Systemic glucocorticoid exposure and postoperative infection risk in 143,782 appendectomy patients-a Danish longitudinal nationwide study.

BACKGROUND: Glucocorticoids are conventionally associated with increased postoperative infection risk. It is necessary to clarify if preoperative glucocorticoid exposure is associated with postoperative infection in appendectomy patients and if the association is different for open and laparoscopic appendectomies. METHODS: A Danish nationwide study of appendectomy patients between 1996 and 2018. Exposures were defined as high (≥ 5 mg) versus no/low (< 5 mg) glucocorticoid exposure in milligram prednisone-equivalents/day preoperatively. The main outcome was any postoperative infection. Then, 90-day cumulative incidences (absolute risk) and adjusted hazard ratios (relative risk) of the outcome were calculated for high versus no/low glucocorticoid exposure within all appendectomies and within open and laparoscopic subgroups. Propensity-score matching was used for sensitivity analysis. RESULTS: Of 143,782 patients, median age was 29 years, 74,543 were female, and 7654 experienced at least one infection during the 90-day follow-up. The 90-day cumulative incidence for postoperative infection was 5.3% within the no/low glucocorticoid exposure group and 10.0% within the high glucocorticoid exposure group. Compared to no/low glucocorticoid exposure, adjusted hazard ratios for 90-day postoperative infection with high glucocorticoid exposure were 1.25 [95% CI 1.02-1.52; p = 0.03] for all appendectomies, 1.59 [1.16-2.18; p = 0.004] for laparoscopic appendectomies, and 1.09 [0.85-1.40; p = 0.52] for open appendectomies (pinteraction < 0.001). The results were robust to sensitivity analyses. CONCLUSION: Preoperative high (≥ 5 mg/day) glucocorticoid exposure was associated with increased absolute risk of postoperative infections in open and laparoscopic appendectomies. The relative risk increase was significant for laparoscopic but not open appendectomies, possibly due to lower absolute risk with no/low glucocorticoid exposure in the laparoscopic subgroup.

Life after 90: Predictors of mortality and performance of the ACS-NSQIP risk calculator in 4,724 nonagenarian patients undergoing emergency general surgery.

BACKGROUND: The decision to emergently operate on nonagenarian patients (NONAs) can be complex due to the uncertainty about outcomes and goals of care at this advanced age. We sought to study: (1) the outcomes and predictors of mortality for NONAs undergoing emergency general surgery (EGS) and (2) the accuracy of ACS-NSQIP mortality risk calculator in this special population. METHODS: Using the 2007 to 2015 ACS-NSQIP database, we included all patients older than 90 years of age who underwent an emergent operation with a Current Procedural Terminology (CPT) code for "digestive system." Multivariable logistic regression analyses were performed to identify independent predictors of 30-day mortality. NONAs' mortality rates for different combinations of risk factors were also studied and compared to the ACS-NSQIP calculator-predicted mortality rates. RESULTS: Out of a total of 4,456,809 patients, 4,724 NONAs were included. The overall 30-day patient mortality and morbidity rates were 21% and 45%, respectively. In multivariable analyses, several independent predictors of 30-day mortality were identified, including recent history of weight loss, history of steroid use, smoking, functional dependence, hypoalbuminemia and sepsis or septic shock. The mortality among NONAs with a history of steroid use and a recent history of weight loss was 100%. Similarly, the mortality of NONAs with recent history of weight loss who presented with preoperative septic shock was 93%. The ACS-NSQIP calculator significantly and consistently underestimated the risk of mortality in all NONAs undergoing EGS. CONCLUSION: Most NONAs undergoing EGS survive the hospital stay and the first 30 postoperative days, even in the presence of significant preexisting comorbidities. However, the combination of recent weight loss with either steroid use or septic shock nearly ensures mortality and should be used in the discussions with patients and families before a decision to operate is made. The ACS-NSQIP surgical risk calculator should be used with caution in these high-risk patients. LEVEL OF EVIDENCE: Prognostic study, level III.

