Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study
Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Marković, Danica Z. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer International Publishing AG 2017 |
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| Übergeordnetes Werk: |
Enthalten in: Aging clinical and experimental research - Berlin : Heidelberg : Springer, 2002, 30(2017), 5 vom: 27. Juli, Seite 419-431 |
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| Übergeordnetes Werk: |
volume:30 ; year:2017 ; number:5 ; day:27 ; month:07 ; pages:419-431 |
| Links: |
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| DOI / URN: |
10.1007/s40520-017-0805-9 |
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SPR036613967 |
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| 245 | 1 | 0 | |a Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study |
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| 520 | |a Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. Conclusions Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers. | ||
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| 700 | 1 | |a Živković, Bojana Marković |4 aut | |
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10.1007/s40520-017-0805-9 doi (DE-627)SPR036613967 (SPR)s40520-017-0805-9-e DE-627 ger DE-627 rakwb eng Marković, Danica Z. verfasserin (orcid)0000-0001-9472-8868 aut Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer International Publishing AG 2017 Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. Conclusions Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers. Period (dpeaa)DE-He213 Preoperative; survivin protein (dpeaa)DE-He213 Human; H-FABP (dpeaa)DE-He213 Human; hsCRP (dpeaa)DE-He213 Human (dpeaa)DE-He213 Jevtović-Stoimenov, Tatjana aut Ćosić, Vladan aut Stošić, Biljana aut Živković, Bojana Marković aut Janković, Radmilo J. aut Enthalten in Aging clinical and experimental research Berlin : Heidelberg : Springer, 2002 30(2017), 5 vom: 27. Juli, Seite 419-431 (DE-627)369554930 (DE-600)2119282-0 1720-8319 nnns volume:30 year:2017 number:5 day:27 month:07 pages:419-431 https://dx.doi.org/10.1007/s40520-017-0805-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2017 5 27 07 419-431 |
| spelling |
10.1007/s40520-017-0805-9 doi (DE-627)SPR036613967 (SPR)s40520-017-0805-9-e DE-627 ger DE-627 rakwb eng Marković, Danica Z. verfasserin (orcid)0000-0001-9472-8868 aut Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer International Publishing AG 2017 Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. Conclusions Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers. Period (dpeaa)DE-He213 Preoperative; survivin protein (dpeaa)DE-He213 Human; H-FABP (dpeaa)DE-He213 Human; hsCRP (dpeaa)DE-He213 Human (dpeaa)DE-He213 Jevtović-Stoimenov, Tatjana aut Ćosić, Vladan aut Stošić, Biljana aut Živković, Bojana Marković aut Janković, Radmilo J. aut Enthalten in Aging clinical and experimental research Berlin : Heidelberg : Springer, 2002 30(2017), 5 vom: 27. Juli, Seite 419-431 (DE-627)369554930 (DE-600)2119282-0 1720-8319 nnns volume:30 year:2017 number:5 day:27 month:07 pages:419-431 https://dx.doi.org/10.1007/s40520-017-0805-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2017 5 27 07 419-431 |
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10.1007/s40520-017-0805-9 doi (DE-627)SPR036613967 (SPR)s40520-017-0805-9-e DE-627 ger DE-627 rakwb eng Marković, Danica Z. verfasserin (orcid)0000-0001-9472-8868 aut Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer International Publishing AG 2017 Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. Conclusions Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers. Period (dpeaa)DE-He213 Preoperative; survivin protein (dpeaa)DE-He213 Human; H-FABP (dpeaa)DE-He213 Human; hsCRP (dpeaa)DE-He213 Human (dpeaa)DE-He213 Jevtović-Stoimenov, Tatjana aut Ćosić, Vladan aut Stošić, Biljana aut Živković, Bojana Marković aut Janković, Radmilo J. aut Enthalten in Aging clinical and experimental research Berlin : Heidelberg : Springer, 2002 30(2017), 5 vom: 27. Juli, Seite 419-431 (DE-627)369554930 (DE-600)2119282-0 1720-8319 nnns volume:30 year:2017 number:5 day:27 month:07 pages:419-431 https://dx.doi.org/10.1007/s40520-017-0805-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2017 5 27 07 419-431 |
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10.1007/s40520-017-0805-9 doi (DE-627)SPR036613967 (SPR)s40520-017-0805-9-e DE-627 ger DE-627 rakwb eng Marković, Danica Z. verfasserin (orcid)0000-0001-9472-8868 aut Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer International Publishing AG 2017 Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. Conclusions Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers. Period (dpeaa)DE-He213 Preoperative; survivin protein (dpeaa)DE-He213 Human; H-FABP (dpeaa)DE-He213 Human; hsCRP (dpeaa)DE-He213 Human (dpeaa)DE-He213 Jevtović-Stoimenov, Tatjana aut Ćosić, Vladan aut Stošić, Biljana aut Živković, Bojana Marković aut Janković, Radmilo J. aut Enthalten in Aging clinical and experimental research Berlin : Heidelberg : Springer, 2002 30(2017), 5 vom: 27. Juli, Seite 419-431 (DE-627)369554930 (DE-600)2119282-0 1720-8319 nnns volume:30 year:2017 number:5 day:27 month:07 pages:419-431 https://dx.doi.org/10.1007/s40520-017-0805-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2017 5 27 07 419-431 |
