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. 2022 May 7;61(23):3483–3490. doi: 10.2169/internalmedicine.9124-21

Table 5.

Fine and Gray Regression Analysis Seeking Risk Factors at Diagnosis for Developing Splenic Infarction (n=347).

Univariate analysis Multivariate analysis
HR 95% CI p value HR 95% CI p value
Age >60yr 0.58 0.21-1.63 0.300 - - -
Male 1.48 0.49-4.42 0.486 - - -
Palpable splenomegaly 14.35 5.52-46.09 <0.001 14.89 4.00-55.35 <0.001
WBC >12.0 ×109/L 0.52 0.25-2.03 0.521 - - -
WBC >25.0 ×109/L 3.04 0.63-14.62 0.166 - - -
Monocyte >1.0 ×109/L 2.32 0.71-7.60 0.165
Platelet >1,000 ×109/L 0.25 0.93-1.90 0.177 - - -
LDH >1.5 ×UNL 3.46 1.21-9.88 0.020 2.73 0.88-8.45 0.082
Positive JAK2V617F 1.25 0.04-4.61 0.736 - - -
Positive CALR mutation 0.53 0.06-5.07 0.580
PV 1.51 0.53-4.26 0.440 - - -
pre-PMF 2.66 0.81-8.74 0.108 - - -
PMF 4.11 1.23-12.78 0.022 0.61 0.13-2.92 0.538
Hypertension 0.41 0.13-1.30 0.129 - - -
Diabetes mellitus 1.05 0.29-3.82 0.945 - - -
Chronic kidney disease 0.67 0.15-3.05 0.604 - - -
Smoking 1.71 0.59-4.95 0.320 - - -
Thrombosis before or at diagnosis 0.4 0.0-91.81 0.235 - - -

HR: hazard ratio, CI: confidence interval, LDH: lactate dehydrogenase, UNL: upper normal limit, PV: polycythemia vera, pre-PMF: prefibrotic/early primary myelofibrosis