The effect of resuscitation strategy on the longitudinal immuno-inflammatory response to blunt trauma.

INTRODUCTION: Resuscitation strategies following blunt trauma have been linked to immuno-inflammatory complications leading to systemic inflammatory syndrome (SIRS), sepsis and multiple organ failure (MOF). The effect of resuscitation strategy on longitudinal inflammation marker trajectories is, however, unknown. We hypothesized that the effect of resuscitation strategy extends beyond the trauma-related coagulopathy, perhaps affecting the longitudinal immuno-inflammatory response to injury. METHODS: We analyzed data prospectively collected for the Inflammation and Host Response to Injury (Glue Grant) study. Blood sampling for inflammation marker analyses from blunt trauma patients was done on admission days 0, 1, 4, 7, 14, 21 and 28 where applicable. Total volume transfused of packed red blood cells (PRBC), fresh frozen plasma (FFP), platelets (PLT), and crystalloids during the initial 48h was extracted, along with an analysis for an array of cytokines by Enzyme Linked Immunosorbent Assay (ELISA) technique. A within patient concentration change (WPCC) was calculated to quantify longitudinal alterations in cytokine levels, while controlling for potential confounders. To account for the multiple comparisons performed, p-values obtained from the multivariate regression model were post-hoc corrected by the false detection rate (FDR) q-value. RESULTS: No longitudinal trajectories of inflammatory markers were found to be associated with PRBC- or PLT transfusion. Three proinflammatory cytokines (Il-1ß, MIP-1ß, and TNFR2) were negatively associated with volume of FFP transfused (q=0.02, q<0.001 and q=0.007 respectively), and one proinflammatory cytokine (MIP-1ß) was positively associated with crystalloid infusion (q=0.005). CONCLUSIONS: Resuscitation strategy employed following blunt trauma has limited association to longitudinal inflammation marker trajectories, with a potential association between the strategy employed and IL-1ß, TNFR2, and MIP-1ß trajectories, respectively.

Heavier smoking increases coffee consumption: findings from a Mendelian randomization analysis.

Background: There is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases metabolism of caffeine, so this may represent a causal effect of smoking on caffeine intake. Methods: We performed Mendelian randomization analyses in the UK Biobank (N = 114 029), the Norwegian HUNT study (N = 56 664) and the Copenhagen General Population Study (CGPS) (N = 78 650). We used the rs16969968 genetic variant as a proxy for smoking heaviness in all studies and rs4410790 and rs2472297 as proxies for coffee consumption in UK Biobank and CGPS. Analyses were conducted using linear regression and meta-analysed across studies. Results: Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI: 0.03, 0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI: -0.002, 0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.16 cups per day, 95% CI: 0.11, 0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI: -0.01, 0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers or that the coffee-related variants were associated with cigarette consumption. Conclusions: Higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but could also reflect a behavioural effect of smoking on coffee drinking.

Coffee intake, cardiovascular disease and all-cause mortality: observational and Mendelian randomization analyses in 95 000-223 000 individuals.

