Systolic blood pressure variability in patients with early severe sepsis or septic shock: a prospective cohort study

Cardiovascular Autonomic Dysfunction in Hospitalized Patients with a Bacterial Infection: A Longitudinal Observational Pilot Study in the UK

PURPOSE

A temporal reduction in the cardiovascular autonomic responses predisposes patients to cardiovascular instability after a viral infection and therefore increases the risk of associated complications. These findings have not been replicated in a bacterial infection. This pilot study will explore the prevalence of cardiovascular autonomic dysfunction (CAD) in hospitalized patients with a bacterial infection.

METHODS

A longitudinal observational pilot study was conducted. Fifty participants were included: 13 and 37 participants in the infection group and healthy group, respectively. Recruitment and data collection were carried out during a two-year period. Participants were followed up for 6 weeks: all participants' cardiovascular function was assessed at baseline (week 1) and reassessed subsequently at week 6 so that the progression of the autonomic function could be evaluated over that period of time. The collected data were thereafter analyzed using STATA/SE version 16.1 (StataCorp). The Fisher Exact test, McNemar exact test, Mann-Whitney test and Wilcoxon test were used for data analysis.

RESULTS

32.4% of the participants in the healthy group were males (n = 12) and 67.6% were females (n = 25). Participants' age ranged from 33 years old to 76 years old with the majority being 40-60 years of age (62.1%) (Mean age 52.4 SD = 11.4). Heart rate variability (HRV) in response to Valsalva Maneuver, metronome breathing, standing and sustained handgrip in the infection group was lower than in the healthy group throughout the weeks. Moreover, both the HRV in response to metronome breathing and standing up showed a statistically significant difference when the mean values were compared between both groups in week 1 (p = 0.03 and p = 0.013). The prevalence of CAD was significantly higher in the infection group compared to healthy volunteers, both at the beginning of the study (p = 0.018) and at the end of follow up (p = 0.057), when all patients had been discharged.

CONCLUSIONS

CAD, as assessed by the HRV, is a common finding during the recovery period of a bacterial infection, even after 6 weeks post-hospital admission. This may increase the risk of complications and cardiovascular instability. It may therefore be of value to conduct a wider scale study to further evaluate this aspect so recommendations can be made for the cardiovascular autonomic assessment of patients while they are recovering from a bacterial infectious process.

Heart rate complexity helps mortality prediction in the intensive care unit: A pilot study using artificial intelligence

BACKGROUND

In intensive care units (ICUs), accurate mortality prediction is crucial for effective patient management and resource allocation. The Simplified Acute Physiology Score II (SAPS-2), though commonly used, relies heavily on comprehensive clinical data and blood samples. This study sought to develop an artificial intelligence (AI) model utilizing key hemodynamic parameters to predict ICU mortality within the first 24 h and assess its performance relative to SAPS-2.

METHODS

We conducted an analysis of select hemodynamic parameters and the structure of heart rate curves to identify potential predictors of ICU mortality. A machine-learning model was subsequently trained and validated on distinct patient cohorts. The AI algorithm's performance was then compared to the SAPS-2, focusing on classification accuracy, calibration, and generalizability.

MEASUREMENTS AND MAIN RESULTS

The study included 1298 ICU admissions from March 27th, 2015, to March 27th, 2017. An additional cohort from 2022 to 2023 comprised 590 patients, resulting in a total dataset of 1888 patients. The observed mortality rate stood at 24.0%. Key determinants of mortality were the Glasgow Coma Scale score, heart rate complexity, patient age, duration of diastolic blood pressure below 50 mmHg, heart rate variability, and specific mean and systolic blood pressure thresholds. The AI model, informed by these determinants, exhibited a performance profile in predicting mortality that was comparable, if not superior, to the SAPS-2.

CONCLUSIONS

The AI model, which integrates heart rate and blood pressure curve analyses with basic clinical parameters, provides a methodological approach to predict in-hospital mortality in ICU patients. This model offers an alternative to existing tools that depend on extensive clinical data and laboratory inputs. Its potential integration into ICU monitoring systems may facilitate more streamlined mortality prediction processes.

