Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in England
Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research...
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| Autor*in: |
van Staa, Tjeerd Pieter [verfasserIn] Pate, Alexander [verfasserIn] Martin, Glen P. [verfasserIn] Sharma, Anita [verfasserIn] Dark, Paul [verfasserIn] Felton, Tim [verfasserIn] Zhong, Xiaomin [verfasserIn] Bladon, Sian [verfasserIn] Cunningham, Neil [verfasserIn] Gilham, Ellie L. [verfasserIn] Brown, Colin S. [verfasserIn] Mirfenderesky, Mariyam [verfasserIn] Palin, Victoria [verfasserIn] Ashiru-Oredope, Diane [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2024 |
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| Übergeordnetes Werk: |
Enthalten in: Infection - Springer Berlin Heidelberg, 1973, 52(2024), 4 vom: 16. Apr., Seite 1469-1479 |
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| Übergeordnetes Werk: |
volume:52 ; year:2024 ; number:4 ; day:16 ; month:04 ; pages:1469-1479 |
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| DOI / URN: |
10.1007/s15010-024-02235-8 |
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| Katalog-ID: |
SPR056793715 |
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| 245 | 1 | 0 | |a Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in England |
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| 520 | |a Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. Conclusion Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy. | ||
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| 650 | 4 | |a Primary care |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Pate, Alexander |e verfasserin |0 (orcid)0000-0002-0849-3458 |4 aut | |
| 700 | 1 | |a Martin, Glen P. |e verfasserin |0 (orcid)0000-0002-3410-9472 |4 aut | |
| 700 | 1 | |a Sharma, Anita |e verfasserin |4 aut | |
| 700 | 1 | |a Dark, Paul |e verfasserin |0 (orcid)0000-0003-3309-0164 |4 aut | |
| 700 | 1 | |a Felton, Tim |e verfasserin |0 (orcid)0000-0001-6868-6633 |4 aut | |
| 700 | 1 | |a Zhong, Xiaomin |e verfasserin |4 aut | |
| 700 | 1 | |a Bladon, Sian |e verfasserin |4 aut | |
| 700 | 1 | |a Cunningham, Neil |e verfasserin |0 (orcid)0000-0002-8578-7628 |4 aut | |
| 700 | 1 | |a Gilham, Ellie L. |e verfasserin |0 (orcid)0000-0003-4266-4844 |4 aut | |
| 700 | 1 | |a Brown, Colin S. |e verfasserin |0 (orcid)0000-0003-4776-3403 |4 aut | |
| 700 | 1 | |a Mirfenderesky, Mariyam |e verfasserin |0 (orcid)0000-0002-6795-6491 |4 aut | |
| 700 | 1 | |a Palin, Victoria |e verfasserin |0 (orcid)0000-0002-0851-8619 |4 aut | |
| 700 | 1 | |a Ashiru-Oredope, Diane |e verfasserin |0 (orcid)0000-0001-9579-2028 |4 aut | |
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10.1007/s15010-024-02235-8 doi (DE-627)SPR056793715 (SPR)s15010-024-02235-8-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.75 bkl van Staa, Tjeerd Pieter verfasserin (orcid)0000-0001-9363-742X aut Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in England 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. Conclusion Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy. Sepsis (dpeaa)DE-He213 Primary care (dpeaa)DE-He213 Deprivation (dpeaa)DE-He213 Race (dpeaa)DE-He213 Frailty (dpeaa)DE-He213 Pate, Alexander verfasserin (orcid)0000-0002-0849-3458 aut Martin, Glen P. verfasserin (orcid)0000-0002-3410-9472 aut Sharma, Anita verfasserin aut Dark, Paul verfasserin (orcid)0000-0003-3309-0164 aut Felton, Tim verfasserin (orcid)0000-0001-6868-6633 aut Zhong, Xiaomin verfasserin aut Bladon, Sian verfasserin aut Cunningham, Neil verfasserin (orcid)0000-0002-8578-7628 aut Gilham, Ellie L. verfasserin (orcid)0000-0003-4266-4844 aut Brown, Colin S. verfasserin (orcid)0000-0003-4776-3403 aut Mirfenderesky, Mariyam verfasserin (orcid)0000-0002-6795-6491 aut Palin, Victoria verfasserin (orcid)0000-0002-0851-8619 aut Ashiru-Oredope, Diane verfasserin (orcid)0000-0001-9579-2028 aut Enthalten in Infection Springer Berlin Heidelberg, 1973 52(2024), 4 vom: 16. Apr., Seite 1469-1479 (DE-627)31236945X (DE-600)2006315-5 1439-0973 nnns volume:52 year:2024 number:4 day:16 month:04 pages:1469-1479 https://dx.doi.org/10.1007/s15010-024-02235-8 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 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_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_152 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_267 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2472 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.75 VZ AR 52 2024 4 16 04 1469-1479 |
