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Acta Paediatrica (Oslo, Norway : 1992) Jun 2024To investigate the role of autonomic nervous system in subpopulations of children with enuresis.
AIM
To investigate the role of autonomic nervous system in subpopulations of children with enuresis.
METHODS
We included 35 children with enuresis, divided in children with (17) and without nocturnal polyuria (18) and 43 healthy controls. For all participants hormones and neurotransmitters were measured. Patients and controls wore a sleep tracker device and children with enuresis underwent a 24 h blood pressure monitoring, nocturnal urine output measurement and uroflowmetry.
RESULTS
Children with enuresis had lower than controls copeptin and aldosterone, with the latter being more prominent in patients without nocturnal polyuria. Dopamine was lower in patients without nocturnal polyuria compared with patients with nocturnal polyuria. Children without polyuria experienced episodes only during NREM sleep, whereas in children with polyuria episodes occurred in both REM and NREM sleep. Children with enuresis experienced a non-dipping phenomenon during sleep which was more prominent in the group without polyuria.
CONCLUSION
In patients with nocturnal polyuria, nocturnal enuresis is associated with sympathetic hyperactivity which results in pressure polyuria and significantly lower systolic dipping during sleep. On the contrary, in children without nocturnal polyuria, it is mostly associated with bladder overactivity due to parasympathetic overstimulation as demonstrated by the NREM-related enuretic episodes and the lower aldosterone and dopamine levels.
PubMed: 38940196
DOI: 10.1111/apa.17338 -
Annals of Agricultural and... Jun 2024Correlations between the number of milk somatic cells (SCC), the number of microorganisms, and the content of basic components of milk were studied on five farms (F1-F5)...
INTRODUCTION AND OBJECTIVE
Correlations between the number of milk somatic cells (SCC), the number of microorganisms, and the content of basic components of milk were studied on five farms (F1-F5) with cows of the same breed, but with different milking systems.
MATERIAL AND METHODS
From each farm, 50 Holstein Friesien milk samples were collected once a month (250 samples/month; n=3,000) during March 2022 - February 2023. Samples from farms F1 and F5 were tested for fat, protein, lactose, no fat dry matter content (FTIR spectroscopy), for the SCC (Fossomatic 7), and for the differential cells (Vetscan DC-Q).
RESULTS
The highest fat content was confirmed on farm F5 (3.85 ± 1.70%) and F4 (3.82 ± 0.21%) with automatic milking system (AMS). However, from the point of view of protein content, these farms showed slightly lower values (<0.05). F1 did not meet the minimum required amount for fat content (2.84 ± 0.81%) set by the legislation of the Slovakia. The comparison shows that there is not much difference in cell size between healthy cells and mastitis cells. The average size of healthy cells was approximately 8.77 ± 0.49 μm. In the monitored period, the average values determined were at the level of 292,000/mL (5.46 ± 0.72 log10 SCC) in cow milk samples, while for the rest of the year, the values remained at 256,000/mL (5.40 ± 0.80 log10 SCC). F1 was categorized as a positive farm with a high TLC (total milk leucocyte count) concentration (5.58 log10 cells/mL, 406.65 ± 53.80 × 10 cells/mL) and a predominant NEU fraction (61%). Farms F2, F4, and F5 were classified as negative farms (TLC was 4.70 ± 0.26 log10 cells/ml).
CONCLUSIONS
According to the results, the size of SCCs in healthy milk does not differ from SCCs found in mastitis milk. From the results, it can be concluded that the transition to the latest generation of robotic milking method can positively affect milk production and its quality.
Topics: Animals; Milk; Dairying; Female; Cell Count; Cattle; Lactose; Slovakia; Milk Proteins; Lactation
PubMed: 38940103
DOI: 10.26444/aaem/187170 -
Circulation. Arrhythmia and... Jun 2024Atrial fibrillation (AF) events in cardiac implantable electronic devices (CIEDs) are temporally associated with stroke risk. This study explores temporal differences in...
