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Table 4 Weighted quadratic or linear regression models to predict changes in incidence of primary and secondary outcomes during the study period after adjusting for teaching status and location of the hospitals

From: Baseline hospital performance and the impact of medical emergency teams: Modelling vs. conventional subgroup analysis

  Change of primary outcome Change of unexpected cardiac arrests Change of unplanned ICU admission Change of unexpected death
  Control: quadratic effect Control: linear effect MET Control MET Control MET Control: quadratic effect Control: linear effect MET
Baseline incidence
(per 1000 admissions)
-2.235
(0.042)*
-0.110
(0.692)
-0.523
(0.002)**
-0.980
(<0.001)**
-0.725
(<0.001)**
-0.085
(0.639)
-0.465
(0.010)**
-1.990
(0.021)*
-1.130
(<0.001)**
-0.680
(<0.001)**
Baseline incidence squared 0.128
(0.046)*
       0.229
(0.216)
  
Teaching vs. non-Teaching 0.521
(0.714)
0.338
(0.856)
-0.862
(0.568)
-0.130
(0.706)
-0.592
(0.212)
0.069
(0.960)
-0.285
(0.846)
-0.098
(0.816)
-0.460
(0.200)
-0.141
(0.695)
Rural vs. Urban 0.531
(0.792)
-0.761
(0.766)
-2.787
(0.129)
-0.739
(0.133)
-0.430
(0.393)
-2.051
(0.317)
-2.582
(0.158)
-0.107
(0.813)
-0.347
(0.437)
-0.338
(0.366)
Constant 5.411
(0.258)
-0.455
(0.928)
7.108
(0.106)
2.628
(0.034)*
2.497
(0.068)
1.998
(0.600)
5.231
(0.211)
2.290
(0.065)
2.557
(0.047)*
1.230
(0.242)
R-squared 11 11 12 11 12 11 12 11 11 12
  1. Note: P values (in the parentheses) for the regression coefficients and the constant; control hospitals showed a quadratic effect for only the primary outcome.
  2. * P < 0.05; ** P < 0.01;
  3. Only the MET hospitals showed a linear effect for all of the four outcomes.