TABLE 28Probit model: likelihood of a U&E

U&ECoefficientStandard errorz-valuep > |z|
age0.0228550.00059438.470.000
sex−0.0039500.020949−0.190.851
Charlson Score0.2840330.0320648.860.000
opcs41dum20.7976290.1575735.060.000
opcs41dum3−0.0229900.163867−0.140.888
opcs41dum4−0.1708000.193337−0.880.377
opcs41dum50.1146080.1611570.710.477
opcs41dum6−0.0681400.159945−0.430.670
opcs41dum70.8312430.1616835.140.000
opcs41dum80.8416260.1705654.930.000
opcs41dum91.1364250.2090705.440.000
opcs41dum100.4663540.1516333.080.002
opcs41dum110.2567100.1660391.550.122
opcs41dum120.3854610.1618102.380.017
opcs41dum130.1718090.1530651.120.262
opcs41dum140.0651270.1560980.420.677
opcs41dum150.2931850.1540213.200.001
opcs41dum160.2211330.1546491.430.153
opcs41dum170.5200820.3220321.620.106
icd101dum20.0453290,3170820.140.886
icd101dum30.2932130.3352720.870.382
icd101dum40.1906690.3504570.540.586
icd101dum50.1096180.3230550.340.734
icd101dum60.2763150.3480330.790.427
icd101dum7−0.1491600.3365000.270.790
icd101dum80.0862300.3235380.270.790
icd101dum90.2230070.3194660.700.485
icd101dum100.0067080.3234770.020.983
icd101dum11−0.1422000.323248−0.440.660
icd101dum120.0069750.3172390.020.982
icd101dum13−0.5041500.322016−1.570.117
icd101dum140.1887210.3380030.560.577
icd101dum15−0.0153100.318523−0.050.962
icd101dum16−0.1425800.325056−0.440.661
icd101dum17−0.0437800.318076−0.140.891
race2−0.1436000.146939−0.980.328
race30.1478740.1148341.290.198
race4−0.1798900.199040−0.900.366
race50.2758620.3690100.750.455
race60.3435290.2312131.490.137
race70.1871720.2746630.680.496
race8−0.0527900.081704−0.650.518
race90.1410520.0797581.770.077
race10−0.1601200.200413−0.800.424
race110.1187220.1248580.950.342
race12−0.0412800.110269−0.370.708
race130.0488660.1213060.400.687
race14−0.2817800.192301−1.470.143
race15−0.6098300.187086−3.260.001
race160.0469190.1159460.400.687
race17−0.2815700.022645−12.430.000
imd2−0.0312300.034310−0.910.363
imd3−0.0533700.033667−1.590.113
imd4−0.0606600.038563−1.570.116
imd5−0.1651300.036124−4.570.000
imd6−0.0781100.033622−2.320.020
imd7−0.2283200.035911−6.360.000
imd8−0.1770800.041008−4.320.000
imd9−0.1588800.037101−4.280.000
imd10−0.2313200.053657−4.310.000
_cons−1.2634000.351905−3.590.000
Number of obs = 21,742
LR χ2 (60) = 4056.30
Prob > χ2 = 0.0000
Log-likelihood = −12,841.233Pseudo-R2 = 0.1364

age, age in years; Charlson Score, Charlson comorbidity index; fbc, dummy variable for FBC test (1 = had test); icd, surgical procedure ICD10 codes, 17 groups (dummy for each group, base = ICD10); imd, socioeconomic status, IMD04 deciles (dummy for each decile, base = IMD1); max., maximum; min., minimum; opcs, primary diagnosis OPCS4 chapter, 17 groups (dummy for each group, base = OPCS1); race, dummies for ethnicity, 17 groups (dummy for each group, base = race1); SD, standard deviation; sex, dummy variable for sex (1 = female); ue, dummy variable for U&E (1 = had test).

From: 6, Routine pre-operative testing regression analysis report

Cover of What is the Value of Routinely Testing Full Blood Count, Electrolytes and Urea, and Pulmonary Function Tests Before Elective Surgery in Patients with No Apparent Clinical Indication and in Subgroups of Patients with Common Comorbidities: A Systematic Review of the Clinical and Cost-Effective Literature
What is the Value of Routinely Testing Full Blood Count, Electrolytes and Urea, and Pulmonary Function Tests Before Elective Surgery in Patients with No Apparent Clinical Indication and in Subgroups of Patients with Common Comorbidities: A Systematic Review of the Clinical and Cost-Effective Literature.
Health Technology Assessment, No. 16.50.
Czoski-Murray C, Jones ML, McCabe C, et al.
Southampton (UK): NIHR Journals Library; 2012 Dec.
© 2012, Crown Copyright.

Included under terms of UK Non-commercial Government License.

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