BACKGROUND
Atrial fibrillation (AF) events in cardiac implantable electronic devices (CIEDs) are temporally associated with stroke risk. This study explores temporal differences in AF burden associated with HF hospitalization risk in patients with CIEDs.
METHODS
Patients with HF events from the Optum de-identified Electronic Health Records from 2007 to 2021 and 120 days of preceding CIED-derived rhythm data from a linked manufacturer's data warehouse were included. AF burden ≥5.5 h/d was defined as an AF event. The AF event burden in the case period (days 1-30 immediately before the HF event) was considered temporally associated with the HF event and compared with the AF event burden in a temporally dissociated control period (days 91-120 before the HF event). The odds ratio for temporally associated HF events and the odds ratio associated with poorly rate-controlled AF (>110 bpm) were calculated.
RESULTS
In total, 7257 HF events with prerequisite CIED data were included; 957 (13.2%) patients had AF events recorded only in either their case (763 [10.5%]) or control (194 [2.7%]) periods, but not both. The odds ratio for a temporally associated HF event was 3.93 (95% CI, 3.36-4.60). This was greater for an HF event with a longer stay of >3 days (odds ratio, 4.51 [95% CI, 3.57-5.68]). In patients with AF during both the control and case periods, poor AF rate control during the case period also increased HF event risk (1.78 [95% CI, 1.22-2.61]). In all, 222 of 4759 (5%) patients without AF events before their HF event had an AF event in the 10 days following.
CONCLUSIONS
In a large real-world population of patients with CIED devices, AF burden was associated with HF hospitalization risk in the subsequent 30 days. The risk is increased with AF and an uncontrolled ventricular rate. Our findings support AF monitoring in CIED algorithms to prevent HF admissions.
REGISTRATION
URL: https://www.clinicaltrials.gov; Unique identifier: NCT04452149 and NCT04987723.
PubMed: 38939945
DOI: 10.1161/CIRCEP.124.012842 -
JACC. Advances Jan 2024Low-density lipoprotein cholesterol (LDL-C) is used to guide lipid-lowering therapy after a myocardial infarction (MI). Lack of LDL-C testing represents a missed...
BACKGROUND
Low-density lipoprotein cholesterol (LDL-C) is used to guide lipid-lowering therapy after a myocardial infarction (MI). Lack of LDL-C testing represents a missed opportunity for optimizing therapy and reducing cardiovascular risk.
OBJECTIVES
The purpose of this study was to estimate the proportion of Medicare beneficiaries who had their LDL-C measured within 90 days following MI hospital discharge.
METHODS
We conducted a retrospective cohort study of Medicare beneficiaries ≥66 years of age with an MI hospitalization between 2016 and 2020. The primary analysis used data from all beneficiaries with fee-for-service coverage and pharmacy benefits (532,767 MI hospitalizations). In secondary analyses, we used data from a 5% random sample of beneficiaries with fee-for-service coverage without pharmacy benefits (10,394 MI hospitalizations), and from beneficiaries with Medicare Advantage (176,268 MI hospitalizations). The proportion of beneficiaries who had their LDL-C measured following MI hospital discharge was estimated accounting for the competing risk of death.
RESULTS
In the primary analysis (mean age 76.9 years, 84.4% non-Hispanic White), 29.9% of beneficiaries had their LDL-C measured within 90 days following MI hospital discharge. Among Hispanic, Asian, non-Hispanic White, and non-Hispanic Black beneficiaries, the 90-day postdischarge LDL-C testing was 33.8%, 32.5%, 30.0%, and 26.0%, respectively. Postdischarge LDL-C testing within 90 days was highest in the Middle Atlantic (36.4%) and lowest in the West North Central (23.4%) U.S. regions. In secondary analyses, the 90-day postdischarge LDL-C testing was 26.9% among beneficiaries with fee-for-service coverage without pharmacy benefits, and 28.6% among beneficiaries with Medicare Advantage coverage.
CONCLUSIONS
LDL-C testing following MI hospital discharge among Medicare beneficiaries was low.
