Article Data

  • Views 3105
  • Dowloads 181

Original Research

Open Access

Analysis of the predictive value of platelet parameters for the prognosis of elderly patients with severe pneumonia

  • Ling Jia1,†
  • Lei Shi2,†
  • Jianqin Cai1
  • Jiao Chen1
  • Jinghui Yang1
  • Xiang Xue1
  • Wei Zhao1
  • Wei Gao3,*,
  • Ya Shen4,*,

1Department of Intensive Care Unit, Sir Run Run Hospital Nanjing Medical University, 211100 Nanjing, Jiangsu, China

2Department of Respiratory Medicine, Sir Run Run Hospital Nanjing Medical University, 211100 Nanjing, Jiangsu, China

3Department of Geriatrics, Zhongda Hospital, School of Medicine, Southeast University, 210009 Nanjing, Jiangsu, China

4Department of Integrated Services, Jiangsu Provincial Center for Disease Control and Prevention, 210009 Nanjing, Jiangsu, China

DOI: 10.22514/sv.2025.039 Vol.21,Issue 3,March 2025 pp.74-80

Submitted: 29 October 2024 Accepted: 17 December 2024

Published: 08 March 2025

*Corresponding Author(s): Wei Gao E-mail: drweig1984@outlook.com
*Corresponding Author(s): Ya Shen E-mail: sy_dr06@126.com

† These authors contributed equally.

Abstract

Background: The aim of this study was to evaluate the ability of platelet parameters to predict outcomes in elderly patients with severe pneumonia. Methods: We retrospectively analyzed the clinical data of 197 elderly patients with severe pneumonia. The patients were divided into two groups based on their survival in 28 days: the survival group (148 cases) and the death group (49 cases). Results: The Acute Physiology and Chronic Health Evaluation (APACHE II) scores were significantly higher in the death group compared to the survival group (p < 0.05). Platelet count (PLT) was significantly lower (p < 0.05), while platelet distribution width (PDW), mean platelet volume (MPV), and platelet-large cell ratio (P-LCR) were significantly higher in the death group than the survival group (p < 0.05). Receiver operating characteristic (ROC) curve analysis revealed that the platelet parameters PLT, PDW, MPV and P-LCR had area under curve (AUC) values of 0.834, 0.760, 0.847 and 0.842, respectively, for predicting 28-day mortality in elderly patients. The combined AUC for these four platelet parameters was 0.964, which was significantly higher than that of any individual parameter (p < 0.05). Kaplan-Meier analysis also demonstrated that PLT, PDW, MPV and P-LCR were all associated with the 28-day prognosis of patients (p < 0.05). Multivariable logistic regression analysis identified APACHE II score, PDW, MPV and P-LCR as independent risk factors for poor prognosis in elderly patients with severe pneumonia (p < 0.05). Conclusions: Our findings suggest that PLT, PDW, MPV and P-LCR could be utilized as prognostic indicators for elderly patients with severe pneumonia as these parameters were notably different between the death and survival groups of these patients. Integrating changes in various platelet parameters hold the potential for improving the prognostic evaluation of elderly individuals with severe pneumonia.


Keywords

Platelet parameters; Severe pneumonia; Prognosis; Predictive value


Cite and Share

Ling Jia,Lei Shi,Jianqin Cai,Jiao Chen,Jinghui Yang,Xiang Xue,Wei Zhao,Wei Gao,Ya Shen. Analysis of the predictive value of platelet parameters for the prognosis of elderly patients with severe pneumonia. Signa Vitae. 2025. 21(3);74-80.

References

[1] Luo A, Liu Y. The effect of low-molecular-weight heparin combined with amikacin on the coagulation function and bacterial clearance in the treatment of patients with severe senile pneumonia. Pakistan Journal of Medical Sciences. 2023; 39: 172–176.

[2] Takazono T, Namie H, Nagayoshi Y, Imamura Y, Ito Y, Sumiyoshi M, et al. Development of a score model to predict long-term prognosis after community-onset pneumonia in older patients. Respirology. 2024; 29: 722–730.

[3] Chongthanadon B, Thirawattanasoot N, Ruangsomboon O. Clinical factors associated with in-hospital mortality in elderly versus non-elderly pneumonia patients in the emergency department. BMC Pulmonary Medicine. 2023; 23: 330.

[4] Yao W, Wang W, Tang W, Lv Q, Ding W. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune inflammation index (SII) to predict postoperative pneumonia in elderly hip fracture patients. Journal of Orthopaedic Surgery and Research. 2023; 18: 673.

[5] Aydemir S, Segmen F, Kucuk O. Evaluation of plateletcrit level from platelet indices as a prognostic marker in COVID-19 patients. European Review for Medical and Pharmacological Sciences. 2023; 27: 9429–9437.

[6] Farghly S, Abd-Elkader R, Zohne RA, El-Kareem DMA. Mean platelet volume change (MPV) and red blood cell distribution width (RDW) as promising markers of community-acquired pneumonia (CAP) outcome. Egyptian Journal of Bronchology. 2020; 14: 23.