RELATIONSHIP BETWEEN SHOCK INDEX, MODIFIED SHOCK INDEX, AND AGE SHOCK INDEX AND 28-DAY MORTALITY AMONG PATIENTS WITH PREHOSPITAL SEPTIC SHOCK

BACKGROUND

A relative hypovolemia occurs during septic shock (SS); the early phase is clinically reflected by tachycardia and low blood pressure. In the prehospital setting, simple objective tools to assess hypovolemia severity are needed to optimize triaging.

OBJECTIVE

The aim of this study was to evaluate the relationship between shock index (SI), diastolic SI (DSI), modified SI (MSI), and age SI (ASI) and 28-day mortality of patients with SS initially cared for in a prehospital setting of a mobile intensive care unit (MICU).

METHODS

From April 6, 2016 through December 31, 2021, 530 patients with SS cared for at a prehospital MICU were analyzed retrospectively. Initial SI, MSI, DSI, and ASI values, that is, first measurement after MICU arrival to the scene were calculated. A propensity score analysis with inverse probability of treatment weighting (IPTW) method was used to assess the relationship between SI, DSI, MSI, and ASI and 28-day mortality.

RESULTS

SS resulted mainly from pulmonary, digestive, and urinary infections in 44%, 25%, and 17% of patients. The 28-day overall mortality was 31%. IPTW propensity score analysis indicated a significant relationship between 28-day mortality and SI (adjusted odds ratio [aOR] 1.13; 95% CI 1.01-1.26; p = 0.04), DSI (aOR 1.16; 95% CI 1.06-1.34; p = 0.03), MSI (aOR 1.03; 95% CI 1.01-1.17; p = 0.03), and ASI (aOR 3.62; 95% CI 2.63-5.38; p < 10-6).

CONCLUSIONS

SI, DSI, MSI, and ASI were significantly associated with 28-day mortality among patients with SS cared for at a prehospital MICU. Further studies are needed to confirm the usefulness of SI and SI derivates for prehospital SS optimal triaging.

Association of Blood Pressure Variability With Death and Discharge Destination Among Critically Ill Patients With and Without Stroke

BACKGROUND AND OBJECTIVES

It is unclear whether blood pressure variability's (BPV) association with worse outcomes is unique to patients with stroke or a risk factor among all critically ill patients. We (1) determined whether BPV differed between patients with stroke and nonstroke patients, (2) examined BPV's associations with in-hospital death and favorable discharge destination in patients with stroke and nonstroke patients, and (3) assessed how minimum mean arterial pressure (MAP)-a correlate of illness severity and cerebral perfusion-affects these associations.

METHODS

This is a retrospective analysis of adult intensive care unit patients hospitalized between 2001 and 2012 from the Medical Information Mart for Intensive Care III database. Confounder-adjusted logistic regressions determined associations between BPV, measured as SD and average real variability (ARV), and (1) in-hospital death and (2) favorable discharge, with testing of minimum MAP for effect modification.

RESULTS

BPV was higher in patients with stroke (N = 2,248) compared with nonstroke patients (N = 9,085) (SD mean difference 2.3, 95% CI 2.1-2.6, p < 0.01). After adjusting for minimum tertile of MAP and other confounders, higher SD remained significantly associated (p < 0.05) with higher odds of in-hospital death for patients with acute ischemic strokes (AISs, odds ratio [OR] 2.7, 95% CI 1.5-4.8), intracerebral hemorrhage (ICH, OR 2.6, 95% CI 1.6-4.3), subarachnoid hemorrhage (SAH, OR 3.4, 95% CI 1.2-9.3), and pneumonia (OR 1.9, 95% CI 1.1-3.3) and lower odds of favorable discharge destination in patients with ischemic stroke (OR 0.3, 95% CI 0.2-0.6) and ICH (OR 0.4, 95% CI 0.3-0.6). No interaction was found between minimum MAP tertile with SD (p > 0.05). Higher ARV was not significantly associated with increased risk of death in any condition when adjusting for illness severity but portended worse discharge destination in those with AIS (OR favorable discharge 0.4, 95% CI 0.3-0.7), ICH (OR favorable discharge 0.5, 95% CI 0.3-0.7), sepsis (OR favorable discharge 0.8, 95% CI 0.6-1.0), and pneumonia (OR favorable discharge 0.5, 95% CI 0.4-0.8).

