.807 | |||
Clinical: | ||||||
Arterial hypertension | 1.374 | 0.477–21.139 | 0.633 | |||
Diabetes mellitus | 1.856 | 0.228–15.096 | 0.563 | |||
Hypercholesterolemia | 2.397 | 0.327–24.812 | 0.142 | |||
PAD | 1.496 | 0.484–11.671 | 0.401 | |||
Perioperative: | ||||||
Number of grafts (2) | 1.478 | 0.961–1.029 | 0.743 | |||
Number of grafts (3) | 1.579 | 0.309–8.078 | 0.583 | |||
Arterial revascularization | 0.91 | 0.567–1.245 | 0.592 | |||
Troponin max | 1.062 | 0.998–1.158 | 0.092 | |||
Postoperative: | ||||||
Creatinine | 0.994 | 0.970–1.022 | 0.726 | |||
Uric acid | 0.889 | 0.616–1.282 | 0.528 | |||
Air pollution exposure: | ||||||
PM2.5 | 1.311 | 0.588–2.923 | 0.509 | 1.518 | 1.050–2.195 | 0.026 |
PM10 | 1.322 | 0.547–3.193 | 0.535 | |||
NO2 | 0.644 | 0.306–1.355 | 0.247 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 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/).
Share and Cite
Urbanowicz, T.; Skotak, K.; Olasińska-Wiśniewska, A.; Filipiak, K.J.; Płachta-Krasińska, A.; Piecek, J.; Krasińska, B.; Krasiński, Z.; Tykarski, A.; Jemielity, M. The Possible Role of PM2.5 Chronic Exposure on 5-Year Survival in Patients with Left Ventricular Dysfunction Following Coronary Artery Bypass Grafting. Toxics 2024, 12, 697. https://doi.org/10.3390/toxics12100697
Urbanowicz T, Skotak K, Olasińska-Wiśniewska A, Filipiak KJ, Płachta-Krasińska A, Piecek J, Krasińska B, Krasiński Z, Tykarski A, Jemielity M. The Possible Role of PM2.5 Chronic Exposure on 5-Year Survival in Patients with Left Ventricular Dysfunction Following Coronary Artery Bypass Grafting. Toxics. 2024; 12(10):697. https://doi.org/10.3390/toxics12100697
Chicago/Turabian StyleUrbanowicz, Tomasz, Krzysztof Skotak, Anna Olasińska-Wiśniewska, Krzysztof J Filipiak, Aleksandra Płachta-Krasińska, Jakub Piecek, Beata Krasińska, Zbigniew Krasiński, Andrzej Tykarski, and Marek Jemielity. 2024. "The Possible Role of PM2.5 Chronic Exposure on 5-Year Survival in Patients with Left Ventricular Dysfunction Following Coronary Artery Bypass Grafting" Toxics 12, no. 10: 697. https://doi.org/10.3390/toxics12100697
APA StyleUrbanowicz, T., Skotak, K., Olasińska-Wiśniewska, A., Filipiak, K. J., Płachta-Krasińska, A., Piecek, J., Krasińska, B., Krasiński, Z., Tykarski, A., & Jemielity, M. (2024). The Possible Role of PM2.5 Chronic Exposure on 5-Year Survival in Patients with Left Ventricular Dysfunction Following Coronary Artery Bypass Grafting. Toxics, 12(10), 697. https://doi.org/10.3390/toxics12100697