PubMed: 38939806
DOI: 10.1016/j.jacadv.2023.100753 -
JACC. Advances Jan 2024A simple ambulatory measure of cardiac function could be helpful for monitoring heart failure patients.
BACKGROUND
A simple ambulatory measure of cardiac function could be helpful for monitoring heart failure patients.
OBJECTIVES
The purpose of this paper was to determine whether a novel pulse waveform analysis using data obtained by our developed multisensor-ambulatory blood pressure monitoring (ABPM) device, the 'Sf/Am' ratio, is associated with echocardiographic left ventricular ejection fraction (LVEF).
METHODS
Multisensor-ABPM was conducted twice at baseline in 20 heart failure (HF) patients with HF-reduced LVEF or HF-preserved LVEF (median age 66 years, male 65%) and over a 6- to 12-month follow-up after patient-tailored treatment. We assessed the changes in the pulse waveform index Sf/Am and LVEF that occurred between the baseline and follow-up. The Sf/Am consists of the area of the ejection part in the square forward wave (Sf) and the amplitude of the measured wave (Am). We divided the patients into the recovered (n = 11) and not-recovered (n = 9) groups defined by a ≥10% increase in LVEF.
RESULTS
Although the ambulatory BP levels and variabilities did not change in either group, the Sf/Am increased significantly in the recovered group (baseline 21.4 ± 4.5; follow-up, 25.6 ± 3.7, = 0.004). The not-recovered group showed no difference between the baseline and follow-up. The follow-up/baseline Sf/Am ratio was significantly associated with the LVEF ratio ( = 0.469, = 0.037). The Sf/Am was significantly correlated with the LVEF in overall measurements (n = 40, = 0.491, = 0.001).
CONCLUSIONS
These results demonstrated that a novel noninvasive pulse waveform index, the Sf/Am measured by multisensor-ABPM is associated with LVEF. The Sf/Am may be useful for estimating cardiac function.
PubMed: 38939805
DOI: 10.1016/j.jacadv.2023.100737 -
Journal of Arrhythmia Jun 2024We explored the results of two tests of the novel HeartInsight algorithm for heart failure (HF) prediction, reconstructing trends from historical cases. Results suggest...
We explored the results of two tests of the novel HeartInsight algorithm for heart failure (HF) prediction, reconstructing trends from historical cases. Results suggest potential extension of HeartInsight to implantable cardioverter defibrillators patients without history of HF and illustrate the importance of the baseline clinical profile in enhancing algorithm specificity.
PubMed: 38939800
DOI: 10.1002/joa3.13032 -
Journal of Arrhythmia Jun 2024We report the behavior of OptiVol2 fluid index (OVFI2) and intrathoracic impedance on remote monitoring before the appearance of signs of infection. A sustained rise in...
We report the behavior of OptiVol2 fluid index (OVFI2) and intrathoracic impedance on remote monitoring before the appearance of signs of infection. A sustained rise in OVFI2 early after implantation reflects peri-device fluid retention.
PubMed: 38939798
DOI: 10.1002/joa3.13005 -
Journal of Arrhythmia Jun 2024Remote monitoring (RM) of cardiac implantable electrical devices (CIEDs) can detect various events early. However, the diagnostic ability of CIEDs has not been...
BACKGROUND
Remote monitoring (RM) of cardiac implantable electrical devices (CIEDs) can detect various events early. However, the diagnostic ability of CIEDs has not been sufficient, especially for lead failure. The first notification of lead failure was almost noise events, which were detected as arrhythmia by the CIED. A human must analyze the intracardiac electrogram to accurately detect lead failure. However, the number of arrhythmic events is too large for human analysis. Artificial intelligence (AI) seems to be helpful in the early and accurate detection of lead failure before human analysis.
OBJECTIVE
To test whether a neural network can be trained to precisely identify noise events in the intracardiac electrogram of RM data.
