Nationwide case–control study of risk factors and outcomes for community-acquired sepsis

Abstract

Sepsis is the main cause of death in the intensive care units (ICU) and increasing incidences of ICU admissions for sepsis are reported. Identification of patients at risk for sepsis and poor outcome is therefore of outmost importance. We performed a nation-wide case–control study aiming at identifying and quantifying the association between co-morbidity and socio-economic factors with intensive care admission for community-acquired sepsis. We also explored 30-day mortality. All adult patients (n = 10,072) with sepsis admitted from an emergency department to an intensive care unit in Sweden between 2008 and 2017 and a control population (n = 50,322), matched on age, sex and county were included. In the sepsis group, 69% had a co-morbid condition at ICU admission, compared to 31% in the control group. Multivariable conditional logistic regression analysis was performed and there was a large variation in the influence of different risk factors associated with ICU-admission, renal disease, liver disease, metastatic malignancy, substance abuse, and congestive heart failure showed the strongest associations. Low income and low education level were more common in sepsis patients compared to controls. The adjusted OR for 30-day mortality for sepsis patients was 132 (95% CI 110–159) compared to controls.

Critical Influenza and COVID-19—A Comparative Nationwide Case-Control Study

“…Congestive heart failure has been shown to increase the risk of ICU admission in community-acquired sepsis (20). This was also seen with influenza and, to a lesser degree, COVID-19 in this study.…”

“…The explanatory mechanisms behind these observations are not fully elucidated, but it has been suggested that this may be related to RAAS and possibly altered expression of ACE 2 ( 19 ). Congestive heart failure has been shown to increase the risk of ICU admission in community-acquired sepsis ( 20 ). This was also seen with influenza and, to a lesser degree, COVID-19 in this study.…”

Explaining sex differences in risk of bloodstream infections using mediation analysis in the population-based HUNT study in Norway

“…We used three distinct sets of mediators measured at inclusion to HUNT2; (1) health behaviours (smoking and alcohol use) and educational attainment; (2) cardiovascular risk factors (body mass index (BMI, kg/m 2 ), systolic blood pressure (mmHg) and non-high-density lipoprotein cholesterol (non-HDL cholesterol, mmol/L); (3) comorbidities defined by self-report of cardiovascular disease (history of myocardial infarction, angina pectoris, and/or stroke), diabetes, cancer history, lung disease (asthma or chronic obstructive pulmonary disease) and standardised measurements of kidney function (estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m 2 ). The three sets of mediators reflect known risk factors for BSI 4 , 20 , 21 . For some of the included mediators there are reports of sex differences in prevalence, pathophysiology and outcomes 28 , 29 .…”

“…Studies on severe infections and sepsis tend to adjust for sex in their analyses 18 but the mechanisms behind the observed sex differences are unexplored 19 . Little is known whether conditions that are known to increase BSI risk, like health behaviours 4 cardiovascular disease risk factors or comorbidity 20 , 21 , contribute to the observed difference in risk of BSI between men and women. Such knowledge may help identify targets for intervention to reduce BSI and sepsis risk.…”

“…To assess the impact of sex as a risk factor for first-time BSI, BSI mortality, and BSI caused by the most common infecting bacteria, Staphylococcus (S.) aureus, Streptococcus (S.) pneumoniae and Escherichia (E.) coli we used data from the Norwegian HUNT study linked with prospectively recorded BSI episodes. Further, we examined if sex differences in health behaviours and education attainment, cardiovascular risk factors and selected comorbidities, which reflect known risk factors for BSI 4 , 20 , 21 may explain the observed sex difference in risk of first-time BSI. We applied sequential mediation analysis 22 using inverse-odds weighting 23 to explore their potential mediating effect on the associations between sex and BSI.…”