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10.1007/s15010-024-02235-8 doi (DE-627)SPR056793715 (SPR)s15010-024-02235-8-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.75 bkl van Staa, Tjeerd Pieter verfasserin (orcid)0000-0001-9363-742X aut Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in England 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. Conclusion Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy. Sepsis (dpeaa)DE-He213 Primary care (dpeaa)DE-He213 Deprivation (dpeaa)DE-He213 Race (dpeaa)DE-He213 Frailty (dpeaa)DE-He213 Pate, Alexander verfasserin (orcid)0000-0002-0849-3458 aut Martin, Glen P. verfasserin (orcid)0000-0002-3410-9472 aut Sharma, Anita verfasserin aut Dark, Paul verfasserin (orcid)0000-0003-3309-0164 aut Felton, Tim verfasserin (orcid)0000-0001-6868-6633 aut Zhong, Xiaomin verfasserin aut Bladon, Sian verfasserin aut Cunningham, Neil verfasserin (orcid)0000-0002-8578-7628 aut Gilham, Ellie L. verfasserin (orcid)0000-0003-4266-4844 aut Brown, Colin S. verfasserin (orcid)0000-0003-4776-3403 aut Mirfenderesky, Mariyam verfasserin (orcid)0000-0002-6795-6491 aut Palin, Victoria verfasserin (orcid)0000-0002-0851-8619 aut Ashiru-Oredope, Diane verfasserin (orcid)0000-0001-9579-2028 aut Enthalten in Infection Springer Berlin Heidelberg, 1973 52(2024), 4 vom: 16. Apr., Seite 1469-1479 (DE-627)31236945X (DE-600)2006315-5 1439-0973 nnns volume:52 year:2024 number:4 day:16 month:04 pages:1469-1479 https://dx.doi.org/10.1007/s15010-024-02235-8 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 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_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_152 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_267 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2472 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.75 VZ AR 52 2024 4 16 04 1469-1479 |
| allfields_unstemmed |
10.1007/s15010-024-02235-8 doi (DE-627)SPR056793715 (SPR)s15010-024-02235-8-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.75 bkl van Staa, Tjeerd Pieter verfasserin (orcid)0000-0001-9363-742X aut Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in England 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. Conclusion Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy. Sepsis (dpeaa)DE-He213 Primary care (dpeaa)DE-He213 Deprivation (dpeaa)DE-He213 Race (dpeaa)DE-He213 Frailty (dpeaa)DE-He213 Pate, Alexander verfasserin (orcid)0000-0002-0849-3458 aut Martin, Glen P. verfasserin (orcid)0000-0002-3410-9472 aut Sharma, Anita verfasserin aut Dark, Paul verfasserin (orcid)0000-0003-3309-0164 aut Felton, Tim verfasserin (orcid)0000-0001-6868-6633 aut Zhong, Xiaomin verfasserin aut Bladon, Sian verfasserin aut Cunningham, Neil verfasserin (orcid)0000-0002-8578-7628 aut Gilham, Ellie L. verfasserin (orcid)0000-0003-4266-4844 aut Brown, Colin S. verfasserin (orcid)0000-0003-4776-3403 aut Mirfenderesky, Mariyam verfasserin (orcid)0000-0002-6795-6491 aut Palin, Victoria verfasserin (orcid)0000-0002-0851-8619 aut Ashiru-Oredope, Diane verfasserin (orcid)0000-0001-9579-2028 aut Enthalten in Infection Springer Berlin Heidelberg, 1973 52(2024), 4 vom: 16. Apr., Seite 1469-1479 (DE-627)31236945X (DE-600)2006315-5 1439-0973 nnns volume:52 year:2024 number:4 day:16 month:04 pages:1469-1479 https://dx.doi.org/10.1007/s15010-024-02235-8 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 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_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_152 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_267 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2472 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.75 VZ AR 52 2024 4 16 04 1469-1479 |
| allfieldsGer |
10.1007/s15010-024-02235-8 doi (DE-627)SPR056793715 (SPR)s15010-024-02235-8-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.75 bkl van Staa, Tjeerd Pieter verfasserin (orcid)0000-0001-9363-742X aut Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in England 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. Conclusion Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy. Sepsis (dpeaa)DE-He213 Primary care (dpeaa)DE-He213 Deprivation (dpeaa)DE-He213 Race (dpeaa)DE-He213 Frailty (dpeaa)DE-He213 Pate, Alexander verfasserin (orcid)0000-0002-0849-3458 aut Martin, Glen P. verfasserin (orcid)0000-0002-3410-9472 aut Sharma, Anita verfasserin aut Dark, Paul verfasserin (orcid)0000-0003-3309-0164 aut Felton, Tim verfasserin (orcid)0000-0001-6868-6633 aut Zhong, Xiaomin verfasserin aut Bladon, Sian verfasserin aut Cunningham, Neil verfasserin (orcid)0000-0002-8578-7628 aut Gilham, Ellie L. verfasserin (orcid)0000-0003-4266-4844 aut Brown, Colin S. verfasserin (orcid)0000-0003-4776-3403 aut Mirfenderesky, Mariyam verfasserin (orcid)0000-0002-6795-6491 aut Palin, Victoria verfasserin (orcid)0000-0002-0851-8619 aut Ashiru-Oredope, Diane verfasserin (orcid)0000-0001-9579-2028 aut Enthalten in Infection Springer Berlin Heidelberg, 1973 52(2024), 4 vom: 16. Apr., Seite 1469-1479 (DE-627)31236945X (DE-600)2006315-5 1439-0973 nnns volume:52 year:2024 number:4 day:16 month:04 pages:1469-1479 https://dx.doi.org/10.1007/s15010-024-02235-8 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 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_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_152 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_267 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2472 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.75 VZ AR 52 2024 4 16 04 1469-1479 |
