Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

A nomogram for predicting the hospital-acquired infections in children with spinal cord injuries: a retrospective, multicenter, observational study

Spinal Cord volume 62, pages 183–191 (2024)Cite this article

Subjects

Study design

Retrospective cohort study.

Objectives

Hospital-acquired infections (HAIs) pose a significant risk for pediatric patients with spinal cord injuries (SCIs), potentially leading to extended hospital stays and increased morbidity. This study aims to identify patients at higher risk for HAIs.

Setting

Hospitals from multiple areas in China.

Methods

This retrospective study included 220 pediatric SCI patients from Jan 2005 to Dec 2023, divided into a training set (n = 154) and a validation set (n = 66). We conducted a multivariate logistic regression analysis to identify risk factors associated with HAIs and constructed a predictive nomogram. The model’s performance was assessed using receiver operating characteristic (ROC) curves, area under the ROC curve (AUC) and calibration plots, while decision curve analysis was utilized to determine clinical utility.

Results

The nomogram incorporated age, time from injury to the hospital, history of urinary and pulmonary infections, urobilinogen positivity, damaged segments, and admission American Spinal Injury Association (ASIA) scores. The model demonstrated excellent discrimination in the training set (AUC = 0.957) and good discrimination in the validation set (AUC = 0.919). Calibration plots indicated an acceptable fit between predicted probabilities and observed outcomes. Decision curve analysis confirmed the model’s net benefit over clinical decision thresholds in both sets.

Conclusion

We developed and validated a predictive nomogram for HAIs in pediatric SCI patients that shows promise for clinical application. The model can assist healthcare providers in identifying patients at higher risk for HAIs, potentially facilitating early interventions and improved patient care strategies.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The design of this study.
Fig. 2: The forest plot for multivariate logistics regression analysis.
Fig. 3: Predictive nomogram for hospital-acquired infections in pediatric spinal cord injury patients.
Fig. 4: Model performance and validation for predicting hospital-acquired infections in pediatric spinal cord injury patients.
Fig. 5: Decision curve analysis of the predictive model for hospital-acquired infections in pediatric SCI patients.

Similar content being viewed by others

Data availability

Deidentified data used to generate the results of this study are available from the corresponding author upon reasonable request.

References

  1. Vogel LC, Betz RR, Mulcahey MJ. Spinal cord injuries in children and adolescents. Handb Clin Neurol. 2012;109:131–48.

    Article  PubMed  Google Scholar 

  2. Howland DR, Trimble SA, Fox EJ, Tester NJ, Spiess MR, Senesac CR, et al. Recovery of walking in nonambulatory children with chronic spinal cord injuries: case series. J Neurosci Res. 2023;101:826–42.

    Article  CAS  PubMed  Google Scholar 

  3. Schottler J, Vogel LC, Sturm P. Spinal cord injuries in young children: a review of children injured at 5 years of age and younger. Dev Med Child Neurol. 2012;54:1138–43.

    Article  PubMed  Google Scholar 

  4. Alizo G, Sciarretta JD, Gibson S, Muertos K, Holmes S, Denittis F, et al. Multidisciplinary team approach to traumatic spinal cord injuries: a single institution’s quality improvement project. Eur J Trauma Emerg Surg. 2018;44:245–50.

    Article  PubMed  Google Scholar 

  5. Linsenmeyer TA, Oakley A. Accuracy of individuals with spinal cord injury at predicting urinary tract infections based on their symptoms. J Spinal Cord Med. 2003;26:352–7.

    Article  PubMed  Google Scholar 

  6. Ahuja CS, Nori S, Tetreault L, Wilson J, Kwon B, Harrop J, et al. Traumatic spinal cord injury. Nat Rev Dis Primers. 2017;3:17018.

    Article  PubMed  Google Scholar 

  7. Sekulić A, Nikolić AK, Bukumirić Z, Trajković G, Corac A, Janković S, et al. Analysis of the factors influencing development of urinary tract infections in patients with spinal cord injuries. Vojnosanit Pregl. 2015;72:1074–9.

    Article  PubMed  Google Scholar 

  8. Kumar R, Lim J, Mekary RA, Rattani A, Dewan MC, Sharif SY, et al. Traumatic spinal injury: global epidemiology and worldwide volume. World Neurosurg. 2018;113:e345–63.

    Article  PubMed  Google Scholar 

  9. Burns SP. Acute respiratory infections in persons with spinal cord injury. Phys Med Rehabil Clin N Am. 2007;18:203–16.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Michael J, Krause JS, Lammertse DP. Recent trends in mortality and causes of death among persons with spinal cord injury. Arch Phys Med Rehabil. 1999;80:1411–9.

    Article  Google Scholar 

  11. Fishburn M, Marino R, Ditunno JJ. Atelectasis and pneumonia in acute spinal cord injury. Arch Phys Med Rehabil. 1990;71:197–200.