DISCUSSION

BPV is higher and generally associated with worse outcomes among patients with stroke compared with nonstroke patients. BPV in patients with AIS and patients with ICH may be a marker of central autonomic network injury, although clinician-driven blood pressure goals likely contribute to the association between BPV and outcomes.

Severe fluctuation in mean perfusion pressure is associated with increased risk of in-hospital mortality in critically ill patients with central venous pressure monitoring: A retrospective observational study

BACKGROUND

The mean perfusion pressure (MPP) was recently proposed to personalize tissue perfusion pressure management in critically ill patients. Severe fluctuation in MPP may be associated with adverse outcomes. We sought to determine if higher MPP variability was correlated with increased mortality in critically ill patients with CVP monitoring.

METHODS

We designed a retrospective observational study and analyzed data stored in the eICU Collaborative Research Database. Validation test was conducted in MIMIC-III database. The exposure was the coefficient of variation (CV) of MPP in the primary analyses, using the first 24 hours MPP data recorded within 72 hours in the first ICU stay. Primary endpoint was in-hospital mortality.

RESULTS

A total of 6,111 patients were included. The in-hospital mortality of 17.6% and the median MPP-CV was 12.3%. Non-survivors had significantly higher MPP-CV than survivors (13.0% vs 12.2%, p<0.001). After accounting for confounders, the highest MPP-CV in decile (CV > 19.2%) were associated with increased risk of hospital mortality compared with those in the fifth and sixth decile (adjusted OR: 1.38, 95% Cl: 1.07-1.78). These relationships remained remarkable in the multiple sensitivity analyses. The validation test with 4,153 individuals also confirmed the results when MPP-CV > 21.3% (adjusted OR: 1.46, 95% Cl: 1.05-2.03).

CONCLUSIONS

Severe fluctuation in MPP was associated with increased short-term mortality in critically ill patients with CVP monitoring.

Evaluation of SI, MSI and DSI for very early (3-day) mortality in patients with septic shock

BACKGROUND

Septic shock is associated with increased mortality. Predicting mortality, including early prediction for septic shock patients in intensive care units (ICUs), remains an important challenge.

METHOD

We searched the Medical Information Mart for Intensive Care IV database. Odds ratios (ORs) with 95% confidence intervals (CIs) of the relationships between shock index (SI), modified SI (MSI), and diastolic SI (DSI) of patients with septic shock requiring vasopressors and 3-day/in-hospital mortality were calculated using logistic regression models. The time-course changes of these parameters were compared between survivors and non-survivors. The performance of the different parameters was described by the area under the receiver operating characteristic (ROC) curve (AUC) and compared with DeLong analysis.

RESULTS

A total of 1266 patients with septic shock requiring vasopressors were identified. The 3-day mortality rate and in-hospital mortality rate were 8.7% and 23.5%, respectively. Multivariable logistic regression analysis showed significant associations between pre-vasopressor SI/MSI/DSI and 3-day mortality in patients with septic shock requiring vasopressors in fully adjusted models (Ps for trend < 0.01). The AUCs of pre-vasopressor SI, MSI, and DSI were 0.746, 0.710, and 0.732 for 3-day mortality, respectively. There were significant differences in the time-course of SI, MSI, and DSI between survivors and non-survivors at 3-day/in-hospital mortality among patients with septic shock requiring vasopressors (repeated-measures ANOVA, inter-subjects difference P < 0.001).

CONCLUSION

Pre-vasopressor SI, MSI, and DSI values identified patients with septic shock requiring vasopressors who are at increased risk of early death. Of these easy-to-acquire values, SI and MSI show a comparatively better performance.

Association of blood pressure variability with short- and long-term cognitive outcomes in patients with critical illness

BACKGROUND

Blood pressure variability (BPV), a modifiable risk factor, can compromise cerebral perfusion in critically ill patients. We studied the association between BPV in the intensive care unit (ICU) and short- and long-term cognitive outcomes.

METHODS

All patients were ≥50 years old. The short-term cognitive end points were delirium and depressed alertness without delirium. The long-term outcome was change in the slope of longitudinal cognitive scores. Primary BPV measure was average real variability (ARV) of systolic blood pressure. Associations were assessed with multivariable multinominal logistic regression and linear mixed effects models.