| allfieldsSound |
10.1007/s15010-024-02235-8 doi (DE-627)SPR056793715 (SPR)s15010-024-02235-8-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.75 bkl van Staa, Tjeerd Pieter verfasserin (orcid)0000-0001-9363-742X aut Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in England 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. Conclusion Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy. Sepsis (dpeaa)DE-He213 Primary care (dpeaa)DE-He213 Deprivation (dpeaa)DE-He213 Race (dpeaa)DE-He213 Frailty (dpeaa)DE-He213 Pate, Alexander verfasserin (orcid)0000-0002-0849-3458 aut Martin, Glen P. verfasserin (orcid)0000-0002-3410-9472 aut Sharma, Anita verfasserin aut Dark, Paul verfasserin (orcid)0000-0003-3309-0164 aut Felton, Tim verfasserin (orcid)0000-0001-6868-6633 aut Zhong, Xiaomin verfasserin aut Bladon, Sian verfasserin aut Cunningham, Neil verfasserin (orcid)0000-0002-8578-7628 aut Gilham, Ellie L. verfasserin (orcid)0000-0003-4266-4844 aut Brown, Colin S. verfasserin (orcid)0000-0003-4776-3403 aut Mirfenderesky, Mariyam verfasserin (orcid)0000-0002-6795-6491 aut Palin, Victoria verfasserin (orcid)0000-0002-0851-8619 aut Ashiru-Oredope, Diane verfasserin (orcid)0000-0001-9579-2028 aut Enthalten in Infection Springer Berlin Heidelberg, 1973 52(2024), 4 vom: 16. Apr., Seite 1469-1479 (DE-627)31236945X (DE-600)2006315-5 1439-0973 nnns volume:52 year:2024 number:4 day:16 month:04 pages:1469-1479 https://dx.doi.org/10.1007/s15010-024-02235-8 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 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_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_152 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_267 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2472 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.75 VZ AR 52 2024 4 16 04 1469-1479 |
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Enthalten in Infection 52(2024), 4 vom: 16. Apr., Seite 1469-1479 volume:52 year:2024 number:4 day:16 month:04 pages:1469-1479 |
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Enthalten in Infection 52(2024), 4 vom: 16. Apr., Seite 1469-1479 volume:52 year:2024 number:4 day:16 month:04 pages:1469-1479 |
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van Staa, Tjeerd Pieter @@aut@@ Pate, Alexander @@aut@@ Martin, Glen P. @@aut@@ Sharma, Anita @@aut@@ Dark, Paul @@aut@@ Felton, Tim @@aut@@ Zhong, Xiaomin @@aut@@ Bladon, Sian @@aut@@ Cunningham, Neil @@aut@@ Gilham, Ellie L. @@aut@@ Brown, Colin S. @@aut@@ Mirfenderesky, Mariyam @@aut@@ Palin, Victoria @@aut@@ Ashiru-Oredope, Diane @@aut@@ |
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The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. 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| author |
van Staa, Tjeerd Pieter |
| spellingShingle |
van Staa, Tjeerd Pieter ddc 610 bkl 44.75 misc Sepsis misc Primary care misc Deprivation misc Race misc Frailty Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in England |
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van Staa, Tjeerd Pieter |
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610 - Medicine & health |
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van Staa, Tjeerd Pieter Pate, Alexander Martin, Glen P. Sharma, Anita Dark, Paul Felton, Tim Zhong, Xiaomin Bladon, Sian Cunningham, Neil Gilham, Ellie L. Brown, Colin S. Mirfenderesky, Mariyam Palin, Victoria Ashiru-Oredope, Diane |
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sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in england |
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Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case–control study with linked primary care and hospital data in England |
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Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. Conclusion Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy. © The Author(s) 2024 |
| abstractGer |
Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. Conclusion Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy. © The Author(s) 2024 |
| abstract_unstemmed |
Purpose Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. Methods Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65–100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. Results 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37–15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45–1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41–1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72–0.76). Case fatality strongly decreased over calendar time. Conclusion Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy. © The Author(s) 2024 |
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| score |
7.399618 |