METHODS
We analyzed 21 918 RM data consisting of 12 925 and 1884 Medtronic and Boston Scientific data, respectively. Among these, 153 and 52 Medtronic and Boston Scientific data, respectively, were diagnosed as noise events by human analysis. In Medtronic, 306 events, including 153 noise events and randomly selected 153 out of 12 692 nonnoise events, were analyzed in a five-fold cross-validation with a convolutional neural network. The Boston Scientific data were analyzed similarly.
RESULTS
The precision rate, recall rate, F1 score, accuracy rate, and the area under the curve were 85.8 ± 4.0%, 91.6 ± 6.7%, 88.4 ± 2.0%, 88.0 ± 2.0%, and 0.958 ± 0.021 in Medtronic and 88.4 ± 12.8%, 81.0 ± 9.3%, 84.1 ± 8.3%, 84.2 ± 8.3% and 0.928 ± 0.041 in Boston Scientific. Five-fold cross-validation with a weighted loss function could increase the recall rate.
CONCLUSIONS
AI can accurately detect noise events. AI analysis may be helpful for detecting lead failure events early and accurately.
PubMed: 38939795
DOI: 10.1002/joa3.13037 -
Journal of Arrhythmia Jun 2024Guidelines recommended remote monitoring (RM) in managing patients with Cardiac Implantable Electronic Devices. In recent years, smart device (phone or tablet)...
BACKGROUND
Guidelines recommended remote monitoring (RM) in managing patients with Cardiac Implantable Electronic Devices. In recent years, smart device (phone or tablet) monitoring-based RM (SM-RM) was introduced. This study aims to systematically review SM-RM versus bedside monitor RM (BM-RM) using radiofrequency in terms of compliance, connectivity, and episode transmission time.
METHODS
We conducted a systematic review, searching three international databases from inception until July 2023 for studies comparing SM-RM (intervention group) versus BM-RM (control group).
RESULTS
Two matched studies (21 978 patients) were retrieved (SM-RM arm: 9642 patients, BM-RM arm: 12 336 patients). There is significantly higher compliance among SM-RM patients compared with BM-RM patients in both pacemaker and defibrillator patients. Manyam et al. found that more SM-RM patients than BM-RM patients transmitted at least once (98.1% vs. 94.3%, < .001), and Tarakji et al. showed that SM-RM patients have higher success rates of scheduled transmissions than traditional BM-RM methods (SM-RM: 94.6%, pacemaker manual: 56.3%, pacemaker wireless: 77.0%, defibrillator wireless: 87.1%). There were higher enrolment rates, completed scheduled and patient-initiated transmissions, shorter episode transmission time, and higher connectivity among SM-RM patients compared to BM-RM patients. Younger patients (aged <75) had more patient-initiated transmissions, and a higher proportion had ≥10 transmissions compared with older patients (aged ≥75) in both SM-RM and BM-RM groups.
CONCLUSION
SM-RM is a step in the right direction, with good compliance, connectivity, and shorter episode transmission time, empowering patients to be in control of their health. Further research on cost-effectiveness and long-term clinical outcomes can be carried out.
PubMed: 38939794
DOI: 10.1002/joa3.13054 -
JACC. Advances Apr 2024Maternal mortality is a major public health crisis in the United States. Cardiovascular disease (CVD) is a leading cause of maternal mortality and morbidity. Labor and... (Review)
Review
Maternal mortality is a major public health crisis in the United States. Cardiovascular disease (CVD) is a leading cause of maternal mortality and morbidity. Labor and delivery is a vulnerable time for pregnant individuals with CVD but there is significant heterogeneity in the management of labor and delivery in high-risk patients due in part to paucity of high-quality randomized data. The authors have convened a multidisciplinary panel of cardio-obstetrics experts including cardiologists, obstetricians and maternal fetal medicine physicians, critical care physicians, and anesthesiologists to provide a practical approach to the management of labor and delivery in high-risk individuals with CVD. This expert panel will review key elements of management from mode, timing, and location of delivery to use of invasive monitoring, cardiac devices, and mechanical circulatory support.
PubMed: 38939671
DOI: 10.1016/j.jacadv.2024.100901