| allfieldsSound |
10.1007/s40520-017-0805-9 doi (DE-627)SPR036613967 (SPR)s40520-017-0805-9-e DE-627 ger DE-627 rakwb eng Marković, Danica Z. verfasserin (orcid)0000-0001-9472-8868 aut Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer International Publishing AG 2017 Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. Conclusions Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers. Period (dpeaa)DE-He213 Preoperative; survivin protein (dpeaa)DE-He213 Human; H-FABP (dpeaa)DE-He213 Human; hsCRP (dpeaa)DE-He213 Human (dpeaa)DE-He213 Jevtović-Stoimenov, Tatjana aut Ćosić, Vladan aut Stošić, Biljana aut Živković, Bojana Marković aut Janković, Radmilo J. aut Enthalten in Aging clinical and experimental research Berlin : Heidelberg : Springer, 2002 30(2017), 5 vom: 27. Juli, Seite 419-431 (DE-627)369554930 (DE-600)2119282-0 1720-8319 nnns volume:30 year:2017 number:5 day:27 month:07 pages:419-431 https://dx.doi.org/10.1007/s40520-017-0805-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2017 5 27 07 419-431 |
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Enthalten in Aging clinical and experimental research 30(2017), 5 vom: 27. Juli, Seite 419-431 volume:30 year:2017 number:5 day:27 month:07 pages:419-431 |
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Enthalten in Aging clinical and experimental research 30(2017), 5 vom: 27. Juli, Seite 419-431 volume:30 year:2017 number:5 day:27 month:07 pages:419-431 |
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Marković, Danica Z. @@aut@@ Jevtović-Stoimenov, Tatjana @@aut@@ Ćosić, Vladan @@aut@@ Stošić, Biljana @@aut@@ Živković, Bojana Marković @@aut@@ Janković, Radmilo J. @@aut@@ |
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2017-07-27T00:00:00Z |
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Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. 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Marković, Danica Z. |
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Marković, Danica Z. misc Period misc Preoperative; survivin protein misc Human; H-FABP misc Human; hsCRP misc Human Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study |
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Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study Period (dpeaa)DE-He213 Preoperative; survivin protein (dpeaa)DE-He213 Human; H-FABP (dpeaa)DE-He213 Human; hsCRP (dpeaa)DE-He213 Human (dpeaa)DE-He213 |
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Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study |
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Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study |
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Marković, Danica Z. |
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Marković, Danica Z. Jevtović-Stoimenov, Tatjana Ćosić, Vladan Stošić, Biljana Živković, Bojana Marković Janković, Radmilo J. |
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Marković, Danica Z. |
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addition of biomarker panel improves prediction performance of american college of surgeons national surgical quality improvement program (acs nsqip) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study |
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Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study |
| abstract |
Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. Conclusions Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers. © Springer International Publishing AG 2017 |
| abstractGer |
Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. Conclusions Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers. © Springer International Publishing AG 2017 |
| abstract_unstemmed |
Background Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate. Aims To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients. Methods This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories. Results Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality. Discussion ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors. Conclusions Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers. © Springer International Publishing AG 2017 |
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Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study |
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https://dx.doi.org/10.1007/s40520-017-0805-9 |
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Jevtović-Stoimenov, Tatjana Ćosić, Vladan Stošić, Biljana Živković, Bojana Marković Janković, Radmilo J. |
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Jevtović-Stoimenov, Tatjana Ćosić, Vladan Stošić, Biljana Živković, Bojana Marković Janković, Radmilo J. |
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| score |
7.4002237 |