Effect of heart rate and blood pressure variability on mortality in Japanese critically ILL patients

AIM: Describe the efficacy and safety of valproate and haloperidol infusion in controlling agitation in the intensive care unit (ICU). MATERIAL AND METHODS: Prospective study on 100 critically ill patients with agitation in Kasralainy Hospital over the period from May 2016 to June 2017.patients were divided into two groups, each group included 50 patients, 1st group patients received Depakene orally, and 2nd group patients received haloperidol by i.v infusion for 72 h. Richmond agitation sedation score and doses of additional sedative drugs were noted and calculated daily in the first three days. RESULTS: Our study showed that valproate was equal in efficacy in controlling agitation; decreasing the RAAS significantly after 48 h from initiation (2.52 ± 0.61 vs 0.28 ± 0.54 with p < 0.001) for Depakene and (2.6 ± 0.67 vs 0.34 ± 0.48 with p < 0.001) for haloperidol. There was also a decrease in the doses of additional sedative drugs used to control agitation (midazolam & propofol) after 48 h from drug initiation. Both drugs therapy was associated with decrease in heart rate (89 ± 20 vs 86.6 ± 13.6 with p = 0.002 for valproate and 99.8 ± 23.3 vs 91 ± 16.7 with p < 0.001 for haloperidol). They did not affect blood pressure. Haloperidol therapy was associated with significant QTc prolongation. CONCLUSION: Valproate was equal in efficacy as haloperidol infusion in controlling agitation in ICU and decreasing the doses of additional sedative drugs used after 48 h from initiation.

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Effectiveness of dexmedetomidine for delirium and its impact on hemodynamics in critically ill patients

Anaesthesia, Pain & Intensive Care ◽

10.35975/apic.v24i6.1402 ◽

2020 ◽

Vol 24 (6) ◽

Author(s):

Shamim Kausar ◽

Iqra Yasin ◽

Irfan Ahsan ◽

Zunairah Rais

Keyword(s):

Blood Pressure ◽

Heart Rate ◽

Diastolic Blood Pressure ◽

Critically Ill ◽

Critically Ill Patients ◽

Local Population ◽

Ethical Review ◽

Hemodynamic Parameters ◽

Blood Pressures ◽

The Impact

Aim/Background: Delirium is common in critically ill patients. For its treatment along with other sedatives, dexmedetomidine has also been prescribed by the clinicians. However, the outcomes with its use are less well-defined by any study in local population. We aimed to study its effectiveness for delirium and the impact on hemodynamics in critically sick patients of our population. Methodology: It was a cross-sectional, prospective observational study conducted on 212 participants after ethical review committee approval at our hospital. Heart rate, systolic and diastolic blood pressures and Richmond Agitation Sedation Scale (RASS) scores were recorded before starting dexmedetomidine and within one hour of starting the drug. More than 10% decrease in heart rate (HR) or systolic or diastolic blood pressure was considered as an impact on hemodynamic parameters. An achievement of RASS of -2 was considered as effectiveness of drug. Results: There was a mean drop of HR by 13.78 ± 18.58 beats/min (14.49%) after starting dexmedetomidine. Mean systolic blood pressure drop was 10.99 ± 20.67 mmHg (9.16%), and mean drop in diastolic blood pressure was 4.958 ± 12.53 mmHg after dexmedetomidine use. The mean value of RASS score achieved on dexmedetomidine was -2. Conclusion: Our study concluded the effectiveness of dexmedetomidine as light sedation for delirium. It significantly impacted on hemodynamic parameters. Its impact on heart rate was more pronounced as compared to systolic and diastolic blood pressures. Key words: Dexmedetomidine; Critical care; Delirium; Hemodynamics Citation: Kausar S, Yasin I, Ahsan I, Rais Z. Effectiveness of dexmedetomidine for delirium and its impact on hemodynamics in critically ill patients. Anaesth. pain intensive care 2020;24(6):--- Received: 14 June 2020, Reviewed: 24 August, 19 October 2020, Accepted: 26 October 2020

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Respiratory induced heart rate and blood pressure variability during mechanical ventilation in critically ill and brain death patients

2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/embc.2012.6346800 ◽

2012 ◽

Author(s):

P. Jurak ◽

V. Zvonicek ◽

P. Leinveber ◽

J. Halamek ◽

V. Vondra

Keyword(s):

Blood Pressure ◽

Heart Rate ◽

Mechanical Ventilation ◽

Brain Death ◽

Critically Ill ◽

Blood Pressure Variability

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Predicting Need for Vasopressors in the Intensive Care Unit Using an Attention Based Deep Learning Model

10.21203/rs.3.rs-45876/v1 ◽

2020 ◽

Author(s):

Gloria Hyunjung Kwak ◽

Lowell Ling ◽

Pan Hui

Keyword(s):

