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. 2018 Jul 24;41(10):zsy147. doi: 10.1093/sleep/zsy147

Table 5.

Sleep Predicting Future Functional Impairment During Recovery

b 95% CI z p χ2, p
Model 1: Sleep predicting future global functioning during recovery (n = 156, obs = 247)
 Baseline factors 72.01, <.001
  Female gender −.36 −.62, −.09 −2.65 <.01
  Head injury severity −.22 −.35, −.09 −3.41 <.01
  Loss of consciousness −.19 −.44, .06 −1.48 .14
 Recovery factors
  Time .12 −.03, .26 1.56 .12
  Depression, lagged −.03 −.05, −.01 −3.13 <.01
  Sleep disturbance, lagged −.04 −.06, −.01 −2.56 .01
Model 2: Logistic model of sleep predicting future functional impairment (n = 126, obs = 214)
 Baseline factors OR; 95% CI 16.04, .02
  Female gender −1.69 5.26; .83, 33.33 −1.76 .08
  Head injury severity −.92 2.50; 1.02, 6.25 −2.00 <.05
  Loss of consciousness −1.54 4.76; .79, 25.00 −1.70 .09
 Recovery factors
  Time .49 .91 .36
  Depression, lagged −.99 −1.28 .20
  Sleep onset insomnia, lagged −1.96 7.14; 1.56, 33.33 −2.54 .01
  Short sleep, lagged −.87 −1.18 .24
Model 3: Global functioning predicting future sleep (n = 154, obs = 246)
 Baseline factors 85.72, <.001
  Female gender 2.66 1.43, 3.89 4.26 <.001
  Head injury severity −.23 −.84, .39 −.72 .47
  Loss of consciousness .70 −.49, 1.88 1.16 .25
 Recovery factors
  Time .09 −.70, .88 .22 .82
  Depression, lagged .19 .08, .29 3.53 <.001
  Functional impairment, lagged −.86 −1.48, −.24 −2.73 <.01

Global functioning assessed by the GOSE. Functional impairment defined as GOSE ≤ 6. TBI severity assessed by the Glasgow Coma Scale. Head injury severity measured by the AIS, item #1. Loss of consciousness at time of injury was self-reported by patient. Depression measured by the PHQ. Sleep disturbance measured by the PSQI. Sleep latency was estimated in minutes on the PSQI, item #2. Sleep duration was measured by PSQI item #4a. Sleep onset insomnia = rating inability to fall asleep within 30 minutes on three or more nights per week, PSQI item #5a. n = sample size; b = unstandardized regression coefficient; CI = confidence interval; z = z-statistic; p = significance value, which describes whether the model explains greater variance in the outcome than a null model with no predictors. obs = number of observations in model. OR (values are inversed for negative associations to ease interpretability), not reported for parameters with p-values > .10.