Risk stratification and survival time of patients with gram-negative bacillary pneumonia in the intensive care unit.

Qiu-Xia Liao, Zhi Feng, Hui-Chang Zhuo, Ye Zhou, Peng Huang, Hai-Rong Lin
Author Information
  1. Qiu-Xia Liao: Department of Intensive Care Unit, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  2. Zhi Feng: Department of Thoracic Surgery, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  3. Hui-Chang Zhuo: Department of Intensive Care Unit, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  4. Ye Zhou: Department of Intensive Care Unit, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  5. Peng Huang: Department of Intensive Care Unit, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  6. Hai-Rong Lin: Department of Intensive Care Unit, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.

Abstract

Introduction: Pneumonia is a common infection in the intensive care unit (ICU), and gram-negative bacilli are the most common bacterial cause. The purpose of the study was to investigate the risk factors for 30-day mortality in patients with gram-negative bacillary pneumonia in the ICU, construct a predictive model, and stratify patients based on risk to assess their short-term survival.
Methods: patients admitted to the ICU with gram-negative bacillary pneumonia at Fujian Medical University Affiliated First Hospital between January 2018 and September 2020 were selected. patients were divided into deceased and survivor groups based on whether death occurred within 30 days. Multifactorial logistic regression analysis was used to identify independent risk factors for 30-day mortality in these patients, and a predictive nomogram model was constructed based on these factors. patients were categorized into low-, medium-, and high-risk groups according to the model's predicted probability, and Kaplan-Meier survival curves were plotted to assess short-term survival.
Results: The study included 305 patients. Lactic acid (odds ratio [OR], 1.524, 95% CI: 1.057-2.197), tracheal intubation (OR: 4.202, 95% CI: 1.092-16.169), and acute kidney injury (OR:4.776, 95% CI: 1.632-13.978) were identified as independent risk factors for 30-day mortality. A nomogram prediction model was established based on these three factors. Internal validation of the model showed a Hosmer-Lemeshow test result of X2=5.770, P=0.834, and an area under the ROC curve of 0.791 (95% CI: 0.688-0.893). Bootstrap resampling of the original data 1000 times yielded a C-index of 0.791, and a decision curve analysis indicated a high net benefit when the threshold probability was between 15%-90%. The survival time for low-, medium-, and high-risk patients was 30 (30, 30), 30 (16.5, 30), and 17 (11, 27) days, respectively, which were significantly different.
Conclusion: Lactic acid, tracheal intubation, and acute kidney injury were independent risk factors for 30-day mortality in patients in the ICU with gram-negative bacillary pneumonia. The predictive model constructed based on these factors showed good predictive performance and helped assess short-term survival, facilitating early intervention and treatment.

Keywords

References

  1. J Glob Antimicrob Resist. 2018 Sep;14:190-196 [PMID: 29751127]
  2. Intern Emerg Med. 2022 Sep;17(6):1575-1588 [PMID: 35852675]
  3. Curr Opin Infect Dis. 2019 Dec;32(6):656-662 [PMID: 31567412]
  4. Clin Respir J. 2018 Mar;12(3):991-995 [PMID: 28168816]
  5. Int J Antimicrob Agents. 2022 Sep;60(3):106633 [PMID: 35787918]
  6. Lancet. 2020 Aug 22;396(10250):565-582 [PMID: 32828189]
  7. Ann Intensive Care. 2023 Jan 7;13(1):1 [PMID: 36609725]
  8. J Crit Care. 2023 Dec;78:154346 [PMID: 37247528]
  9. Crit Care Med. 2017 Apr;45(4):600-606 [PMID: 28291091]
  10. Curr Opin Pulm Med. 2023 May 1;29(3):168-173 [PMID: 36917219]
  11. Pneumonia (Nathan). 2022 May 5;14(1):4 [PMID: 35509063]
  12. J Crit Care. 2021 Aug;64:108-113 [PMID: 33845446]
  13. J Coll Physicians Surg Pak. 2011 Jan;21(1):4-8 [PMID: 21276376]
  14. J Infect Public Health. 2019 Sep - Oct;12(5):630-633 [PMID: 30824328]
  15. Curr Opin Crit Care. 2023 Oct 1;29(5):438-445 [PMID: 37641512]
  16. Exp Ther Med. 2015 Nov;10(5):1824-1828 [PMID: 26640556]
  17. Cell Mol Biol (Noisy-le-grand). 2022 Sep 30;68(10):124-129 [PMID: 37114259]
  18. Fam Pract. 2020 Oct 19;37(5):631-636 [PMID: 32473018]
  19. Eur J Clin Microbiol Infect Dis. 2020 May;39(5):965-970 [PMID: 31933017]
  20. J Intensive Care Med. 2020 Dec;35(12):1405-1410 [PMID: 30678533]
  21. Biomedicines. 2021 Jun 08;9(6): [PMID: 34200989]
  22. Int J Clin Pract. 2021 Apr;75(4):e13872 [PMID: 33247984]
  23. Adv Exp Med Biol. 2017;955:39-46 [PMID: 27739023]
  24. Am J Kidney Dis. 2013 May;61(5):649-72 [PMID: 23499048]
  25. Kidney Int. 2010 Mar;77(6):527-35 [PMID: 20032961]
  26. Front Immunol. 2021 Jul 22;12:698121 [PMID: 34367158]
  27. Cochrane Database Syst Rev. 2015 Aug 24;(8):CD007577 [PMID: 26301604]
  28. Curr Environ Health Rep. 2021 Dec;8(4):267-280 [PMID: 34839446]
  29. J Antimicrob Chemother. 2018 Nov 1;73(11):3053-3059 [PMID: 30060117]
  30. JAAPA. 2019 Oct;32(10):18-23 [PMID: 31513034]
  31. Viruses. 2023 Sep 15;15(9): [PMID: 37766340]
  32. Respir Care. 2021 May;66(5):742-750 [PMID: 33593935]

MeSH Term

Humans
Intensive Care Units
Male
Female
Middle Aged
Risk Factors
Aged
Pneumonia, Bacterial
Risk Assessment
Gram-Negative Bacterial Infections
Nomograms
Retrospective Studies
Kaplan-Meier Estimate
ROC Curve
Prognosis
Adult

Word Cloud

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