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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Improved prediction of all-cause mortality by a combination of serum total testosterone and insulin-like growth factor I in adult men

Friedrich, Nele, Schneider, Harald J., Haring, Robin, Nauck, Matthias, Völzke, Henry, Kroemer, Heyo K., Dörr, Marcus, Klotsche, Jens, Jung-Sievers, Caroline, Pittrow, David, Lehnert, Hendrik, März, Winfried, Pieper, Lars, Wittchen, Hans-Ulrich, Wallaschofski, Henri, Stalla, Günter K. 10 September 2013 (has links) (PDF)
Objective: Lower levels of anabolic hormones in older age are well documented. Several studies suggested that low insulin-like growth factor I (IGF-I) or testosterone levels were related to increased mortality. The aim of the present study was to investigate the combined influence of low IGF-I and low testosterone on all-cause mortality in men. Methods and results: From two German prospective cohort studies, the DETECT study and SHIP, 3942 men were available for analyses. During 21,838 person-years of follow-up, 8.4% (n = 330) of men died. Cox model analyses with age as timescale and adjusted for potential confounders revealed that men with levels below the 10th percentile of at least one hormone [hazard ratio (HR) 1.38 (95% confidence-interval (CI) 1.06–1.78), p = 0.02] and two hormones [HR 2.88 (95% CI 1.32–6.29), p < 0.01] showed a higher risk of all-cause mortality compared to men with non-low hormones. The associations became non-significant by using the 20th percentile as cut-off showing that the specificity increased with lower cut-offs for decreased hormone levels. The inclusion of both IGF-I and total testosterone in a mortality prediction model with common risk factors resulted in a significant integrated discrimination improvement of 0.5% (95% CI 0.3–0.7%, p = 0.03). Conclusions: Our results prove that multiple anabolic deficiencies have a higher impact on mortality than a single anabolic deficiency and suggest that assessment of more than one anabolic hormone as a biomarker improve the prediction of all-cause mortality.
2

Improved prediction of all-cause mortality by a combination of serum total testosterone and insulin-like growth factor I in adult men

Friedrich, Nele, Schneider, Harald J., Haring, Robin, Nauck, Matthias, Völzke, Henry, Kroemer, Heyo K., Dörr, Marcus, Klotsche, Jens, Jung-Sievers, Caroline, Pittrow, David, Lehnert, Hendrik, März, Winfried, Pieper, Lars, Wittchen, Hans-Ulrich, Wallaschofski, Henri, Stalla, Günter K. January 2012 (has links)
Objective: Lower levels of anabolic hormones in older age are well documented. Several studies suggested that low insulin-like growth factor I (IGF-I) or testosterone levels were related to increased mortality. The aim of the present study was to investigate the combined influence of low IGF-I and low testosterone on all-cause mortality in men. Methods and results: From two German prospective cohort studies, the DETECT study and SHIP, 3942 men were available for analyses. During 21,838 person-years of follow-up, 8.4% (n = 330) of men died. Cox model analyses with age as timescale and adjusted for potential confounders revealed that men with levels below the 10th percentile of at least one hormone [hazard ratio (HR) 1.38 (95% confidence-interval (CI) 1.06–1.78), p = 0.02] and two hormones [HR 2.88 (95% CI 1.32–6.29), p < 0.01] showed a higher risk of all-cause mortality compared to men with non-low hormones. The associations became non-significant by using the 20th percentile as cut-off showing that the specificity increased with lower cut-offs for decreased hormone levels. The inclusion of both IGF-I and total testosterone in a mortality prediction model with common risk factors resulted in a significant integrated discrimination improvement of 0.5% (95% CI 0.3–0.7%, p = 0.03). Conclusions: Our results prove that multiple anabolic deficiencies have a higher impact on mortality than a single anabolic deficiency and suggest that assessment of more than one anabolic hormone as a biomarker improve the prediction of all-cause mortality.

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