Empirical Predictability of Community Responses to Climate Change

Robust predictions of ecosystem responses to climate change are challenging. To achieve such predictions, ecology has extensively relied on the assumption that community states and dynamics are at equilibrium with climate. However, empirical evidence from Quaternary and contemporary data suggest that species communities rarely follow equilibrium dynamics with climate change. This discrepancy between the conceptual foundation of many predictive models and observed community dynamics casts doubts on our ability to successfully predict future community states. Here we used community response diagrams (CRDs) to empirically investigate the occurrence of different classes of disequilibrium responses in plant communities during the Late Quaternary, and bird communities during modern climate warming in North America. We documented a large variability in types of responses including alternate states, suggesting that equilibrium dynamics are not the most common type of response to climate change. Bird responses appeared less predictable to modern climate warming than plant responses to Late Quaternary climate warming. Furthermore, we showed that baseline climate gradients were a strong predictor of disequilibrium states, while ecological factors such as species' traits had a substantial, but inconsistent effect on the deviation from equilibrium. We conclude that (1) complex temporal community dynamics including stochastic responses, lags, and alternate states are common; (2) assuming equilibrium dynamics to predict biodiversity responses to future climate changes may lead to unsuccessful predictions

Empirical Predictability of Community Responses to Climate Change

Robust predictions of ecosystem responses to climate change are challenging. To achieve such predictions, ecology has extensively relied on the assumption that community states and dynamics are at equilibrium with climate. However, empirical evidence from Quaternary and contemporary data suggest that species communities rarely follow equilibrium dynamics with climate change. This discrepancy between the conceptual foundation of many predictive models and observed community dynamics casts doubts on our ability to successfully predict future community states. Here we used community response diagrams (CRDs) to empirically investigate the occurrence of different classes of disequilibrium responses in plant communities during the Late Quaternary, and bird communities during modern climate warming in North America. We documented a large variability in types of responses including alternate states, suggesting that equilibrium dynamics are not the most common type of response to climate change. Bird responses appeared less predictable to modern climate warming than plant responses to Late Quaternary climate warming. Furthermore, we showed that baseline climate gradients were a strong predictor of disequilibrium states, while ecological factors such as species’ traits had a substantial, but inconsistent effect on the deviation from equilibrium. We conclude that (1) complex temporal community dynamics including stochastic responses, lags, and alternate states are common; (2) assuming equilibrium dynamics to predict biodiversity responses to future climate changes may lead to unsuccessful predictions

Risk assessment models for potential use in the emergency department have lower predictive ability in older patients compared to the middle-aged for short-term mortality - a retrospective cohort study

Table S1. Comparison of Baseline characteristics of the TRIAGE II study and TRIAGE III study. Patients above 40 years were included in the current study Table S2. Comparison of AUCs of individual predictors in discriminating short-term mortality of ED patients, grouped according to age: 40–69 years (middle-aged), and 70+ years (older). Figure S1. Area under the Curve (AUC) for Receiver operating characteristics for all-cause mortality within 7 days for acutely admitted patients. Comparison of patients aged 40-69 (Middle-aged, blue colour), and patients aged 70+ (Older, red colour). The graph presents four different approaches of risk assessment of patients acutely presenting at the emergency department. Two different triage algorithms; Adaptive Process Triage (ADAPT) and Copenhagen Triage Algorithm (CTA), a predictive model using four vital signs (heart rate, arterial oxygen saturation, respiratory rate and systolic blood pressure), and a predictive model using levels of seven routine biomarkers (albumin, creatinine, c-reactive protein, haemoglobin, leucocytes, potassium, sodium). (DOCX 241 kb

Temporal Changes, Patient Characteristics, and Mortality, According to Microbiological Cause of Infective Endocarditis:A Nationwide Study

BACKGROUND: Monitoring of microbiological cause of infective endocarditis (IE) remains key in the understanding of IE; however, data from large, unselected cohorts are sparse. We aimed to examine temporal changes, patient characteristics, and in‐hospital and long‐term mortality, according to microbiological cause in patients with IE from 2010 to 2017. METHODS AND RESULTS: Linking Danish nationwide registries, we identified all patients with first‐time IE. In‐hospital and long‐term mortality rates were assessed according to microbiological cause and compared using multivariable adjusted logistic regression analysis and Cox proportional hazard analysis, respectively. A total of 4123 patients were included. Staphylococcus aureus was the most frequent cause (28.1%), followed by Streptococcus species (26.0%), Enterococcus species (15.5%), coagulase‐negative staphylococci (6.2%), and “other microbiological causes” (5.3%). Blood culture–negative IE was registered in 18.9%. The proportion of blood culture–negative IE declined during the study period, whereas no significant changes were seen for any microbiological cause. Patients with Enterococcus species were older and more often had a prosthetic heart valve compared with other causes. For Streptococcus species IE, in‐hospital and long‐term mortality (median follow‐up, 2.3 years) were 11.1% and 58.5%, respectively. Compared with Streptococcus species IE, the following causes were associated with a higher in‐hospital mortality: S aureus IE (odds ratio [OR], 3.48 [95% CI, 2.74–4.42]), Enterococcus species IE (OR, 1.48 [95% CI, 1.11–1.97]), coagulase‐negative staphylococci IE (OR, 1.79 [95% CI, 1.21–2.65]), “other microbiological cause” (OR, 1.47 [95% CI, 0.95–2.27]), and blood culture–negative IE (OR, 1.99 [95% CI, 1.52–2.61]); and the following causes were associated with higher mortality following discharge (median follow‐up, 2.9 years): S aureus IE (hazard ratio [HR], 1.39 [95% CI, 1.19–1.62]), Enterococcus species IE (HR, 1.31 [95% CI, 1.11–1.54]), coagulase‐negative staphylococci IE (HR, 1.07 [95% CI, 0.85–1.36]), “other microbiological cause” (HR, 1.45 [95% CI, 1.13–1.85]), and blood culture–negative IE (HR, 1.05 [95% CI, 0.89–1.25]). CONCLUSIONS: This nationwide study showed that S aureus was the most frequent microbiological cause of IE, followed by Streptococcus species and Enterococcus species. Patients with S aureus IE had the highest in‐hospital mortality

