Şiddetli Toplum Kökenli Pnömonili Hastalarda Pan-İmmün-İnflamasyon Değerinin 30 Günlük Mortaliteyi Öngörmedeki Rolü

Abstract

Toplum kökenli pnömoni (TKP), özellikle yoğun bakım ünitelerine (YBÜ) yatırılan kritik hastalarda önemli morbidite ve mortalite nedenidir. Prognostik sınıflamada yaygın olarak kullanılan çeşitli klinik skorlama sistemleri bulunsa da, bu sistemlerin sınırlılıkları yeni biyobelirteçlere olan ilgiyi artırmıştır. Pan-immün-inflamasyon değeri (PIIV), sistemik inflamasyon ve bağışıklık durumunu değerlendirmede yeni tanımlanmış bir biyobelirteçtir. Bu çalışmada, YBÜ’ye yatırılan TKP hastalarında PIIV ile diğer geleneksel inflamatuar belirteçler ve mortalite arasındaki ilişki araştırılmıştır. Çalışmaya retrospektif olarak toplam 248 TKP hastası dahil edilmiştir. Elektronik arşivlerden elde edilen demografik, klinik ve laboratuvar verileri ile 30 günlük mortalite arasındaki ilişki değerlendirilmiştir. Bağımsız mortalite belirleyicilerini tanımlamak amacıyla univaryant ve multivaryant lojistik regresyon analizleri yapılmış, ROC analizi ile tanısal performans değerlendirilmiştir. Çalışmadaki 248 hastanın 156’sı (%62,9) hayatını kaybetmiştir. PIIV, prokalsitonin, laktat ve nötrofil-lenfosit oranı (NLO), sağ kalamayan hastalarda anlamlı düzeyde yüksek bulunmuştur. Çok değişkenli analizde, PIIV (düzeltilmiş OR: 1,227; %95 CI: 1,097–1,372; p < 0,001), laktat (düzeltilmiş OR: 1,637; %95 CI: 1,290–2,077; p < 0,001) ve prokalsitonin (düzeltilmiş OR: 1,017; %95 CI: 1,002–1,033; p = 0,022) 30 günlük mortalitenin bağımsız belirleyicileri olarak tanımlandı. ROC analizinde PIIV için 1928,3 kesim değerinde %54,5 duyarlılık ve %70,7 özgüllük elde edilmiştir. Laktat en yüksek duyarlılığı (%75,6) gösterirken, prokalsitonin %73,7 duyarlılık ve %61,9 özgüllüğe sahiptir. PIIV, TKP hastalarında mortaliteyi öngörmede bağımsız ve değerli bir biyobelirteçtir. Çok sayıda hematolojik parametreyi entegre ederek bağışıklık-inflamasyon dengesini yansıtabilir ve mevcut belirteçlerle birlikte kullanıldığında klinik karar süreçlerine katkı sağlayabilir.

Keywords

• Toplum Kökenli Pnömoni
• Prognoz
• mortalite
• pan-immun-inflamasyon değeri

Assessing the Prognostic Performance of Pan Immune-Inflammation Value and Inflammatory Biomarkers in Critically Ill Patients with Community-Acquired Pneumonia

Abstract

Community-acquired pneumonia (CAP) remains a major cause of morbidity and mortality, particularly among critically ill patients in intensive care units (ICUs). Although various clinical scoring systems are used for prognostic stratification, their limitations have prompted interest in novel biomarkers. The pan-immune-inflammation value (PIIV) is a recently proposed index assessing systemic inflammation and immune status. This study investigates the relationship between PIIV, traditional inflammatory markers, and mortality outcomes in ICU-admitted CAP patients. A total of 248 CAP patients were retrospectively analyzed. Demographic, clinical, and laboratory data were obtained from electronic medical records. Associations between these variables and 30-day mortality were evaluated. Univariate and multivariate logistic regression analyses identified independent mortality predictors, and Receiver Operating Characteristic (ROC) analysis assessed diagnostic performance. Among 248 patients, 156 (62.9%) died. PIIV, procalcitonin, lactate, and neutrophil-lymphocyte ratio (NLR) levels were significantly higher in non-survivors. Multivariable analysis identified PIIV (adjusted OR: 1.227; 95% CI: 1.097–1.372; p < 0.001), lactate (adjusted OR: 1.637; 95% CI: 1.290–2.077; p < 0.001), and procalcitonin (adjusted OR: 1.017; 95% CI: 1.002–1.033; p = 0.022), as independent predictors of 30-day mortality. ROC analysis showed optimal cut-off values: PIIV ≥1928.3 (54.5% sensitivity, 70.7% specificity), lactate ≥1.6 mmol/L (75.6% sensitivity), and procalcitonin ≥1.26 ng/mL (73.7% sensitivity, 61.9% specificity). PIIV is an independent prognostic indicator of mortality in CAP patients, reflecting systemic inflammation through multiple hematological parameters. It may capture complex immune-inflammatory dynamics and serve as a useful adjunctive biomarker alongside established markers.