RESULTS

Of 794 patients (1130 admissions) 185 developed delirium and 274 developed depressed alertness. There was a dose-response association of 24-h systolic ARV with delirium (adjusted OR, 95% CI 2.15 per 5 mm Hg increase, 1.31-3.06, P < 0.017) and with depressed alertness (OR 1.89, 95% CI 1.18-3.03, P < 0.008). For 371 patients with available longitudinal cognitive scores, the decline in cognitive trajectory was accelerated after discharge (annual change OR -0.097, 95% CI -0.122 to -0.073). This acceleration increased with delirium (additional decline -0.132 [-0.233 to 0.030], P = 0.011). We found no significant association between BPV and post-ICU cognitive trajectory.

CONCLUSIONS

BPV was associated with increased likelihood of delirium in the ICU. Delirium, but not BPV, was associated with long-term cognitive decline.

The Association between Inflammatory Biomarkers and Cardiovascular Autonomic Dysfunction after Bacterial Infection

Heart rate variability (HRV) is a known measure of cardiac autonomic function. A cardiovascular autonomic dysfunction (CAD), measured as changes in HRV, is usually presented after an infectious process. The aim of the present study is to assess the association between serum inflammatory markers and CAD. For this purpose, 50 volunteers (13 of them recovering from an infection) were recruited and followed-up for 6 weeks. Their serum inflammatory biomarkers (CRP, IL1, IL4, IL6, IL10, and TNFalpha) were quantified throughout those weeks, along with their HRV resting, in response to the Valsalva maneuver, metronome breathing, standing and sustained handgrip. The correlation of within-subject changes in both HRV and inflammatory biomarkers was assessed to evaluate the concurrent changes. An inverse within-subject correlation was found between CRP and HRV in response to the Valsalva maneuver (rho (95% CI): −0.517 (−0.877 to −0.001); p = 0.032) and HRV standing (rho (95% CI): −0.490 (−0.943 to −0.036); p = 0.034). At the beginning, increased values of CRP are found along with reduced levels of HRV. Then, the CRP was reduced, accompanied by an improvement (increase) in HRV. These results suggest that CRP is a potential marker of CAD. Whether it is the cause, the consequence or a risk indicator non-causally associated is still to be determined.

Influence of ambulatory blood pressure-related indicators within 24 h on in-hospital death in sepsis patients

Background: Sepsis is a serious public health problem worldwide. Blood pressure is one of the indicators that is closely monitored in intensive-care units, and it reflects complex interactions between the internal cardiovascular control mechanism and the external environment. We aimed to determine the impact of indicators related to the ambulatory blood pressure on the prognosis of sepsis patients. Methods: This retrospective study was based on the Medical Information Mart for Intensive Care IV database. Relevant information about sepsis patients was extracted according to specific inclusion and exclusion criteria. Examined parameters included the average blood pressure, blood pressure variability (BPV), and circadian rhythm, and the study outcome was in-hospital death. We investigated the effects of these indicators on the risk of in-hospital death among sepsis patients using Cox proportional-hazards models, restricted cubic splines analysis, and subgroup analysis. Results: This study enrolled 10,316 sepsis patients, among whom 2,117 died during hospitalization. All parameters except the nighttime variation coefficient of the diastolic blood pressure (DBP) were associated with in-hospital death of sepsis patients. All parameters except for fluctuations in DBP exhibited nonlinear correlations with the outcome. The subgroup analysis revealed that some of the examined parameters were associated with in-hospital death only in certain subgroups. Conclusion: Indicators related to the ambulatory blood pressure within 24 h are related to the prognosis of sepsis patients. When treating sepsis, in addition to blood pressure, attention should also be paid to BPV and the circadian rhythm in order to improve the prognosis and the survival rate.

Assessment of Sepsis in the ICU by Linear and Complex Characterization of Cardiovascular Dynamics