Prevalence and Mortality of Infective Endocarditis in Community-Acquired and Healthcare-Associated Staphylococcus aureus Bacteremia::A Danish Nationwide Registry-Based Cohort Study.

BACKGROUND: Staphylococcus aureus bacteremia (SAB) can be community-acquired or healthcare-associated, and prior small studies have suggested that this mode of acquisition impacts the subsequent prevalence of infective endocarditis (IE) and patient outcomes. METHODS: First-time SAB was identified from 2010 to 2018 using Danish nationwide registries and categorized into community-acquired (no healthcare contact within 30 days) or healthcare-associated (SAB >48 hours of hospital admission, hospitalization within 30 days, or outpatient hemodialysis). Prevalence of IE (defined from hospital codes) was compared between groups using multivariable adjusted logistic regression analysis. One-year mortality of S aureus IE (SAIE) was compared between groups using multivariable adjusted Cox proportional hazard analysis. RESULTS: We identified 5549 patients with community-acquired SAB and 7491 with healthcare-associated SAB. The prevalence of IE was 12.1% for community-acquired and 6.6% for healthcare-associated SAB. Community-acquired SAB was associated with a higher odds of IE as compared with healthcare-associated SAB (odds ratio, 2.12 [95% confidence interval {CI}, 1.86–2.41]). No difference in mortality was observed with 0–40 days of follow-up for community-acquired SAIE as compared with healthcare-associated SAIE (HR, 1.07 [95% CI, .83–1.37]), while with 41–365 days of follow-up, community-acquired SAIE was associated with a lower mortality (HR, 0.71 [95% CI, .53–.95]). CONCLUSIONS: Community-acquired SAB was associated with twice the odds for IE, as compared with healthcare-associated SAB. We identified no significant difference in short-term mortality between community-acquired and healthcare-associated SAIE. Beyond 40 days of survival, community-acquired SAIE was associated with a lower mortality

Surgical treatment of patients with infective endocarditis:changes in temporal use, patient characteristics, and mortality—a nationwide study

BACKGROUND: Valve surgery guidelines for infective endocarditis (IE) are unchanged over decades and nationwide data about the use of valve surgery do not exist. METHODS: We included patients with first-time IE (1999–2018) using Danish nationwide registries. Proportions of valve surgery were reported for calendar periods (1999–2003, 2004–2008, 2009–2013, 2014–2018). Comparing calendar periods in multivariable analyses, we computed likelihoods of valve surgery with logistic regression and rates of 30 day postoperative mortality with Cox regression. RESULTS: We included 8804 patients with first-time IE; 1981 (22.5%) underwent surgery during admission, decreasing by calendar periods (N = 360 [24.4%], N = 483 [24.0%], N = 553 [23.5%], N = 585 [19.7%], P = < 0.001 for trend). For patients undergoing valve surgery, median age increased from 59.7 to 66.9 years (P ≤ 0.001) and the proportion of males increased from 67.8% to 72.6% (P = 0.008) from 1999–2003 to 2014–2018. Compared with 1999–2003, associated likelihoods of valve surgery were: Odds ratio (OR) = 1.14 (95% CI: 0.96–1.35), OR = 1.20 (95% CI: 1.02–1.42), and OR = 1.10 (95% CI: 0.93–1.29) in 2004–2008, 2009–2013, and 2014–2018, respectively. 30 day postoperative mortalities were: 12.7%, 12.8%, 6.9%, and 9.7% by calendar periods. Compared with 1999–2003, associated mortality rates were: Hazard ratio (HR) = 0.96 (95% CI: 0.65–1.41), HR = 0.43 (95% CI: 0.28–0.67), and HR = 0.55 (95% CI 0.37–0.83) in 2004–2008, 2009–2013, and 2014–2018, respectively. CONCLUSIONS: On a nationwide scale, 22.5% of patients with IE underwent valve surgery. Patient characteristics changed considerably and use of valve surgery decreased over time. The adjusted likelihood of valve surgery was similar between calendar periods with a trend towards an increase while rates of 30 day postoperative mortality decreased. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12872-022-02761-z