[7] Gozukucuk R, Kılıc HH, Uyanik BS, Cakiroglu B. The İmportance of hematological parameters in the prognosis of patients with severe COVID-19, A single-center retrospective study. Nigerian Journal of Clinical Practice. 2023; 26: 1297–1302.

[8] Lindenauer PK, Strait KM, Grady JN, Ngo CK, Parisi ML, Metersky M, et al. Variation in the diagnosis of aspiration pneumonia and association with hospital pneumonia outcomes. Annals of the American Thoracic Society. 2018; 15: 562–569.

[9] Shi S, Wang F, Chen B, Pan J, Luo D, Pei C, et al. Efficacy and safety of Shenfu injection for severe pneumonia in the elderly: a systematic review and meta-analysis based on western and eastern medicine. Frontiers in Pharmacology. 2022; 13: 779942.

[10] Song Y, Wang X, Lang K, Wei T, Luo J, Song Y, et al. Development and validation of a nomogram for predicting 28-day mortality on admission in elderly patients with severe community-acquired pneumonia, Journal of Inflammation Research. 2022; 15: 4149–4158.

[11] Aydemir S, Hoşgün D. Evaluation of the factors affecting long-term mortality in geriatric patients followed up in intensive care unit due to hospital-acquired pneumonia. Medicine. 2022; 101: e30645.

[12] Işler Y, Kaya H. Relationship of platelet counts, platelet volumes, and Curb-65 scores in the prognosis of COVID-19 patients. The American Journal of Emergency Medicine. 2022; 51: 257–261.

[13] Thungthienthong M, Vattanavanit V. Platelet-to-white blood cell ratio as a predictor of mortality in patients with severe COVID-19 pneumonia: a retrospective cohort study. Infection and Drug Resistance. 2023; 16: 445–455.

[14] Wang J, Cui L, Guo Z. Predictive value of platelet-related parameters combined with pneumonia severity index score for mortality rate of patients with severe pneumonia, African Health Sciences. 2023; 23: 202–207.

[15] 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: 1339–1347.

[16] Diao Y, Zhao Y, Li X, Li B, Huo R, Han X. A simplified machine learning model utilizing platelet-related genes for predicting poor prognosis in sepsis. Frontiers in Immunology. 2023; 14: 1286203.

[17] Xie X, Yan D, Liu X, Wang Y, Deng Y, Yao R, et al. High platelet distribution width is an independent risk factor of postoperative pneumonia in patients with type A acute aortic dissection. Frontiers in Cardiovascular Medicine. 2022; 9: 984693.

[18] Fan C, Mao Y, Liu J, Gao H, Fang B, Li R, et al. Dynamics of platelet parameters in children with severe community-acquired pneumonia between viral and bacterial infections. Translational Pediatrics. 2024; 13: 52–62.

[19] Asmaa Y, Kakalia S, Irtza M, Malik R. The diagnostic association of radiological and clinicopathological parameters in community-acquired pneumonia in children: a cross-sectional study. Cureus. 2024; 16: e53626.

[20] Quispe-Pari JF, Gonzales-Zamora JA, Munive-Dionisio J, Castro-Contreras C, Villar-Astete A, Kong-Paravicino C, et al. Mean platelet volume as a predictor of COVID-19 severity: a prospective cohort study in the highlands of Peru. Diseases. 2022; 10: 22.

[21] Dixit S, Arora JK, Kumar R, Arora R. Role of routine blood parameters in predicting mortality among surgical patients with sepsis. Cureus. 2023; 15: e37413.

[22] Sugihara H, Marumo A, Okabe H, Kohama K, Mera T, Morishita E. Platelet and large platelet ratios are useful in predicting severity of COVID-19. International Journal of Hematology. 2024; 119: 638–646.

[23] Mahalingam S, Bhaskar V, Batra P, Dewan P, Gogoi P. Hematological indices for identifying adverse outcomes in children admitted to pediatric ICUs. Cureus. 2024; 16: e53744.

[24] Zhuang J, Shen L, Li M, Sun J, Hao J, Li J, et al. Cancer-associated fibroblast-derived miR-146a-5p generates a niche that promotes bladder cancer stemness and chemoresistance. Cancer Research. 2023; 83: 1611–1627.

[25] Wang L, Lv Q, Zhang X, Jiang B, Liu E, Xiao C, et al. The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores. PeerJ. 2020; 8: e10018.

[26] Pan J, Bu W, Guo T, Geng Z, Shao M. Development and validation of an in-hospital mortality risk prediction model for patients with severe community-acquired pneumonia in the intensive care unit. BMC Pulmonary Medicine. 2023; 23: 303.


Abstracted / indexed in

Science Citation Index Expanded (SCIE) (On Hold)

Chemical Abstracts Service Source Index

Scopus: CiteScore 1.3 (2024)

Embase

Submission Turnaround Time

Top