Sepsis is one of the pathological conditions with the highest incidence in intensive care units. Sepsis-induced cardiac and autonomic dysfunction are well-known effects, among others, caused by a dysregulated host response to infection. In this context, we investigate the role of complex cardiovascular dynamics quantified through sample entropy indices from the inter-beat interval, systolic and diastolic blood pressure time series as well as the cross-entropy between heartbeat and systolic blood pressure in patients with sepsis in the first hour of intensive care when compared with non-septic subjects. Results show a significant (p<0.05) reduction in the probability of being septic for a unitary increase in entropy for systolic and diastolic time series (odds equal to 0.038 and 0.264, respectively) when adjusting for confounding factors. A significant (p<0.001) odds ratio (0.248) is observed also in cross-entropy, showing a reduced probability of being septic for an increase in heartbeat and systolic pressure asynchrony. The inclusion of our measures of complexity also determines an increase in the predictive ability (+0.03) of a logistic regression model reaching an area under the receiving operating and precision recall curves both equal to 0.95.Clinical relevance The study demonstrates the ability of information theory in catching a reduction of complex cardiovascular dynamics from vital signs commonly recorded in ICU. The considered complexity measures contribute to characterize sepsis development by showing a general loss of the interaction between heartbeat and pressure regulation. The extracted measures also improve the ability to identify sepsis in the first hour of intensive care.

An explainable machine learning algorithm for risk factor analysis of in-hospital mortality in sepsis survivors with ICU readmission

BACKGROUND AND OBJECTIVE

Patients who survive sepsis in the intensive care unit (ICU) (sepsis survivors) have an increased risk of long-term mortality and ICU readmission. We aim to identify the risk factors for in-hospital mortality in sepsis survivors with later ICU readmission and visualize the quantitative relationship between the individual risk factors and mortality by applying machine learning (ML) algorithm.

METHODS

Data were obtained from the Medical Information Mart for Intensive Care III (MIMIC-III) database for sepsis and non-sepsis ICU survivors who were later readmitted to the ICU. The data on the first day of ICU readmission and the in-hospital mortality was combined for the ML algorithm modeling and the SHapley Additive exPlanations (SHAP) value of the correlation between the risk factors and the outcome.

RESULTS

Among the 2970 enrolled patients, in-hospital mortality during ICU readmission was significantly higher in sepsis survivors (n = 2228) than nonsepsis survivors (n = 742) (50.4% versus 30.7%, P<0.001). The ML algorithm identified 18 features that were associated with a risk of mortality in these groups; among these, BUN, age, weight, and minimum heart rate were shared by both groups, and the remaining mean systolic pressure, urine output, albumin, platelets, lactate, activated partial thromboplastin time (APTT), potassium, pCO2, pO2, respiration rate, Glasgow Coma Scale (GCS) score for eye-opening, anion gap, sex and temperature were specific to previous sepsis survivors. The ML algorithm also calculated the quantitative contribution and noteworthy threshold of each factor to the risk of mortality in sepsis survivors.

CONCLUSION

14 specific parameters with corresponding thresholds were found to be associated with the in-hospital mortality of sepsis survivors during the ICU readmission. The construction of advanced ML techniques could support the analysis and development of predictive models that can be used to support the decisions and treatment strategies made in a clinical setting in critical care patients.

Blood pressure management after mechanical thrombectomy in stroke patients

Endovascular treatment of acute ischemic stroke (AIS) and mechanical thrombectomy (MT) is proven as a safe and effective novel treatment for emergent large vessel occlusion in the anterior cerebral circulation. However, there are still many unanswered questions on peri and post-procedural management including blood pressure (BP) control. The current guidelines recommend maintaining BP <180/105 mmHg in the first 24 h after MT. However, recent studies suggest that maintaining BP levels at lower levels in the first 24 h after successful revascularization have been associated with favorable functional outcome, reduced mortality rate, and hemorrhagic complications. Not only absolute BP but also its variation in the first 24 h after MT have been associated with neurological outcomes. Evidence on the effect of BP variability (BPV) after MT in AIS even though limited, it does indicate the association of the higher BPV in the first 24 h after MT and poor functional outcomes in AIS. In this review, we will discuss the current literature on BP management in the first 24 h after MT and the impact of BPV in the first 24 h after MT.

Blood pressure variability and outcome after acute intracerebral hemorrhage

Intracerebral hemorrhage (ICH) is life threatening neurologic event that results in significant rate of morbidity and mortality. Unfortunately, several randomized clinical trials aiming at limiting the hematoma expansion (HE) in the acute phase of ICH have not shown significant effects in improving the functional outcomes. Blood pressure variability (BPV) is common following ICH. High BPs have been associated with increased risk of bleeding and HE. Conversely, recurrent sudden decrease in BP promote perihematomal ischemia. However, it is still not clear weather BPV causes adverse prognosis following ICH or large ICHs cause fluctuations in BP. In the current review, we will discuss the mechanistic pathophysiology of BPV and the evidence regarding the role of BPV on the ICH outcomes.

