Pulmonary outcomes following specialized respiratory management for acute cervical spinal cord injury: a retrospective analysis

Abstract

Study design: Retrospective analysis.

Objectives: To identify multivariate interactions of respiratory function that are sensitive to spinal cord injury level and pharmacological treatment to promote strategies that increase successful liberation from mechanical ventilation.

Setting: United States regional spinal cord injury (SCI) treatment center.

Methods: Retrospective chart review of patients consecutively admitted to Santa Clara Valley Medical Center between May 2013 and December 2014 for ventilator weaning with C1-C5 American Spinal Injury Association Impairment Scale (AIS) A or B SCI, <3 months from injury and who had a tracheostomy in place. A nonlinear, categorical principal component analysis (NL-PCA) was performed to test the multivariate interaction of respiratory outcomes from patients (N=36) being weaned off ventilator support after acute SCI with (N=15) or without (N=21) theophylline treatment.

Results: In total, 36 patients met inclusion criteria (2 C1, 5 C2, 11 C3, 14 C4 and 4 C5). The NL-PCA returned three independent components that accounted for 95% of the variance in the data set. Multivariate general linear models hypothesis tests revealed a significant syndromic interaction between theophylline treatment and SCI level (Wilks' Lambda, P=0.028, F (12,64)=2.116, η²=0.256, 1-β=0.838), with post hoc testing demonstrating a significant interaction on PC1, explained by a positive correlation between improved forced vital capacity and time it took to reach 16 h of ventilator-free breathing. Thirty-three patients (92%) achieved 16 h of ventilator-free breathing (VFB) and 30 patients (83%) achieved 24 h of VFB.

Conclusions: We suspect that some portion of the high success rate of ventilator weaning may be attributable to theophylline use in higher cervical SCI, in addition to our aggressive regimen of high volume ventilation, medication optimization and pulmonary toilet (positive pressure treatments and mechanical insufflation-exsufflation).

Figure 1. Statistical analysis workflow

(A) Data distribution of each clinically relevant outcome was assessed to determine the type of statistical tests to use. (B) Correlation matrix of all outcomes used to perform (C) non-linear principal component analysis (NL-PCA) to identify 3 principal components (PC) based on both having eigenvalues greater than 1 whose (D) multivariate outcomes also had face validity to the clinicians that collected the data. (E) Composite PC scores from each multivariate outcome was assigned to each patient and used to map each subject into a 3D space based on their syndromic outcomes generated with NL-PCA. Workflows A-E were all conducted blinded to treatment condition. (F) Hypothesis testing was performed on multivariate outcomes (PC1-PC3) for interactions between type of treatment (group 1 vs group 2) and SCI spinal level on the multivariate space. (G) Individual outcomes tested with the same hypothesis using univariate statistics, demonstrating that only the multivariate outcomes are sufficiently powered for hypothesis testing, whereas individual outcomes separately cannot reliably test these hypotheses.

Figure 2. Multivariate effects of theophylline treatment on respiratory function

(A) NL-PCA (Original) and stability testing (Bootstrapped) of respiratory outcome patterns revealed a 3-factor structure that accounted for 95% of the variance in the dataset. Principal component 1 (PC1) accounted for 48.3% of the variance in the dataset, and represents the positive correlation between FVC best, FVC improved, and time to 16 hours VFB. After bootstrapping the sample, the error range of PC1 remained above a PC loading of 0.4 (vertical dotted lines), suggesting a stable relationship between these 3 variables. PC2 accounted for 27.8% of the variance in the dataset, and represents the positive correlation between BMI, FVC first and FVC best. Bootstrapping the sample revealed error variance in the PC loadings that fell below 0.4 for BMI and first FVC, with only best FVC remaining stable. PC3 accounted for 19.0% of the variance in the dataset, and represents the positive correlation between BMI and time from injury to admission, which remained stable after bootstrapping. (B) Multivariate hypothesis testing of PC scores for each patient (individual dots) identified a significant interaction between theophylline treatment (red color) and SCI level (different shapes) across the full 3D syndromic space that was stable after bootstrapping. (C) Posthoc hypothesis testing for each principal component (PC) showed a significant interaction between treatment and SCI level on PC1.

Figure 3. Univariate effects of theophylline treatment on clinically relevant variables of respiratory function

Box and whisker plots illustrating the full range (boxes) and median values for measures of respiratory function, grouped to test the interaction between SCI level (C1-C5) and theophylline treatment for (A) time to admission after SCI, time to 16 hours of (B) VFB, (C) BMI, (D) first FVC, (E) best FVC and (F) improved FVC. No significant interactions between SCI level and treatment condition were found for any of the measures individually.