Prognostic value of nighttime blood pressure in patients with chronic kidney disease

Hypertension Research, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 21, 2025

Language: Английский

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Critically ill patients with a reverse blood pressure dipping phenotype at increased risk for delirium and death.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

Abstract Background The ICU environment is disruptive to a patient’s biological rhythms where sleep-wake cycles are often desynchronized from the environmental day-night changes. This puts patients at increased risk develop delirium with consequent fiscal pressure for health care system. An underappreciated dimension how time-specific patient phenotypes in critical relate clinical outcomes. We set out analyze rhythmic components (or lack thereof) physiological data streams sampled high resolution were associated future incidence of and death. To offer cues further interrogation into mechanism prognosis, we examined differences 24-hour fluctuations labs populations risk. Methods Rhythmic using dipping ratios JTK_CYCLE statistics derived blood heart rate measurements available admissions recorded MIMIC IV database. Logistic adjusted regression models assessed association between disrupted vital sign during same hospital admission Aggregation numeric lab across first 24 hours all allowed modelling patterns subsequent studies link potential biochemical mechanisms perturbed adverse Results Patients reverse 40% higher have diagnosis (Odds Ratio: 1.40, 95% CI: 1.14-1.72) 13% death 1.13, 1.02-1.26). Compared population nocturnal dip, dippers showed biochemistry profiles suggestive altered circadian programs specifically parameters renal, metabolic, hemostatic function. Conclusions Reverse can be an early development accompanied by biorhythms multiple organ systems. Dampened reversed patients. Considering inclusion these factors preventive may improve outcomes reduce burden on

Language: Английский

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Development and Validation of a Deep Learning Model for Prediction of Adult Physiological Deterioration

Critical Care Explorations, Journal Year: 2024, Volume and Issue: 6(9), P. e1151 - e1151

Published: Sept. 1, 2024

BACKGROUND: Prediction-based strategies for physiologic deterioration offer the potential earlier clinical interventions that improve patient outcomes. Current are limited because they operate on inconsistent definitions of deterioration, attempt to dichotomize a dynamic and progressive phenomenon, poor performance. OBJECTIVE: Can deep learning prediction model (Deep Learning Enhanced Triage Emergency Response Inpatient Optimization [DETERIO]) based consensus definition (the Adult Decompensation Event [AIDE] criteria) approaches as state “value-estimation” problem outperform commercially available score? DERIVATION COHORT: The derivation cohort contained retrospective data collected from both inpatient services (inpatient) emergency departments (EDs) two hospitals within University California San Diego Health System. There were 330,729 total patients; 71,735 258,994 ED. Of these data, 20% randomly sampled “testing set.” VALIDATION validation temporal data. 65,898 13,750 52,148 PREDICTION MODEL: DETERIO was developed validated using AIDE criteria generate composite score. DETERIO’s architecture builds upon previous work. performance up 12 hours before T0 compared against Epic Deterioration Index (EDI). RESULTS: In testing set, area under receiver operating characteristic curve (AUC) 0.797 0.874 ED subsets, respectively. cohort, corresponding AUC 0.775 0.856, outperformed EDI in (AUC, vs. 0.721; p < 0.01) while maintaining superior sensitivity comparable rate false alarms (sensitivity, 45.50% 30.00%; positive predictive value, 20.50% 16.11%). CONCLUSIONS: demonstrates promise viability value-estimation approach predicting adult deterioration. It may offering additional utility triage clinician interaction with confidence explanations. Additional studies needed assess generalizability real-world impact.

Language: Английский

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Disrupted rest-activity circadian rhythms are associated with all-cause mortality in patients with chronic kidney diseases

Chronobiology International, Journal Year: 2024, Volume and Issue: 41(11), P. 1399 - 1410

Published: Oct. 24, 2024

Circadian rhythms are important biological contributors to health. Rest activity (RAR) emerging as biomarkers of circadian behavior that associated with chronic disease when abnormal. RAR have not yet been characterized in kidney diseases (CKD). Leveraging the National Health and Nutrition Examination Survey (2011-2014), patients CKD (

Language: Английский

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Feel the rhythm of the beat: rhythmic components in ambulatory blood pressure monitoring for predicting cardiovascular risk in CKD patients

Journal of Human Hypertension, Journal Year: 2024, Volume and Issue: 38(9), P. 629 - 630

Published: Aug. 27, 2024

Language: Английский

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