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Infection related never events in pediatric patients undergoing spinal fusion procedures in United States: prevalence and predictors.

Publication ,  Journal Article
Allareddy, V; Allareddy, V; Nalliah, RP; Rampa, S; Lee, MK
Published in: PLoS One
2013

OBJECTIVE: To examine the prevalence and predictors of infection related never events (NE) associated with spinal fusion procedures (SFP) in children (age < = 18 years) in the United States. METHODS: We performed a retrospective analysis of the Nationwide Inpatient Sample for the years 2004 to 2008. All pediatric hospitalizations that underwent SFP were selected for analysis. The main outcomes measures include occurrence of certain NE's. The association between the occurrence of a NE and factors (patient & hospital related) were examined using multivariable logistic regression analysis. RESULTS: Of 56,465 hospitalizations, 61.7% occurred among females. The average age was 13.7 y and two-thirds were whites. The major insurance payer was private insurance (67.4%). About 82% of all hospitalizations occurred on an elective basis. Teaching hospitals accounted for a majority of hospitalizations (87.9%). Two-thirds were posterior fusion techniques, 52.3% had underlying musculoskeletal deformities, and the most frequently present co-morbid conditions (CMC) included paralysis (10.9%), chronic pulmonary disease (9.7%), and fluid/electrolyte disorders (7.6%). Overall rate of occurrence of a NE was 4.8%. Post-operative pneumonia was the most frequently occurring NE (2.9%). Female gender (OR = 0.78) and elective admissions (OR = 0.66) were associated with lower risk of NE occurrence. Medicaid coverage (OR = 1.46), primary diagnosis of other acquired deformities (OR = 1.82), spinal cord injury (OR = 6.94), other nervous system disorders (OR = 2.84) were associated with higher risk of NE occurrence. Among CMC, those with chronic blood loss anemia (OR = 2.57), coagulopathy (OR = 1.97), depression (OR = 2), drug abuse (OR = 3.71), fluid/electrolyte disorders (OR = 2.62), neurological disorders (OR = 1.72), paralysis (OR = 1.75), renal failure (OR = 5.45), and weight loss (OR = 4.61) were risk factors for higher odds of a NE occurrence. Hospital teaching status, region, hospital size, and patient race did not influence the occurrence of NE. CONCLUSION: The never events examined in the current study occurred in 4.8% of children hospitalized with SFP. Certain predictors of NE are identified in this study.

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Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2013

Volume

8

Issue

11

Start / End Page

e77540

Location

United States

Related Subject Headings

  • United States
  • Spinal Fusion
  • Risk Factors
  • Retrospective Studies
  • Prevalence
  • Postoperative Complications
  • Pneumonia
  • Musculoskeletal Abnormalities
  • Multivariate Analysis
  • Male
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Allareddy, V., Nalliah, R. P., Rampa, S., & Lee, M. K. (2013). Infection related never events in pediatric patients undergoing spinal fusion procedures in United States: prevalence and predictors. PLoS One, 8(11), e77540. https://doi.org/10.1371/journal.pone.0077540
Allareddy, Veerajalandhar, Veerasathpurush Allareddy, Romesh P. Nalliah, Sankeerth Rampa, and Min Kyeong Lee. “Infection related never events in pediatric patients undergoing spinal fusion procedures in United States: prevalence and predictors.PLoS One 8, no. 11 (2013): e77540. https://doi.org/10.1371/journal.pone.0077540.
Allareddy, Veerajalandhar, et al. “Infection related never events in pediatric patients undergoing spinal fusion procedures in United States: prevalence and predictors.PLoS One, vol. 8, no. 11, 2013, p. e77540. Pubmed, doi:10.1371/journal.pone.0077540.

Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2013

Volume

8

Issue

11

Start / End Page

e77540

Location

United States

Related Subject Headings

  • United States
  • Spinal Fusion
  • Risk Factors
  • Retrospective Studies
  • Prevalence
  • Postoperative Complications
  • Pneumonia
  • Musculoskeletal Abnormalities
  • Multivariate Analysis
  • Male