Response to: the metabolic cost of whistling is low but measurable in dolphins

Author Posting. © Company of Biologists, 2020. This article is posted here by permission of Company of Biologists for personal use, not for redistribution. The definitive version was published in Journal of Experimental Biology 223(11), (2020): jeb224915, doi: 10.1242/jeb.224915.Costs of sound production have been investigated only sparsely incetaceans, despite recent efforts to understand how increasinganthropogenic noise affects these animals that rely extensively onsound for communication and foraging. Theoretical estimates suggestthat metabolic costs of whistling for bottlenose dolphins should be<0.54% of resting metabolic rate (RMR) (Jensen et al., 2012),whereas empirical studies of a single whistling dolphin surprisinglyclaimed that sound production costs were around 20% of RMR (Holtet al., 2015; Noren et al., 2013). Addressing this discrepancy, wefound that costs of whistling were significantly less than 20% RMRand not statistically different from theoretical estimates (Pedersenet al., 2020). In their correspondence, Noren et al., 2020 argue thatthey did not claim whistling was‘costly’and questioned aspects ofour methods, and we address these points here.2021-06-0

Potassium Disturbances and Risk of Ventricular Fibrillation Among Patients With ST-Segment-Elevation Myocardial Infarction

Background Potassium disturbances per se increase the risk of ventricular fibrillation (VF). Whether potassium disturbances in the acute phase of ST-segment-elevation myocardial infarction (STEMI) are associated with VF before primary percutaneous coronary intervention (PPCI) is uncertain. Methods and Results All consecutive STEMI patients were identified in the Eastern Danish Heart Registry from 1999 to 2016. Comorbidities and medication use were assessed from Danish nationwide registries. Potassium levels were collected immediately before PPCI start. Multivariate logistic models were performed to determine the association between potassium and VF. The main analysis included 8624 STEMI patients of whom 822 (9.5%) had VF before PPCI. Compared with 6693 (77.6%) patients with normokalemia (3.5-5.0 mmol/L), 1797 (20.8%) patients with hypokalemia (5.0 mmol/L) were older with more comorbidities. After adjustment, patients with hypokalemia and hyperkalemia had a higher risk of VF before PPCI (odds ratio 1.90, 95% CI 1.57-2.30, P<0.001) and (odds ratio 3.36, 95% CI 1.95-5.77, P<0.001) compared with normokalemia, respectively. Since the association may reflect a post-resuscitation phenomenon, a sensitivity analysis was performed including 7929 STEMI patients without VF before PPCI of whom 127 (1.6%) had VF during PPCI. Compared with normokalemia, patients with hypokalemia had a significant association with VF during PPCI (odds ratio 1.68, 95% CI 1.01-2.77, P=0.045) after adjustment. Conclusions Hypokalemia and hyperkalemia are associated with increased risk of VF before PPCI during STEMI. For hypokalemia, the association may be independent of the measurement of potassium before or after VF

Effect of implantable cardioverter-defibrillators in patients with non-ischaemic systolic heart failure and concurrent coronary atherosclerosis

AIMS: Prophylactic implantable cardioverter‐defibrillators (ICD) reduce mortality in patients with ischaemic heart failure (HF), whereas the effect of ICD in patients with non‐ischaemic HF is less clear. We aimed to investigate the association between concomitant coronary atherosclerosis and mortality in patients with non‐ischaemic HF and the effect of ICD implantation in these patients. METHODS AND RESULTS: Patients were included from DANISH (Danish Study to Assess the Efficacy of Implantable Cardioverter Defibrillators in Patients with Non‐Ischaemic Systolic Heart Failure on Mortality), randomizing patients to ICD or control. Study inclusion criteria for HF were left ventricular ejection fraction ≤ 35% and increased levels (>200 pg/mL) of N‐terminal pro‐brain natriuretic peptide. Of the 1116 patients from DANISH, 838 (75%) patients had available data from coronary angiogram and were included in this subgroup analysis. We used Cox regression to assess the relationship between coronary atherosclerosis and mortality and the effect of ICD implantation. Of the included patients, 266 (32%) had coronary atherosclerosis. Of these, 216 (81%) had atherosclerosis without significant stenoses, and 50 (19%) had significant stenosis. Patients with atherosclerosis were significantly older {67 [interquartile range (IQR) 61–73] vs. 61 [IQR 54–68] years; P < 0.0001}, and more were men (77% vs. 70%; P = 0.03). During a median follow‐up of 64.3 months (IQR 47–82), 174 (21%) of the patients died. The effect of ICD on all‐cause mortality was not modified by coronary atherosclerosis [hazard ratio (HR) 0.94; 0.58–1.52; P = 0.79 vs. HR 0.82; 0.56–1.20; P = 0.30], P for interaction = 0.67. In univariable analysis, coronary atherosclerosis was a significant predictor of all‐cause mortality [HR, 1.41; 95% confidence interval (CI), 1.04–1.91; P = 0.03]. However, this association disappeared when adjusting for cardiovascular risk factors (age, gender, diabetes, hypertension, smoking, and estimated glomerular filtration rate) (HR 1.05, 0.76–1.45, P = 0.76). CONCLUSIONS: In patients with non‐ischaemic systolic heart failure, ICD implantation did not reduce all‐cause mortality in patients either with or without concomitant coronary atherosclerosis. The concomitant presence of coronary atherosclerosis was associated with increased mortality. However, this association was explained by other risk factors