Keywords

• Community acquired pneumonia
• prognosis
• mortality
• pan-immune-inflammation value

References

1. 1. Fally M, Hansel J, Robey RC, Haseeb F, Kouta A, Williams T, et al. Decoding community-acquired pneumonia: a systematic review and analysis of diagnostic criteria and definitions used in clinical trials. Clin Microbiol Infect. 2025;31(5):724-730
2. 2. Ramirez JA, File TM. How to assess survival prognosis in patients hospitalized for community-acquired pneumonia in 2024? Curr Opin Crit Care. 2024;30(5):399-405
3. 3. Calis AG, Karaboga B, Uzer F, Kaplan N, Karaca M, Gedik RB, et al. Correlation of Pneumonia Severity Index and CURB-65 Score with Neutrophil/Lymphocyte Ratio, Platelet/Lymphocyte Ratio, and Monocyte/Lymphocyte Ratio in Predicting In-Hospital Mortality for Community-Acquired Pneumonia: Observational Study. J Clin Med. 2025;14(3):728.
4. 4. Zhou HJ, Lan TF, Guo SB. Outcome prediction value of National Early Warning Score in septic patients with community-acquired pneumonia in emergency department: A single-center retrospective cohort study. World J Emerg Med. 2020;11(4):206-215.
5. 5. Zhou H, Zhu X, Zhang Y, Xu W, Li S. The incremental value of aspartate aminotransferase/alanine aminotransferase ratio combined with CURB-65 in predicting treatment outcomes in hospitalized adult community-acquired pneumonia patients with type 2 diabetes mellitus. BMC Pulm Med. 2025;25(1):26.
6. 6. Torun S, Tunc BD, Suvak B, Yildiz H, Tas A, Sayilir A, et al. Assessment of neutrophil-lymphocyte ratio in ulcerative colitis: a promising marker in predicting disease severity. Clin Res Hepatol Gastroenterol. 2012;36(5):491-7
7. 7. Akdur G, Bardakçı O, Das M, Akdur O, Beyazit Y. Diagnostic utility of hematological indices in predicting adverse outcomes and severity of acute pancreatitis based on BISAP and modified Glasgow score. Ulus Travma Acil Cerrahi Derg. 2022;28(3):268-275.
8. 8. Çoşkun N, Metin M, Doğan G, İpek H, Demir E, Afşarlar ÇE. PAN-Immune inflammation value: a new biomarker for diagnosing appendicitis in children?? BMC Pediatr. 2025;25(1):165.

9. 9. Karaduman A, Yılmaz C, Keten MF, Balaban İ, Kültürsay B, Danışman N, et al. Prognostic value of pan immune-inflammation value in patients undergoing unprotected left main coronary artery stenting. Biomark Med. 2024;18(21-22):957-967.
10. 10. Wang Q, Zhong W, Xiao Y, Lin G, Lu J, Xu L, et al. Pan-immune-inflammation value predicts immunotherapy response and reflects local antitumor immune response in rectal cancer. Cancer Sci. 2025;116(2):350-366.
11. 11. Zheng Z., Yu M., Peng G, Xiao Y. Systemic Immune Inflammation Index (SII) and Prognostic Nutritional Index (PNI) Associated with Prolonged Intensive Care Unit (ICU) Stay in Patients with Pneumonia Complicated with Respiratory Failure. Int J General Med. 2025;18:1765–1776.
12. 12. Mardan M, Zheng H, Xu Q, Song S, Lu Z, Deng H, et al. Comprehensive analysis of Pan-Immune Inflammation and all-cause mortality in rheumatoid arthritis: a database-driven approach, 1999-2018. Front Immunol. 2025;16:1549955.
13. 13. Dinh A, Duran C, Ropers J, Bouchand F, Deconinck L, Matt M, et al. Exclusive oral antibiotic treatment for hospitalized community-acquired pneumonia: a post-hoc analysis of a randomized clinical trial. Clin Microbiol Infect. 2024;30(8):1020-1028.
14. 14. Unal Cetin E, Kurtkulagi O, Kamis F, Das M, Simsek E, Cetin AU, et al. Advancing ICU mortality prediction in community-acquired pneumonia: Combining fibrinogen-to-albumin ratio, CT severity score, PSI, and CURB-65. Biomol Biomed. 2025. doi: 10.17305/bb.2025.12127
15. 15. Guo Q, Li HY, Song WD, Li M, Chen XK, Liu H, et al. Updating cut-off values of severity scoring systems for community-acquired pneumonia to orchestrate more predictive accuracy. Ann Med. 2023;55(1):2202414.
16. 16. Ewig S, de Roux A, Bauer T, García E, Mensa J, Niederman M, et al. Validation of predictive rules and indices of severity for community acquired pneumonia. Thorax. 2004;59(5):421-7.
17. 17. Beyazit Y, Sayilir A, Torun S, Suvak B, Yesil Y, Purnak T, et al. Mean platelet volume as an indicator of disease severity in patients with acute pancreatitis. Clin Res Hepatol Gastroenterol. 2012;36(2):162-8.
18. 18. Hu C, Du N, Li J, Chen L, Meng X, Yao L,et al. Correlation Between Monocyte Count, Monocyte-Lymphocyte Ratio, and Other Inflammatory Cells With Sleep and Psychiatric Symptoms in First-Episode Schizophrenia Patients. Neuropsychiatr Dis Treat. 2025;21:373-381
19. 19. Bardakci O, Das M, Akdur G, Akman C, Siddikoglu D, Akdur O, et al. Haemogram indices are as reliable as CURB-65 to assess 30-day mortality in Covid-19 pneumonia. Natl Med J India. 2022;35(4):221-228.
20. 20. Qiu Y, Su Y, Tu GW, Ju MJ, He HY, Gu ZY, et al. Neutrophil-to-Lymphocyte Ratio Predicts Mortality in Adult Renal Transplant Recipients with Severe Community-Acquired Pneumonia. Pathogens. 2020;9(11):913. 21. Karadag-Oncel E, Ozsurekci Y, Kara A, Karahan S, Cengiz AB, Ceyhan M. The value of mean platelet volume in the determination of community acquired pneumonia in children. Ital J Pediatr. 2013;39:16.
21. 22. Enersen CC, Egelund GB, Petersen PT, Andersen S, Ravn P, Rohde G, et al. The ratio of neutrophil-to-lymphocyte and platelet-to-lymphocyte and association with mortality in community-acquired pneumonia: a derivation-validation cohort study. Infection. 2023;51(5):1339-1347.
22. 23. Mutlu E, Inanc M. Prognostic significance of inflammation scores in malignant mesothelioma. Eur Rev Med Pharmacol Sci. 2024;28(6):2340-2350
23. 24. Duan L, Guo W, Yin S, et al. The Baseline Pan-Immune-Inflammation Value (PIV) and PILE in Predicting Clinical Outcomes and Therapeutic Response for Primary Central Nervous System Lymphoma. J Inflamm Res. 2024;17:5347-5363.
24. 25. Yilmaz Y, Kelesoglu S. The Importance of Pan-Immune Inflammation Value (PIV) in Predicting Coronary Collateral Circulation in Stable Coronary Artery Patients. Angiology. 2024 Jun 1.
25. 26. Sharma Y, Thompson C, Zinellu A, Shahi R, Horwood C, Mangoni AA. The role of the neutrophil-to-lymphocyte ratio in predicting outcomes among patients with community-acquired pneumonia. Clin Med (Lond). 2025;25(1):100278.
26. 27. Cui XJ, Xie B, Zhu KW, Liao QQ, Zhou JC, Du S, et al. Prognostic value of the platelet, neutrophil, monocyte, basophil, and eosinophil to lymphocyte ratios in patients with severe community-acquired pneumonia (SCAP). Sci Rep. 2024;14(1):30406
27. 28. Lee H. Procalcitonin as a biomarker of infectious diseases. Korean J Intern Med. 2013;28(3):285-91
28. 29. Doganci M, Eraslan Doganay G, Sazak H, Alagöz A, Cirik MO, Hoşgün D, et al. The Utility of C-Reactive Protein, Procalcitonin, and Leukocyte Values in Predicting the Prognosis of Patients with Pneumosepsis and Septic Shock. Medicina (Kaunas). 2024;60(10):1560
29. 30. Ozbay S, Ayan M, Ozsoy O, Akman C, Karcioglu O. Diagnostic and Prognostic Roles of Procalcitonin and Other Tools in Community-Acquired Pneumonia: A Narrative Review. Diagnostics (Basel). 2023;13(11):1869