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Table 2 Influential factors for pulmonary TB cases confirmed by bacteriology and bacteriologically confirmed cases tested for drug resistance

From: Impact of multiple policy interventions on the screening and diagnosis of drug-resistant tuberculosis patients: a cascade analysis on six prefectures in China

Variables

Model 1

TB cases confirmed by bacteriology

Model 2

Bacteriologically confirmed cases tested for drug resistance

β

S.E

P value

OR

β

S.E

P value

OR

Smear test as base

        

 Rapid molecular testing

0.107

0.027

 < 0.001

1.113

/

/

/

/

DST coverage: suspected high-risk DR-TB patients as base

 Smear positive TB patients

/

/

/

/

0.931

0.042

 < 0.001

2.537

 Smear positive or culture positive TB patients

/

/

/

/

0.834

0.042

 < 0.001

2.304

 Biologically confirmed TB patients

/

/

/

/

1.345

0.043

 < 0.001

3.839

Year

0.174

0.005

 < 0.001

1.190

0.196

0.009

 < 0.001

1.217

Prefecture: Zhenjiang as base

 Changzhou

− 0.139

0.032

 < 0.001

0.870

− 0.030

0.035

0.395

0.971

 Huai’an

− 0.273

0.035

 < 0.001

0.761

− 0.491

0.043

 < 0.001

0.612

 Lianyungang

0.014

0.042

0.734

1.014

0.016

0.051

0.759

1.016

 Nantong

− 0.312

0.027

0.000

0.732

− 0.410

0.034

 < 0.001

0.664

 Yangzhou

− 0.109

0.035

0.002

0.897

− 0.212

0.044

 < 0.001

0.809

Gender: male as base

 Female

0.144

0.017

 < 0.001

1.155

0.248

0.021

 < 0.001

1.281

Age group: over 60 as base (years)

 < 45

− 0.407

0.019

 < 0.001

0.666

− 0.335

0.022

 < 0.001

0.715

 45–60

− 0.292

0.019

 < 0.001

0.747

− 0.250

0.022

 < 0.001

0.779

Treatment: new as base

 Retreatment

0.721

0.022

 < 0.001

2.057

0.888

0.024

 < 0.001

2.430

Cavitary disease: no as base

 Yes

0.078

0.037

0.034

1.081

0.052

0.041

0.206

1.053

Administrative level of diagnosis agency: county level as base

 Prefecture level

− 0.087

0.029

0.003

0.916

− 0.304

0.033

0.000

0.738

Type of current diagnosis agency: general hospitals as base

 Specialized hospitals

− 0.092

0.024

 < 0.001

0.912

− 0.087

0.027

0.001

0.916

 CDC or TB dispensary

− 0.221

0.035

 < 0.001

0.802

− 0.247

0.043

 < 0.001

0.781

Current residency: within county as base

 Within prefecture

0.001

0.025

0.965

1.001

− 0.150

0.029

 < 0.001

0.861

 Within province

0.344

0.060

 < 0.001

1.410

− 0.456

0.082

 < 0.001

0.634

 Outside province

0.346

0.082

 < 0.001

1.414

− 0.214

0.102

0.036

0.808

Constant

− 1.074

0.057

 < 0.001

0.342

− 397.045

17.935

 < 0.001

0.000

 − 2 Log likelihood

98,704.781

77,168.226

 Cox & Snell R Square

0.066

0.135

 Nagelkerke R Square

0.090

0.200

  1. “/” means indicator not included in the model; OR: odd ratio