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Clinical features and direct medical cost of splenic injury in China: a cross-sectional study.


ABSTRACT:

Objectives

This study analyses the clinical features and direct medical cost (DMC) of splenic injury during 2000-2013 in China.

Design

This was a cross-sectional study.

Methods

We used 'The No. 1 Military Medical Project' information system to conduct a retrospective study. Patients' information from 2000 to 2013 were identified. Demographic data, treatment, clinical data and DMC were collected. We performed a generalised linear method (GLM) using gamma distribution to assess the drivers of DMCs.

Results

We included 8083 patients with splenic injury who met the study criteria. Over the 14-year study period, 2782 (34.4%) patients were treated with non-operative management (NOM), 5301 (65.6%) with OM. From 2000 to 2013, the rate of NOM increased from 34.7% to 55.9%, while OM decreased from 65.3% to 44.1%. Mean per-patient DMC in both NOM and OM increased from 2000 to 2013. In GLM analysis, male, old age, length of stay, severe splenic injury grade, OM, intensive care unit, blood transfusion and tertiary hospitals were associated with higher DMC, while female and NOM was associated with lower DMC.

Conclusions

In China, management of splenic injury was the most important factor impacting the total DMC. Proper management and public policy could curtail the burden of splenic injury.

SUBMITTER: Chen Y 

PROVIDER: S-EPMC9185598 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Clinical features and direct medical cost of splenic injury in China: a cross-sectional study.

Chen Yong Y   Liu Yan Y   Ma Yubo Y   Qi Yong Y   Zhang Qiu Q   Zhou Ji-Hong JH  

BMJ open 20220609 6


<h4>Objectives</h4>This study analyses the clinical features and direct medical cost (DMC) of splenic injury during 2000-2013 in China.<h4>Design</h4>This was a cross-sectional study.<h4>Methods</h4>We used 'The No. 1 Military Medical Project' information system to conduct a retrospective study. Patients' information from 2000 to 2013 were identified. Demographic data, treatment, clinical data and DMC were collected. We performed a generalised linear method (GLM) using gamma distribution to asse  ...[more]

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