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Table 5 Multivariate logistic regression model for dying on the SIPC ward according to symptom clusters

From: Systematic symptom and problem assessment at admission to the palliative care ward – perspectives and prognostic impacts

 

Results of bivariate logistic regression for dying on the SIPC ward

Results of multivariate logistic regression for dying on the SIPC ward

 

β

SE

OR (95% CI)

p

β

SE

OR (95% CI)

p

Age

.025

.004

1.025 (1.017, 1.034)

<.001

.019

.005

1.019 (1.009, 1.029)

<.001

Performance status

 ECOG 3/4

1.451

.174

4.269 (3.035, 6.005)

<.001

.992

.196

2.679 (1.836, 3.961)

<.001

Presence of HOPE-SP-CL symptom cluster

 Deteriorated Physical Condition/Decompensation of Home Care

1.287

.166

3.621 (2.614, 5.017)

<.001

.864

.190

2.372 (1.636, 3.440)

<.001

 Gastrointestinal

-.257

.155

.774 (.571, 1.048)

.098

a

   

 Emotional

.084

.131

1.088 (.841, 1.407)

.521

a

   

Presence of leading symptoms

 Pain (moderate/severe)

.118

.120

1.125 (.889, 1.423)

.327

a

   

 Dyspnea (moderate/severe)

.995

.125

2.706 (2.120, 3.454)

<.001

.895

.135

2.448 (1.877, 3.192)

<.001

  1. Reference group: Patient’s discharge from palliative care ward (binary logistic regression analyses)
  2. Reference values: ECOG: 0–2; HOPE-SP-CL symptom clusters: absence of symptom cluster; single symptoms: no/little pain and dyspnea
  3. Multivariate regression analysis: N = 1082 patients; Nagelkerke’s R2 = .185
  4. ECOG, Performance Status according to the Eastern Co-operative Oncology Group
  5. HOPE-SP-CL, Symptom and Problem Checklist of the German Hospice and Palliative Care Evaluation
  6. SIPC, specialist inpatient palliative care
  7. anot included in multivariate regression model due to result of bivariate analysis