    CAS  PubMed  Google Scholar 

  12. Lalwani S, Punia P, Mathur P, Trikha V, Satyarthee G, Misra MC. Hospital acquired infections: preventable cause of mortality in spinal cord injury patients. J Lab Physicians. 2014;6:36–9.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Wang ZM, Zou P, Yang JS, Liu TT, Song LL, Lu Y, et al. Epidemiological characteristics of spinal cord injury in Northwest China: a single hospital-based study. J Orthop Surg Res. 2020;15:214.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Yan L, Ge H, Zhang Y, Li N. Epidemiology of pathogens and antimicrobial resistance of nosocomial urinary tract infections in patients with spinal cord injuries in China: a systematic review and meta-analysis. J Spinal Cord Med. 2023;46:632–48.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Li MP, Liu WC, Wu JB, Luo K, Liu Y, Zhang Y, et al. Machine learning for the prediction of postoperative nosocomial pulmonary infection in patients with spinal cord injury. Eur Spine J. 2023;32:3825–35.

    Article  PubMed  Google Scholar 

  16. Nicolle LE, Buffet L, Alfieri N, Tate R. Nosocomial infections on a rehabilitation unit in an acute care hospital. Infect Control Hosp Epidemiol. 1988;9:553–8.

    Article  CAS  PubMed  Google Scholar 

  17. Wilson JR, Arnold PM, Singh A, Kalsi-Ryan S, Fehlings MG. Clinical prediction model for acute inpatient complications after traumatic cervical spinal cord injury: a subanalysis from the surgical timing in acute spinal cord injury study. J Neurosurg Spine. 2012;17:46–51.

    Article  PubMed  Google Scholar 

  18. Xie Y, Wang Y, Zhou Y, Liu M, Li S, Bao Y, et al. A nomogram for predicting acute respiratory failure after cervical traumatic spinal cord injury based on admission clinical findings. Neurocrit Care. 2022;36:421–33.

    Article  CAS  PubMed  Google Scholar 

  19. Biedron C, Lyman M, Stuckey MJ, Homsy J, Lamorde M, Luvsansharav UO, et al. Evaluation of infection prevention and control readiness at frontline health care facilities in high-risk districts bordering ebola virus disease-affected areas in the Democratic Republic of the Congo - Uganda, 2018. MMWR Morb Mortal Wkly Rep. 2019;68:851–4.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Paul E, Alzaydani Asiri IA, Al-Hakami A, Chandramoorthy HC, Alshehri S, Beynon CM, et al. Healthcare workers’ perspectives on healthcare-associated infections and infection control practices: a video-reflexive ethnography study in the Asir region of Saudi Arabia. Antimicrob Resist Infect Control. 2020;9:110.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kim Y, Cho MH, Do K, Kang HJ, Mok JJ, Kim MK, et al. Incidence and risk factors of urinary tract infections in hospitalised patients with spinal cord injury. J Clin Nurs. 2021;30:2068–78.

    Article  PubMed  Google Scholar 

  22. Fähndrich C, Gemperli A, Baumberger M, Harder M, Roth B, Schaefer DJ, et al. Risk factors of major complications after flap surgery in the treatment of stage III and IV pressure injury in people with spinal cord injury/disorder: a retrospective cohort study. Spinal Cord. 2024;62:34–41.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Southeast University, No. 87 Dingjiaqiao, Nanjing City, Jiangsu Province, 210000, China

    Bo Wang & Yuntao Wang

  2. Department of Orthopaedic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, China

    Bo Wang & Pengfei Zheng

  3. Anhui Province Children’s Hospital, Hefei City, Anhui Province, 230051, China

    Yapeng Zhang

  4. The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, 310009, China

    Wangmi Liu

  5. Zhongda Hospital, Southeast University, Nanjing City, Jiangsu Province, 210000, China

    Lei Liu & Yuntao Wang

Authors
  1. Bo Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pengfei Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yapeng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wangmi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yuntao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Study conception: BW, YW. Data analysis: BW, PZ, YZ. Manuscript draft: BW, WL, LL. Manuscript review: All authors. Approval of final manuscript: All authors.

Corresponding author

Correspondence to Yuntao Wang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical approval

The research methodology secured approval from the Ethical Review Committee of Children’s Hospital of Nanjing Medical University, Zhongda Hospital Affiliated to Southeast University, Anhui Province Children’s Hospital, The Second Affiliated Hospital of Zhejiang University School of Medicine Hospital and aligns with the ethical guidelines set forth by the Declaration of Helsinki.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, B., Zheng, P., Zhang, Y. et al. A nomogram for predicting the hospital-acquired infections in children with spinal cord injuries: a retrospective, multicenter, observational study. Spinal Cord 62, 183–191 (2024). https://doi.org/10.1038/s41393-024-00966-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41393-024-00966-x

Search

Advanced search

Quick links