Background: Coffee has been associated with modestly lower risk of cardiovascular disease and all-cause mortality in meta-analyses; however, it is unclear whether these are causal associations. We tested first whether coffee intake is associated with cardiovascular disease and all-cause mortality observationally; second, whether genetic variations previously associated with caffeine intake are associated with coffee intake; and third, whether the genetic variations are associated with cardiovascular disease and all-cause mortality. Methods: First, we used multivariable adjusted Cox proportional hazard regression models evaluated with restricted cubic splines to examine observational associations in 95 366 White Danes. Second, we estimated mean coffee intake according to five genetic variations near the AHR (rs4410790; rs6968865) and CYP1A1/2 genes (rs2470893; rs2472297; rs2472299). Third, we used sex- and age adjusted Cox proportional hazard regression models to examine genetic associations with cardiovascular disease and all-cause mortality in 112 509 Danes. Finally, we used sex and age-adjusted logistic regression models to examine genetic associations with ischaemic heart disease including the Cardiogram and C4D consortia in a total of up to 223 414 individuals. We applied similar analyses to ApoE genotypes associated with plasma cholesterol levels, as a positive control. Results: In observational analyses, we observed U-shaped associations between coffee intake and cardiovascular disease and all-cause mortality; lowest risks were observed in individuals with medium coffee intake. Caffeine intake allele score (rs4410790 + rs2470893) was associated with a 42% higher coffee intake. Hazard ratios per caffeine intake allele were 1.02 (95% confidence interval: 1.00-1.03) for ischaemic heart disease, 1.02 (0.99-1.02) for ischaemic stroke, 1.02 (1.00-1.03) for ischaemic vascular disease, 1.02 (0.99-1.06) for cardiovascular mortality and 1.01 (0.99-1.03) for all-cause mortality. Including international consortia, odds ratios per caffeine intake allele for ischaemic heart disease were 1.00 (0.98-1.02) for rs4410790, 1.01 (0.99-1.03) for rs6968865, 1.02 (1.00-1.04) for rs2470893, 1.02 (1.00-1.04) for rs2472297 and 1.03 (0.99-1.06) for rs2472299. Conversely, 5% lower cholesterol level caused by ApoE genotype had a corresponding odds ratio for ischaemic heart disease of 0.93 (0.89-0.97). Conclusions: Observationally, coffee intake was associated with U-shaped lower risk of cardiovascular disease and all-cause mortality; however, genetically caffeine intake was not associated with risk of cardiovascular disease or all-cause mortality.

Coffee intake and risk of obesity, metabolic syndrome and type 2 diabetes: a Mendelian randomization study.

BACKGROUND: Coffee is one of the most widely consumed beverages. We tested the hypothesis that genetically high coffee intake is associated with low risk of obesity, metabolic syndrome and type 2 diabetes, and with related components thereof. METHODS: We included 93,179 individuals from two large general population cohorts in a Mendelian randomization study. We tested first whether high coffee intake is associated with low risk of obesity, metabolic syndrome and type 2 diabetes, and with related components thereof, in observational analyses; second, whether five genetic variants near the CYP1A1, CYP1A2 and AHR genes are associated with coffee intake; and third, whether the genetic variants are associated with obesity, metabolic syndrome and type 2 diabetes, and with related components thereof. Finally, we tested the genetic association with type 2 diabetes in a meta-analysis including up to 78,021 additional individuals from the DIAGRAM consortium. RESULTS: Observationally, high coffee intake was associated with low risk of obesity, metabolic syndrome and type 2 diabetes. Further, high coffee intake was associated with high body mass index, waist circumference, weight, height, systolic/diastolic blood pressure, triglycerides and total cholesterol and with low high-density lipoprotein cholesterol, but not with glucose levels. In genetic analyses, 9-10 vs 0-3 coffee-intake alleles were associated with 29% higher coffee intake. However, genetically derived high coffee intake was not associated convincingly with obesity, metabolic syndrome, type 2 diabetes, body mass index, waist circumference, weight, height, systolic/diastolic blood pressure, triglycerides, total cholesterol, high-density lipoprotein cholesterol or glucose levels. Per-allele meta-analysed odds ratios for type 2 diabetes were 1.01 (0.98-1.04) for AHR rs4410790, 0.98 (0.95-1.01) for AHR rs6968865, 1.01 (0.99-1.03) for CYP1A1/2 rs2470893, 1.01 (0.98-1.03) for CYP1A1/2 rs2472297 and 0.98 (0.95-1.01) for CYP1A1 rs2472299. CONCLUSIONS: High coffee intake was associated observationally with low risk of obesity, metabolic syndrome and type 2 diabetes, and was associated observationally with related components thereof, but with no genetic evidence to support corresponding causal relationships.