Blood Pressure ◽

Heart Rate ◽

Intensive Care ◽

Deep Learning ◽

Mean Arterial Pressure ◽

Critically Ill ◽

Critically Ill Patients ◽

Class Imbalance ◽

Vasopressor Therapy ◽

Icu Admission

Abstract BackgroundPrevious models on prediction of shock mostly focused on septic shock and often required laboratory results in their models. Database analyses often report only limited data pre-processing which may introduce significant bias into machine classifiers. The purpose of this study was to use deep learning approaches to predict vasopressor requirement for critically ill patients within 24 hours of ICU admission using only vital signs. Performance bias from relative missing data and inadequate matching was assessed. MethodsWe used data from the Medical Information Mart for Intensive Care III database and the eICU Collaborative Research Database to develop a vasopressor prediction model. We performed systematic data pre-processing using matching of cohorts, oversampling and imputation to control for bias, class imbalance and missing data. After pre-processing we used bidirectional long short-term memory (Bi-LSTM), a multivariate time series model to predict the need for vasopressor therapy using serial physiological data collected 21 hours prior to prediction time. ResultsUsing data from 10,941 critically ill patients from 209 ICUs, our Bi-LSTM model achieved an initial area under the curve (AUC) of 0.96 (95%CI 0.96-0.96) to predict the need for vasopressor therapy in 2 hours within the first day of ICU admission. After matching to control class imbalance, the Bi-LSTM model had AUC of 0.83 (95%CI 0.82-0.83). Heart rate, respiratory rate and mean arterial pressure contributed most to the model amongst other serial physiological variables of systolic blood pressure, diastolic blood pressure, pulse oximetry and temperature. ConclusionsWe used Bi-LSTM to develop a model to predict the need for vasopressor for critically ill patients for the first 24 hours of ICU admission. With attention mechanism, respiratory rate, mean arterial pressure and heart rate were identified as key sequential determinants of vasopressor requirements. Although rigorous data pre-processing such as missing value analysis and class matching reduced predictive performance, it minimized bias in data and should be performed for database studies.

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Relationship Between Short-Term Blood Pressure Variability and Incidence of Acute Kidney Injury in Critically Ill Patients

Kidney & Blood Pressure Research ◽

10.1159/000485927 ◽

2017 ◽

Vol 42 (6) ◽

pp. 1238-1246 ◽

Cited By ~ 3

Author(s):

Zhichao Xie ◽

Xuelian Liao ◽

Wanhong Yin ◽

Yan Kang ◽

Jun Guo ◽

...

Keyword(s):

Blood Pressure ◽

Acute Kidney Injury ◽

Critically Ill ◽

Critically Ill Patients ◽

Blood Pressure Variability ◽

Kidney Injury ◽

Short Term

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Report of the first AKI Round Table meeting: an initiative of the ESICM AKI Section

Intensive Care Medicine Experimental ◽

10.1186/s40635-019-0280-z ◽

2019 ◽

Vol 7 (1) ◽

Cited By ~ 1

Author(s):

M. Ostermann ◽

A. Schneider ◽

T. Rimmele ◽

I. Bobek ◽

M. van Dam ◽

...

Keyword(s):

Blood Pressure ◽

Critical Care ◽

Intensive Care ◽

Renal Replacement Therapy ◽

Replacement Therapy ◽

Critically Ill ◽

Critically Ill Patients ◽

Future Research ◽

Knowledge Gaps ◽

Blood Pressure Targets

Abstract Purpose Critical Care Nephrology is an emerging sub-specialty of Critical Care. Despite increasing awareness about the serious impact of acute kidney injury (AKI) and renal replacement therapy (RRT), important knowledge gaps persist. This report represents a summary of a 1-day meeting of the AKI section of the European Society of Intensive Care Medicine (ESICM) identifying priorities for future AKI research. Methods International Members of the AKI section of the ESICM were selected and allocated to one of three subgroups: “AKI diagnosis and evaluation”, “Medical management of AKI” and “Renal Replacement Therapy for AKI.” Using a modified Delphi methodology, each group identified knowledge gaps and developed potential proposals for future collaborative research. Results The following key research projects were developed: Systematic reviews: (a) epidemiology of AKI with stratification by patient cohorts and diagnostic criteria; (b) role of higher blood pressure targets in patients with hypertension admitted to the Intensive Care Unit, and (c) specific clearance characteristics of different modalities of continuous renal replacement therapy (CRRT). Observational studies: (a) epidemiology of critically ill patients according to AKI duration, and (b) current clinical practice of CRRT. Intervention studies:( a) Comparison of different blood pressure targets in critically ill patients with hypertension, and (b) comparison of clearance of solutes with various molecular weights between different CRRT modalities. Conclusion Consensus was reached on a future research agenda for the AKI section of the ESICM.

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