降钙素原
医学
败血症
重症监护室
阿帕奇II
生物标志物
内科学
疾病严重程度
重症监护医学
急诊医学
生物化学
化学
作者
Nayani Makkar,Manish Soneja,Umang Arora,Rita Sood,Sagnik Biswas,Ranveer Singh Jadon,Ashutosh Biswas,Naveet Wig
标识
DOI:10.1136/jim-2021-002276
摘要
Procalcitonin (PCT) is one of the best validated biomarkers in the management of sepsis. However, its prognostic utility remains poorly studied. The present study sought to assess the prognostic utility of serial PCT assessments in patients with sepsis, and to compare the prognostic predictive capability of serial measurements of PCT with conventional markers of inflammation and validated intensive care unit (ICU) severity scoring systems. We recruited consecutive patients admitted to the medical units of a tertiary care center with suspected or proven bacterial infection and sepsis. Measurement of serum PCT levels, inflammatory markers, and ICU severity scores were performed at admission and repeated every 48 hours subsequently for the duration of hospital stay. 99 patients with bacterial infection and sepsis were recruited and followed until death or discharge. Median serum PCT level was similar between survivors and non-survivors on day 1, but was significantly lower at days 3, 5 and 7 in the survivors. The analysis found Acute Physiology and Chronic Health Evaluation (APACHE IV) score on all days (1, 3, 5, and 7), PCT on days 5 and 7, and Sequential Organ Failure Assessment score at 24 hours to have good predictive accuracy for adverse patient outcome. PCT clearance on days 3 and 5 of admission was measured and demonstrated predictive accuracy comparable to day-matched APACHE IV scores. While serial levels of serum PCT in patients with sepsis are accurate in the prediction of adverse patient outcome, they do not offer any additional clinical benefit over existing severity of illness scores and may be cost prohibitive in resource-limited settings. While serial levels of serum PCT in patients with sepsis are accurate in the prediction of adverse patient outcome, they do not offer any additional clinical benefit over existing severity of illness scores and may be cost prohibitive in resource-limited settings.
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