Impact of Mean Arterial Pressure Fluctuation on Mortality in Critically Ill Patients

OBJECTIVE

The purpose of this study was to investigate the association between mean arterial pressure fluctuations and mortality in critically ill patients admitted to the ICU.

DESIGN

Retrospective cohort.

SETTING

All adult ICUs at a tertiary care hospital.

PATIENTS

All adult patients with complete mean arterial pressure records were selected for analysis in the Multiparameter Intelligent Monitoring in Intensive Care II database. Patients in the external cohort were newly recruited adult patients in the Medical Information Mart for Intensive Care III database.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The records of 8,242 patients were extracted. Mean arterial pressure fluctuation was calculated as follows: (mean nighttime mean arterial pressure - mean daytime mean arterial pressure)/mean arterial pressure. Patients were divided into two groups according to the degree of mean arterial pressure fluctuation: group A (between -5% and 5%) and group B (<-5% and >5%). The endpoints of this study were ICU and hospital mortality. Patients in group A (n = 4,793) had higher ICU and hospital mortality than those in group B (n = 3,449; 11.1% vs 8.1%, p < 0.001 and 13.8% vs 10.1%, p < 0.001, respectively). After adjusting for other covariates, the mean arterial pressure fluctuations between -5% and 5% were significantly correlated with ICU mortality (odds ratio, 1.296; 95% CI, 1.103-1.521; p = 0.002) and hospital mortality (odds ratio, 1.323; 95% CI, 1.142-1.531; p < 0.001). This relationship remained remarkable in patients with low or high Sequential Organ Failure Assessment scores in the sensitive analysis. Furthermore, external validation on a total of 4,502 individuals revealed that patients in group A still had significantly higher ICU (p < 0.001) and hospital mortality (p < 0.001) than those in group B.

CONCLUSIONS

The reduced mean arterial pressure fluctuation (within -5% and 5%) may be associated with ICU and hospital mortality in critically ill patients.

Cerebral Autoregulation-Guided Optimal Blood Pressure in Sepsis-Associated Encephalopathy: A Case Series

BACKGROUND

Impaired cerebral autoregulation and cerebral hypoperfusion may play a critical role in the high morbidity and mortality in patients with sepsis-associated encephalopathy (SAE). Bedside assessment of cerebral autoregulation may help individualize hemodynamic targets that optimize brain perfusion. We hypothesize that near-infrared spectroscopy (NIRS)-derived cerebral oximetry can identify blood pressure ranges that enhance autoregulation in patients with SAE and that disturbances in autoregulation are associated with severity of encephalopathy.

METHODS

Adult patients with acute encephalopathy directly attributable to sepsis were followed using NIRS-based multimodal monitoring for 12 consecutive hours. We used the correlation in time between regional cerebral oxygen saturation and mean arterial pressure (MAP) to determine the cerebral oximetry index (COx) as a measure of cerebral autoregulation. Autoregulation curves were constructed for each patient with averaged COx values sorted by MAP in 3 sequential 4-hour periods; the optimal pressure (MAP_OPT), defined as the MAP associated with most robust autoregulation (lowest COx), was identified in each period. Severity of encephalopathy was measured with Glasgow coma scale (GCS).

RESULTS

Six patients with extracranial sepsis met the stringent criteria specified, including no pharmacological sedation or neurologic premorbidity. Optimal MAP was identified in all patients and ranged from 55 to 115 mmHg. Additionally, MAP_OPT varied within individual patients over time during monitoring. Disturbed autoregulation, based on COx, was associated with worse neurologic status (GCS < 13) both with and without controlling for age and severity of sepsis (adjusted odds ratio [OR]: 2.11; 95% confidence interval [CI]: 1.77-2.52; P < .001; OR: 2.97; 95% CI: 1.63-5.43; P < .001).

CONCLUSIONS

In this high-fidelity group of patients with SAE, continuous, NIRS-based monitoring can identify blood pressure ranges that improve autoregulation. This is important given the association between cerebral autoregulatory function and severity of encephalopathy. Individualizing blood pressure goals using bedside autoregulation monitoring may better preserve cerebral perfusion in SAE than current practice.