14 research outputs found

    The combination of kidney function variables with cell cycle arrest biomarkers identifies distinct subphenotypes of sepsis-associated acute kidney injury: a <i>post-hoc</i> analysis (the PHENAKI study)

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    The severity and course of sepsis-associated acute kidney injury (SA-AKI) are correlated with the mortality rate. Early detection of SA-AKI subphenotypes might facilitate the rapid provision of individualized care. In this post-hoc analysis of a multicenter prospective study, we combined conventional kidney function variables with serial measurements of urine (tissue inhibitor of metalloproteinase-2 [TIMP-2])* (insulin-like growth factor-binding protein [IGFBP7]) at 0, 6, 12, and 24 h) and then using an unsupervised hierarchical clustering of principal components (HCPC) approach to identify different phenotypes of SA-AKI. We then compared the subphenotypes with regard to a composite outcome of in-hospital death or the initiation of renal replacement therapy (RRT). We included 184 patients presenting SA-AKI within 6 h of the initiation of catecholamines. Three distinct subphenotypes were identified: subphenotype A (99 patients) was characterized by a normal urine output (UO), a low SCr and a low [TIMP-2]*[IGFBP7] level; subphenotype B (74 patients) was characterized by existing chronic kidney disease (CKD), a higher SCr, a low UO, and an intermediate [TIMP-2]*[IGFBP7] level; and subphenotype C was characterized by very low UO, a very high [TIMP-2]*[IGFBP7] level, and an intermediate SCr level. With subphenotype A as the reference, the adjusted hazard ratio (aHR) [95%CI] for the composite outcome was 3.77 [1.92–7.42] (p p = 0.004) for subphenotype C. Combining conventional kidney function variables with urine measurements of [TIMP-2]*[IGFBP7] might help to identify distinct SA-AKI subphenotypes with different short-term courses and survival rates.</p

    Demographic and epidemiological characteristics of the studied population at the admission to the ICU; management, ICU length of stay and mortality.

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    <p>BMI: body mass index; SAPS II: simplified acute physiology score II; ICU: intensive care unit; LOS: length of stay; “SAMU”: <b>S</b>ervice d’<b>A</b>ide <b>M</b>édicale <b>U</b>rgente: mobile emergency team.</p

    Univariate Cox model of factors associated with ICU mortality.

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    <p>* As compared with female; Ref: reference category; reduced staff: weekend and public holydays admissions; RRT: renal replacement therapy; “SAMU”: <b>S</b>ervice d’<b>A</b>ide <b>M</b>édicale <b>U</b>rgente: mobile emergency team.</p

    Characteristics of patients admitted per time variable regardless of type of the day (working days or not).

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    <p>BMI: body mass index; SAPS II: simplified acute physiology score II; ICU: intensive care unit; LOS: length of stay; “SAMU”: <b>S</b>ervice d’<b>A</b>ide <b>M</b>édicale <b>U</b>rgente: mobile emergency team; MV: mechanical ventilation. p = significance as compared to group admitted from 08:00 to 17:59.</p

    Comparison of patients admitted during on-hours to those admitted during weeknights, and to those admitted during weekends and public holidays.

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    <p>Weekend admission was defined as admission between 08:00 am Sunday and 7:59 am Monday; BMI: body mass index; SAPS II: simplified acute physiology score II; ICU: intensive care unit; LOS: length of stay; “SAMU”: Service d’Aide Médicale Urgente: mobile emergency team; p: On-hours vs Week-night; p*: On-hours vs weekends and public holidays.</p

    Multivariate Cox model of factors associated with ICU mortality.

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    <p>Included variables in the analysis: age, sex, BMI, SAPS II, nutritional status, admission source, hospital admission category, reason for admission, life support treatments.</p

    Comparison of patients admitted during on-hours and off-hours.

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    <p>BMI: body mass index; SAPS II: simplified acute physiology score II; ICU: intensive care unit; LOS: length of stay; “SAMU”: <b>S</b>ervice d’<b>A</b>ide <b>M</b>édicale <b>U</b>rgente: mobile emergency team.</p
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