MR-proADM as a Prognostic Marker in Patients With ST-Segment-Elevation Myocardial Infarction - DANAMI-3 (a Danish Study of Optimal Acute Treatment of Patients With STEMI) Substudy

Background Midregional proadrenomedullin ( MR ‐pro ADM ) has demonstrated prognostic potential after myocardial infarction ( MI ). Yet, the prognostic value of MR ‐pro ADM at admission has not been examined in patients with ST‐segment–elevation MI ( STEMI ). Methods and Results The aim of this substudy, DANAMI‐3 (The Danish Study of Optimal Acute Treatment of Patients with ST ‐segment–elevation myocardial infarction), was to examine the associations of admission concentrations of MR ‐pro ADM with short‐ and long‐term mortality and hospital admission for heart failure in patients with ST ‐segment–elevation myocardial infarction. Outcomes were assessed using Cox proportional hazard models and area under the curve using receiver operating characteristics. In total, 1122 patients were included. The median concentration of MR ‐pro ADM was 0.64 nmol/L (25th–75th percentiles, 0.53–0.79). Within 30 days 23 patients (2.0%) died and during a 3‐year follow‐up 80 (7.1%) died and 38 (3.4%) were admitted for heart failure. A doubling of MR ‐pro ADM was, in adjusted models, associated with an increased risk of 30‐day mortality (hazard ratio, 2.67; 95% confidence interval, 1.01–7.11; P =0.049), long‐term mortality (hazard ratio, 3.23; 95% confidence interval, 1.97–5.29; P &lt;0.0001), and heart failure (hazard ratio, 2.71; 95% confidence interval, 1.32–5.58; P =0.007). For 30‐day and 3‐year mortality, the area under the curve for MR ‐pro ADM was 0.77 and 0.78, respectively. For 3‐year mortality, area under the curve (0.84) of the adjusted model marginally changed (0.85; P =0.02) after addition of MR ‐pro ADM . Conclusions Elevation of admission MR ‐pro ADM was associated with long‐term mortality and heart failure, whereas the association with short‐term mortality was borderline significant. MR ‐pro ADM may be a marker of prognosis after ST‐segment–elevation myocardial infarction but does not seem to add substantial prognostic information to established clinical models. Clinical Trial Registration URL : http:/www.ClinicalTrials.gov /. Unique identifiers: NCT 01435408 and NCT 01960933. </jats:sec

Seasonality of ventricular fibrillation at first myocardial infarction and association with viral exposure

AIMS:To investigate seasonality and association of increased enterovirus and influenza activity in the community with ventricular fibrillation (VF) risk during first ST-elevation myocardial infarction (STEMI). METHODS:This study comprised all consecutive patients with first STEMI (n = 4,659; aged 18-80 years) admitted to the invasive catheterization laboratory between 2010-2016, at Copenhagen University Hospital, Rigshospitalet, covering eastern Denmark (2.6 million inhabitants, 45% of the Danish population). Hospital admission, prescription, and vital status data were assessed using Danish nationwide registries. We utilized monthly/weekly surveillance data for enterovirus and influenza from the Danish National Microbiology Database (2010-2016) that receives copies of laboratory tests from all Danish departments of clinical microbiology. RESULTS:Of the 4,659 consecutively enrolled STEMI patients, 581 (12%) had VF before primary percutaneous coronary intervention. In a subset (n = 807), we found that VF patients experienced more generalized fatigue and flu-like symptoms within 7 days before STEMI compared with the patients without VF (OR 3.39, 95% CI 1.76-6.54). During the study period, 2,704 individuals were diagnosed with enterovirus and 19,742 with influenza. No significant association between enterovirus and VF (OR 1.00, 95% CI 0.99-1.02), influenza and VF (OR 1.00, 95% CI 1.00-1.00), or week number and VF (p-value 0.94 for enterovirus and 0.89 for influenza) was found. CONCLUSION:We found no clear seasonality of VF during first STEMI. Even though VF patients had experienced more generalized fatigue and flu-like symptoms within 7 days before STEMI compared with patients without VF, no relationship was found between enterovirus or influenza exposure and occurrence of VF

Unreported exclusion and sampling bias in interpretation of randomized controlled trials in patients with STEMI

Aims: To assess the impact of sampling bias due to reported as well as unreported exclusion of the target population in a multi-center randomized controlled trial (RCT)of ST-elevation myocardial infarction (STEMI). Methods and Results: We compared clinical characteristics and mortality between participants in the DANAMI-3 trial to contemporary non-participants with STEMI using unselected registries. A total of 179 DANAMI-3 participants (8%)and 617 contemporary non-participants (22%)had died (Log-Rank: P < 0.001)after a median follow-up of 1333 days (range: 1–2021 days). In an unadjusted Cox regression model all groups of non-participants had a higher hazard ratio to predict mortality compared to participants: eligible excluded (n = 144)(hazard ratio: 3.41 (95% CI: (2.69–4.32)), ineligible excluded (n = 472)(hazard ratio: 3.42 (95% CI: (2.44–4.80), eligible non-screened (n = 154)(hazard ratio: 3.37 (95% CI: (2.36–4.82)), ineligible non-screened (n = 154)(hazard ratio: 6.48 (95% CI: (4.77–8.80). Conclusion: Sampling bias had occurred due to both reported and unreported exclusion of eligible patients and the difference in mortality between participants and non-participants could not be explained only by the trial exclusion criteria. Thus, screening logs may not be suited to address the risks of sampling bias

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes