External validation of the prediction model of intradialytic hypotension: a multicenter prospective cohort study

OBJECTIVE

Intradialytic hypotension (IDH) is a common and serious complication in patients with Maintenance Hemodialysis (MHD). The purpose of this study is to externally verify three IDH risk prediction models recently developed by Ma et al. and recalibrate, update and present the optimal model to improve the accuracy and applicability of the model in clinical environment.

METHODS

A multicenter prospective cohort study of patients from 11 hemodialysis centers in Sichuan Province, China, was conducted using convenience sampling from March 2022 to July 2022, with a follow-up period of 1 month. Model performance was assessed by: (1) Discrimination: Evaluated through the computation of the Area Under Curve (AUC) and its corresponding 95% confidence intervals. (2) Calibration: scrutinized through visual inspection of the calibration plot and utilization of the Brier score. (3) The incremental value of risk prediction and the utility of updating the model were gauged using NRI (Net Reclassification Improvement) and IDI (Integrated Discrimination Improvement). Decision Curve Analysis (DCA) was employed to evaluate the clinical benefit of updating the model.

RESULTS

The final cohort comprised 2235 individuals undergoing maintenance hemodialysis, exhibiting a 14.6% occurrence rate of IDH. The externally validated Area Under the Curve (AUC) values for the three original prediction models were 0.746 (95% CI: 0.718 to 0.775), 0.709 (95% CI: 0.679 to 0.739), and 0.735 (95% CI: 0.706 to 0.764) respectively. Conversely, the AUC value for the recalibrated and updated columnar plot model reached 0.817 (95% CI: 0.791 to 0.842), accompanied by a Brier score of 0.081. Furthermore, Decision Curve Analysis (DCA) exhibited a net benefit within the threshold probability range of 15.2% to 87.1%.

CONCLUSION

Externally validated, recalibrated, updated, and presented IDH prediction models may serve as a valuable instrument for evaluating IDH risk in clinical practice. Furthermore, they hold the potential to guide clinical providers in discerning individuals at risk and facilitating judicious clinical intervention decisions.

Intraoperative Blood Pressure Management and Its Effects on Postoperative Delirium After Cardiac Surgery: A Single-Center Retrospective Cohort Study

OBJECTIVES

There is accumulating evidence that blood pressure management might be associated with end-organ dysfunction after cardiac surgery. This study aimed to investigate the impact of intraoperative hypotension (IOH) on adverse neurologic outcomes and mortality.

DESIGN

A single-center retrospective cohort study.

SETTING

The Heart and Diabetes Centre Bad Oeynhausen NRW, Ruhr-University Bochum.

PARTICIPANTS

This retrospective cohort study included 31,315 adult patients who underwent elective cardiac surgery at the authors' institution between January 2009 and December 2018.

INTERVENTIONS

All cardiac surgery procedures except assist device implantation, organ transplantation, and emergency surgery.

MEASUREMENTS AND MAIN RESULTS

Adverse neurologic outcomes were defined as postoperative delirium and stroke. IOH was defined as mean arterial pressure below 60 mmHg for >2 minutes. The frequency of IOH episodes and the cumulative IOH duration were recorded. The association between IOH and adverse neurologic outcomes was examined with unadjusted statistical analysis and multiple logistic regression analysis. Eight hundred forty-nine (2.9%) patients developed postoperative stroke, and 2,401 (7.7%) patients developed postoperative delirium. The frequency of IOH episodes was independently associated with postoperative delirium in the multiple logistic regression analysis (odds ratio 1.02, 95% CI 1.003-1.03, p < 0.001), whereas there was no association between it and stroke.

CONCLUSION

This large retrospective monocentric cohort study revealed that increased episodes of IOH were associated with the risk of developing postoperative delirium after cardiac surgery. This might have important clinical implications with respect to careful and precise hemodynamic monitoring and proactive treatment, especially in patients with increased risk for postoperative delirium.

Skin mottling score assesses peripheral tissue hypoperfusion in critically ill patients following cardiac surgery

BACKGROUND

Skin mottling is a common manifestation of peripheral tissue hypoperfusion, and its severity can be described using the skin mottling score (SMS). This study aims to evaluate the value of the SMS in detecting peripheral tissue hypoperfusion in critically ill patients following cardiac surgery.

METHODS

Critically ill patients following cardiac surgery with risk factors for tissue hypoperfusion were enrolled (n = 373). Among these overall patients, we further defined a hypotension population (n = 178) and a shock population (n = 51). Hemodynamic and perfusion parameters were recorded. The primary outcome was peripheral hypoperfusion, defined as significant prolonged capillary refill time (CRT, > 3.0 s). The characteristics and hospital mortality of patients with and without skin mottling were compared. The area under receiver operating characteristic curves (AUROC) were used to assess the accuracy of SMS in detecting peripheral hypoperfusion. Besides, the relationships between SMS and conventional hemodynamic and perfusion parameters were investigated, and the factors most associated with the presence of skin mottling were identified.

RESULTS

Of the 373-case overall population, 13 (3.5%) patients exhibited skin mottling, with SMS ranging from 1 to 5 (5, 1, 2, 2, and 3 cases, respectively). Patients with mottling had lower mean arterial pressure, higher vasopressor dose, less urine output (UO), higher CRT, lactate levels and hospital mortality (84.6% vs. 12.2%, p < 0.001). The occurrences of skin mottling were higher in hypotension population and shock population, reaching 5.6% and 15.7%, respectively. The AUROC for SMS to identify peripheral hypoperfusion was 0.64, 0.68, and 0.81 in the overall, hypotension, and shock populations, respectively. The optimal SMS threshold was 1, which corresponded to specificities of 98, 97 and 91 and sensitivities of 29, 38 and 67 in the three populations (overall, hypotension and shock). The correlation of UO, lactate, CRT and vasopressor dose with SMS was significant, among them, UO and CRT were identified as two major factors associated with the presence of skin mottling.

CONCLUSION

In critically ill patients following cardiac surgery, SMS is a very specific yet less sensitive parameter for detecting peripheral tissue hypoperfusion.

Preoperative Renin-Angiotensin System Antagonists Intake and Blood Pressure Responses During Ambulatory Surgical Procedures: A Prospective Cohort Study

BACKGROUND

There is limited evidence to inform the association between the intake of angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs) and intraoperative blood pressure (BP) changes in an ambulatory surgery population.

METHODS

Adult patients who underwent ambulatory surgery and were discharged on the same day or within 24 hours of their procedure were enrolled in this prospective cohort study. The primary outcome of the study was early intraoperative hypotension (first 15 minutes of induction). Secondary outcomes included any hypotension, BP variability, and recovery. Hypotension was defined as a decrease in systolic BP of >30% from baseline for ≥5 minutes or a mean BP of <55 mm Hg. Four exposure groups were compared (no antihypertensives, ACEI/ARB intake <10 hours before surgery, ACEI/ARB intake ≥10 hours before surgery, and other antihypertensives).

RESULTS

Of the 537 participants, early hypotension was observed in 25% (n = 134), and any hypotension in 41.5% (n = 223). Early hypotension occurred in 30% (29 of 98) and 41% (17 of 41) with the intake of ACEI/ARBs <10 and ≥10 hours before surgery, respectively, compared to 30% (9 of 30) with other antihypertensives and 21% (79 of 368) with no antihypertensives ( P = .02). Those on antihypertensives also experienced any hypotension more frequently than those who were not on antihypertensives ( P < .001). After adjusting for age and baseline BP in a regression analysis, antihypertensive exposure groups were observed to be associated only with any intraoperative hypotension ( P = .012). In the ACEI/ARB subset, there was no evidence of an association between time since the last ACEI/ARB dose, and hypotension or minimum mean or systolic BP. Compared to normal baseline BP, BP ≥ 140/90 mm Hg increased the odds of early and any hypotension (odds ratio [OR], 3.9; 95% confidence interval [CI], 2.1-7.1 and OR, 7.7; 95% CI, 3.7-14.9, respectively; P < .001). Intraoperative variability in systolic and diastolic BP demonstrated significant differences with age, baseline BP, and antihypertensive exposure group ( P < .001).

CONCLUSIONS

Early and any hypotension occurred more frequently in those on antihypertensives than those not on antihypertensives. Unadjusted associations between antihypertensive exposure and intraoperative hypotension were largely explained by baseline hypertension rather than the timing of ACEI/ARBs or type of antihypertensive exposure. Patients with hypertension and on treatment experience more intraoperative BP variability and should be monitored appropriately.

Predictive value of estimated plasma volume for postoperative hypotension in percutaneous intramyocardial septal radiofrequency ablation treating for hypertrophic obstructive cardiomyopathy

BACKGROUND

Estimated plasma volume status (ePVS) estimated by the Duarte formula is associated with clinical outcomes in patients with heart failure. It remains unclear the predictive value of the ePVS to the postoperative hypotension (POH) in percutaneous intramyocardial septal radiofrequency ablation (PIMSRA) treating hypertrophic obstructive cardiomyopathy (HOCM).

METHODS

Data of HOCM patients who underwent PIMSRA were retrospectively collected. Preoperative ePVS was calculated using the Duarte formulas which derived from hemoglobin and hematocrit ratios. Clinical variables including physical assessment, biological and echocardiographic parameters were recorded. Patients were labeled with or without POH according to the medical record in the hospital. Univariable and multivariable logistic regression were performed to evaluate the association between ePVS and POH. Using different thresholds derived from quartiles and the best cutoff value of the receiver operating characteristic curve, the diagnostic performance of ePVS was quantified.

RESULTS

Among the 405 patients included in this study, 53 (13.1%) patients were observed with symptomatic POH. Median (IQR) of ePVS in overall patients was 3.77 (3.27~4.40) mL/g and in patients with POH were higher than those without POH. The ePVS was associated with POH, with the odds ratio of 1.669 (95% CI 1.299 ~ 2.144) per mL/g. After adjusted by potential confounders, ePVS remained independently associated with POH, with the approximate odds ratio in different models.

CONCLUSION

The preoperative ePVS derived from the Duarte formulas was independently associated with postoperative hypotension in HOCM patients who underwent PIMSRA and showed prognostic value to the risk stratification of postoperative management.

TRIAL REGISTRATION

NCT06003478 (22/08/2023).

Haemodynamic assessment and management of hypotension in the preterm

The management of low blood flow states in premature neonates is fraught with many challenges. We remain over-reliant on regimented stepwise protocols that use mean blood pressure as a threshold for intervention to guide treatment, without giving due consideration to the underlying pathophysiology. The current available evidence does not reflect the need to concentrate on the unique pathophysiology of the preterm infant and thus leads to widespread misuse of vasoactive agents that often do not provide the desired clinical effect. Therefore, understanding the underlying pathophysiological underpinnings of haemodynamic compromise may better guide choice of agent and assess physiological response to the selected intervention.

The real-world safety of sacubitril / valsartan among older adults (≥75): A pharmacovigilance study from the FDA data

BACKGROUND

Heart failure is a major cause of morbidity and mortality among older adults. Sacubitril-Valsartan (Sac/Val) has been shown to improve patients' outcomes; however, its safety profile among older adults has not been adequately examined. We therefore aimed to examine its safety profile among this population.

METHODS

We conducted a retrospective pharmacovigilance study utilizing the FDA's database of safety reports (FAERS). We employed disproportionality analysis comparing Sac/Val to angiotensin receptor blockers (ARBs). We aim to evaluate the reporting of pre-defined adverse events associated with Sac/Val (hypotension, acute kidney injury (AKI), hyperkalemia and angioedema) in two age groups: adults (< 75 years) and older adults (≥ 75). For each subgroup, we calculated reporting odds ratio (ROR) and compared them by calculating P for interaction.

RESULTS

The FAERS database encompassed 18,432 unique reports of Sac/Val. Of them, 12,630 (68.5%) subjects were adults (< 75 years), and 5802 (31.5%) were older adults (≥ 75 years), with a median age (IQR) of 68 (59-77). When compared to ARBs, Sac/Val was associated with higher reporting of hypotension, lower reporting of acute kidney injury (AKI) and hyperkalemia, and similar reporting of angioedema. Notably, we did not observe a significant interaction between the age subgroups and the risk estimates (AKI: Pinteraction = 0.72, hyperkalemia: Pinteraction = 0.94, hypotension: Pinteraction = 0.31, and angioedema: Pinteraction = 0.61).

CONCLUSIONS

In this postmarking study, none of the prespecified adverse events was reported more frequently in older adults. These findings provide reassurance for safety use of Sac/Val in older adults.

CON: The hypotension prediction index is not a validated predictor of hypotension

The Hypotension Prediction Index (HPI) algorithm is a commercial prediction algorithm developed to predict hypotension, a mean arterial pressure (MAP) below 65 mmHg. Although HPI has been investigated in several studies, recent concerns of have been raised regarding HPI's predictive abilities, which may have been overstated. A selection bias may have forced the HPI algorithm to learn almost exclusively from MAP. This CON position paper describes the selection bias further and summarises the scientific status of HPI's predictive abilities, including the meaning of a recent erratum retracting the primary conclusion of a published HPI validation study. We argue that the HPI algorithm needs re-validation or complete re-development to achieve a clinically relevant 'added value' in comparison with the predictive performance of a simple and costless MAP alarm threshold in the range of 70 to 75 mmHg.

Prevalence of postprandial hypotension in older adults: a systematic review and meta-analysis

BACKGROUND

Older adults with postprandial hypotension (PPH) increase susceptibility to falls, syncope, stroke, acute cardiovascular diseases and even death. However, the prevalence of this condition varies significantly across studies. We aimed to determine the prevalence of PPH in older adults.

METHODS

Web of Science, PubMed, Cochrane Library, Embase and CINAHL were searched from their inception until February 2023. Search terms included 'postprandial period', 'hypotension' and 'postprandial hypotension'. Eligible studies were assessed using the Joanna Briggs Institute tool. Meta-analyses were performed among similar selected studies.

RESULTS

Thirteen eligible studies were included, and data from 3,021 participants were pooled. The meta-analysis revealed a PPH prevalence of 40.5% [95% confidence interval (CI): 0.290-0.519] in older adults, and this was prevalent in the community (32.8%, 95% CI: 0.078-0.647, n = 1,594), long-term healthcare facility (39.4%, 95% CI: 0.254-0.610, n = 1,062) and geriatrics department of hospitals (49.3%, 95% CI: 0.357-0.630, n = 365). The pooled results showed significant heterogeneity (I2 > 90%), partially related to the different ages, sex, pre-prandial systolic blood pressure levels of participants, or the different criteria and methodology used to diagnose PPH.

CONCLUSIONS

PPH is a prevalent condition in older adults. Further research is needed to confirm this result, and priority should be given to establishing international consensus on PPH diagnostic criteria and designing its diagnostic procedure.

American society of anesthesiologists physical status classification significantly affects the performances of machine learning models in intraoperative hypotension inference

STUDY OBJECTIVE

To explore how American Society of Anesthesiologists (ASA) physical status classification affects different machine learning models in hypotension prediction and whether the prediction uncertainty could be quantified.

DESIGN

Observational Studies SETTING: UofL health hospital PATIENTS: This study involved 562 hysterectomy surgeries performed on patients (≥ 18 years) between June 2020 and July 2021.

INTERVENTIONS

None MEASUREMENTS: Preoperative and intraoperative data is collected. Three parametric machine learning models, including Bayesian generalized linear model (BGLM), Bayesian neural network (BNN), a newly proposed BNN with multivariate mixed responses (BNNMR), and one nonparametric model, Gaussian Process (GP), were explored to predict patients' diastolic and systolic blood pressures (continuous responses) and patients' hypotensive event (binary response) for the next five minutes. Data was separated into American Society of Anesthesiologists (ASA) physical status class 1- 4 before being read in by four machine learning models. Statistical analysis and models' constructions are performed in Python. Sensitivity, specificity, and the confidence/credible intervals were used to evaluate the prediction performance of each model for each ASA physical status class.

MAIN RESULTS

ASA physical status classes require distinct models to accurately predict intraoperative blood pressures and hypotensive events. Overall, high sensitivity (above 0.85) and low uncertainty can be achieved by all models for ASA class 4 patients. In contrast, models trained without controlling ASA classes yielded lower sensitivity (below 0.5) and larger uncertainty. Particularly, in terms of predicting binary hypotensive event, for ASA physical status class 1, BNNMR yields the highest sensitivity of 1. For classes 2 and 3, BNN has the highest sensitivity of 0.429 and 0.415, respectively. For class 4, BNNMR and GP are tied with the highest sensitivity of 0.857. On the other hand, the sensitivity is just 0.031, 0.429, 0.165 and 0.305 for BNNMR, BNN, GBLM and GP models respectively, when training data is not divided by ASA physical status classes. In terms of predicting systolic blood pressure, the GP regression yields the lowest root mean squared errors (RMSE) of 2.072, 7.539, 9.214 and 0.295 for ASA physical status classes 1, 2, 3 and 4, respectively, but a RMSE of 126.894 if model is trained without controlling the ASA physical status class. The RMSEs for other models are far higher. RMSEs are 2.175, 13.861, 17.560 and 22.426 for classes 1, 2, 3 and 4 respectively for the BGLM. In terms of predicting diastolic blood pressure, the GP regression yields the lowest RMSEs of 2.152, 6.573, 5.371 and 0.831 for ASA physical status classes 1, 2, 3 and 4, respectively; RMSE of 8.084 if model is trained without controlling the ASA physical status class. The RMSEs for other models are far higher. Finally, in terms of the width of the 95% confidence interval of the mean prediction for systolic and diastolic blood pressures, GP regression gives narrower confidence interval with much smaller margin of error across all four ASA physical status classes.

CONCLUSIONS

Different ASA physical status classes present different data distributions, and thus calls for distinct machine learning models to improve prediction accuracy and reduce predictive uncertainty. Uncertainty quantification enabled by Bayesian inference provides valuable information for clinicians as an additional metric to evaluate performance of machine learning models for medical decision making.

Droxidopa or Atomoxetine for Refractory Hypotension in Critically Ill Cardiothoracic Surgery Patients

OBJECTIVE

To evaluate the effects of droxidopa or atomoxetine on intravenous (IV) vasoactive agent discontinuation in cardiothoracic intensive care unit (ICU) patients with hypotension refractory to midodrine.

DESIGN

Single-center, retrospective cohort study.

SETTING

Tertiary- and quaternary-care university teaching hospital.

PARTICIPANTS

Included patients who received at least 4 consecutive doses of droxidopa or atomoxetine and remained on concurrent midodrine. Patients were excluded if they received study medication before admission, had clinical deterioration after study medication initiation requiring additional vasoactives/escalation of IV vasoactive dosage for at least 12 hours, had a diagnosis of hepatorenal syndrome, were prisoners, or were pregnant.

INTERVENTIONS

Droxidopa, atomoxetine, or both.

MEASUREMENTS AND MAIN RESULTS

The primary endpoint was time to discontinuation of IV vasoactive agents after initiation of study medication, analyzed using a Kaplan-Meier estimate with the Wilcoxon method, censoring death within 24 hours of the last dose of study medication. No adjustment for repetitive analyses was made, as the analysis was hypothesis-generating. Of the 72 charts reviewed, 45 patients met inclusion criteria (18 atomoxetine, 17 droxidopa, and 10 both). There were no differences in median time to discontinuation of IV vasoactive agents (21.9 days v 8.0 days v 13.9 days, respectively; p = 0.259) or ICU or hospital length of stay between groups. A higher percentage of patients who survived to hospital discharge received both study medications or droxidopa alone (90% v 76.5%) than atomoxetine alone (44.4%, p = 0.028).

CONCLUSIONS

Droxidopa and atomoxetine are oral vasoactive agents with potential mechanisms to facilitate IV vasopressor weaning for patients in the ICU with hypotension refractory to midodrine, but further prospective research is needed.

EARLY BLOOD LACTATE AS A BIOMARKER FOR CARDIOVASCULAR COLLAPSE IN EXPERIMENTAL SEPSIS

ABSTRACT

Cecal ligation and puncture (CLP) is the gold standard model for studying septic shock, which is characterized by hypotension and hyporeactivity to vasoconstrictors. However, approximately 30% of CLP animals do not exhibit cardiovascular changes, requiring more replicates because of the high variability of the model. Therefore, biomarkers enabling the early prediction of cardiovascular collapse in sepsis would greatly benefit sepsis nonclinical studies, refining experimental models and improving clinical translation. Thus, this study aimed to test whether the early increase in lactate levels could predict hypotension and hyporesponsiveness to vasoconstrictors in a rat model of sepsis. Male and female Wistar rats were subjected to CLP or sham procedure. Tail blood lactate was measured 6, 12, and 24 h after surgery. Then, inflammatory, biochemical, and hemodynamic parameters were evaluated. Rats subjected to CLP developed hypotension, hyporesponsiveness to vasoconstrictors, an intense inflammatory process, and increased plasma markers of organ dysfunction. By using receiver operating characteristics curve analysis, we have established that a lactate value of 2.45 mmol/L can accurately discriminate between a rat exhibiting a normal vasoconstrictive response and a vasoplegic rat with 84% accuracy (area under the curve: 0.84; confidence interval [CI]: 0.67-1.00). The sensitivity, which is the ability to identify a diseased rat (true positive), was 75% (CI: 41-95), and the true negative rate was 81% (CI: 57-93). Therefore, early measurement of lactate levels in sepsis could serve as a valuable biomarker for distinguishing vasoplegic rats from those exhibiting normal vasoconstrictive responses.

Inferior vena cava collapsibility index as a predictor of hypotension after induction of general anesthesia in hypertensive patients

BACKGROUND

Hypertensive patients are more susceptible to develop hypotension after the induction of general anesthesia (GA), most likely due to hypovolemia. An inferior vena cava collapsibility index (IVCCI) > 40-50% can predict hypotension after the induction of GA in the general population by variable accuracies. The current study aimed to investigate IVCCI% as a predictor of postinduction hypotension in hypertensive patients undergoing noncardiac surgery.

METHODS

Ultrasound IVCCI % was assessed for all controlled hypertensive patients immediately before induction of GA. After induction of GA, patients were diagnosed with postinduction hypotension if their systolic arterial pressure (SAP) dropped by ≥ 30% of the baseline value and/or mean arterial pressure (MAP) dropped to < 65 mmHg up to 15 min after intubation. The receiver operating characteristic (ROC) curve of IVCCI% was compared to patients' classification either developing hypotension after induction of GA or not as a gold standard.

RESULTS

Of the 153 patients who completed the study, 62 (40.5%) developed hypotension after the induction of GA, and 91 (59.5%) did not. An IVCCI > 39% predicted the occurrence of postinduction hypotension with high accuracy (84%) (AUC 0.908, P < 0.001). The area of uncertainty (by gray zone analysis) of IVCCI lies at values from 39 to 45%. This gray zone included 21 patients (13.7% of all patients).

CONCLUSION

An inferior vena cava collapsibility index > 39% before anesthetic induction can be a simple noninvasive reliable predictor of hypotension after the induction of GA for hypertensive patients not treated with angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) and undergoing noncardiac surgery.

TRIAL REGISTRATION

This clinical trial was approved by the Institutional Review Board (IRB) at Zagazig University (ZUIRB #9424 dated 03/04/2022), and patients' informed consent for participation in the study was obtained during the period from May 2022 to May 2023. All study procedures were carried out in accordance with the ethical standards of the Helsinki Declaration of 2013.

Evaluation and management of hypotensive patients in the emergency department

Hypotension can be a sign of significant underlying pathology, and if it is not rapidly identified and addressed, it can contribute to organ injury. Treatment of hypotension is best targeted at the underlying etiology, although this can be difficult to discern early in a patient's disease course. Expedited bedside evaluation with rapid initiation of treatment based on the most likely underlying etiology is paramount, followed by serial reassessment of the patient's condition. This review synthesizes the key aspects of the presentation and evaluation of a patient with hypotension, including salient historical features, physical examination findings, and diagnostic tests that can help guide treatment.

Tissue plasminogen activator challenge thrombelastography is the most accurate assay in predicting the need for massive transfusion in hypotensive trauma patients

BACKGROUND

Tissue plasminogen activator (tPA) added to thrombelastography (TEG) detects hyperfibrinolysis by measuring clot lysis at 30 min (tPA-challenge-TEG). We hypothesize that tPA-challenge-TEG is a better predictor of massive transfusion (MT) than existing strategies in trauma patients with hypotension.

METHODS

Trauma activation patients (TAP, 2014-2020) with 1) systolic blood pressure <90 mmHg (early) or 2) those who arrived normotensive but developed hypotension within 1H postinjury (delayed) were analyzed. MT was defined as >10 RBC U/6H postinjury or death within 6H after ≥1 RBC unit. Area under the receiver operating characteristics curves were used to compare predictive performance. Youden index determined optimal cutoffs.

RESULTS

tPA-challenge-TEG was the best predictor of MT in the early hypotension subgroup (N = 212) with positive (PPV) and negative predictive values (NPV) of 75.0%, and 77.6%, respectively. tPA-challenge-TEG was a better predictor of MT than all but TASH (PPV = 65.0%, NPV = 93.3%) in the delayed hypotension group (N = 125).

CONCLUSIONS

The tPA-challenge-TEG is the most accurate predictor of MT in trauma patients arriving hypotensive and offers early recognition of MT in patients with delayed hypotension.

Incorporating intraoperative blood pressure time-series variables to assist in prediction of acute kidney injury after type a acute aortic dissection repair: an interpretable machine learning model

BACKGROUND

Acute kidney injury (AKI) is a common and serious complication after the repair of Type A acute aortic dissection (TA-AAD). However, previous models have failed to account for the impact of blood pressure fluctuations on predictive performance. This study aims to develop machine learning (ML) models combined with intraoperative medicine and blood pressure time-series data to improve the accuracy of early prediction for postoperative AKI risk.

METHODS

Indicators reflecting the duration and depth of hypotension were obtained by analyzing continuous mean arterial pressure (MAP) monitored intraoperatively with multiple thresholds (<65, 60, 55, 50) set in the study. The predictive features were selected by logistic regression and the least absolute shrinkage and selection operator (LASSO), and 4 ML models were built based on the above features. The performance of the models was evaluated by area under receiver operating characteristic curve (AUROC), calibration curve and decision curve analysis (DCA). Shapley additive interpretation (SHAP) was used to explain the prediction models.

RESULTS

Among the indicators reflecting intraoperative hypotension, 65 mmHg showed a statistically superior difference to other thresholds in patients with or without AKI (p < .001). Among 4 models, the extreme gradient boosting (XGBoost) model demonstrated the highest AUROC: 0.800 (95% 0.683-0.917) and sensitivity: 0.717 in the testing set and was verified the best-performing model. The SHAP summary plot indicated that intraoperative urine output, cumulative time of mean arterial pressure lower than 65 mmHg outside cardiopulmonary bypass (OUT_CPB_MAP_65 time), autologous blood transfusion, and smoking were the top 4 features that contributed to the prediction model.

CONCLUSION

With the introduction of intraoperative blood pressure time-series variables, we have developed an interpretable XGBoost model that successfully achieve high accuracy in predicting the risk of AKI after TA-AAD repair, which might aid in the perioperative management of high-risk patients, particularly for intraoperative hemodynamic regulation.

Development and validation of a nomogram for predicting intraoperative hypotension in cardiac valve replacement

Background: Cardiac valve replacement risks include intraoperative hypotension, endangering organ perfusion. Our nomogram predicted hypotension risk in valve surgery, guiding early intervention. Methods: Analyzing 561 patients from July to November 2022, we developed a nomogram to predict hypotension in valve replacement patients, validated using data from December 2022 to January 2023 on 241 patients, with robust statistical confirmation. Results: Our study identified age, hypertension, left ventricular ejection fraction and serum creatinine as hypotension predictors. The resulting nomogram, validated with high concordance index and area under the curve scores, provided a clinically useful tool for managing intraoperative risk. Conclusion: For valve replacement patients, factors like age, hypertension, low left ventricular ejection fraction and high serum creatinine predicted hypotension risk. Our nomogram enabled clinicians to quantify this risk and proactively manage it.

Evaluation of the accuracy of oscillometric non-invasive blood pressure measurement at the ankle in children during general anesthesia

This study aimed to evaluate the accuracy of oscillometric blood pressure measurement at the ankle in children using invasive blood pressure as reference standard. This prospective observational study included children undergoing noncardiac surgery. Paired radial invasive and ankle non-invasive blood pressure measurements were obtained. Delta blood pressure was calculated as the difference between two consecutive readings. The primary outcome was the mean bias and agreement between the two methods using the Bland-Altman analysis. The ISO standard was fulfilled if the mean bias between the two methods was ≤ 5 ± 8 mmHg. Other outcomes included the trending ability of ankle blood pressure using the four-quadrant plot and the accuracy of ankle measurement to detect hypotension using area under receiver operating characteristic curve (AUC) analysis. We analyzed 683 paired readings from 86 children. The mean bias between the two methods for systolic, diastolic, and mean blood pressure (SBP, DBP, MAP) was - 7.2 ± 10.7, 4.5 ± 12.8, and - 1.8 ± 8.2 mmHg, respectively. The concordance rate of ankle blood pressure was 72%, 71%, and 77% for delta SBP, DBP and MAP, respectively. The AUC (95% confidence interval) for ankle MAP ability to detect hypotension was 0.91 (0.89-0.93) with negative predictive value of 100% at cut-off value ≤ 70 mmHg, We concluded that in pediatric population undergoing noncardiac surgery, ankle blood pressure was not interchangeable with the corresponding invasive readings with the ankle MAP having the least bias compared to SBP and DBP. An ankle MAP > 70 mmHg can exclude hypotension with negative predictive value of 100%.

A prospective comparison of invasive and non-invasive blood pressure in children undergoing cardiac catheterization

BACKGROUND

Blood pressure measurement is a standard of monitoring during general anesthesia. Invasive measurement is considered the gold standard but is less commonly used than non-invasive. Automated oscillometric blood pressure devices measure the mean arterial pressure (MAP) and use an algorithm to determine the systolic and diastolic pressures. Few devices have been validated in children, particularly during anesthesia. Few studies have assessed the agreement between invasive and non-invasive blood pressure measurements in children.

METHODS

This was a multi-center prospective observational study of children under 16 years undergoing cardiac catheterization with general anesthesia. Paired invasive and non-invasive blood pressure measurements were recorded for each patient during stable periods of the procedure. Correlation within and between sites was assessed with Pearson's correlation coefficient, and agreement was examined using Bland-Altman methodology to determine bias. Agreement during episodes of hypotension and for age and weight was also determined. Bias greater than 5 mmHg and standard deviation greater than 8 mmHg was considered clinically significant. The primary end point was agreement of MAP measurements.

RESULTS

A total of 683 paired blood pressure values were collected from 254 children in three pediatric hospitals. Median [IQR] age and weight were 3 [1-7] years and 13.9 [8-23] Kg. The overall bias (SD) for mean arterial pressure values was 7.2 (11.4) mmHg. During hypotension (190 readings), the bias (SD) was 15 (11.0) mmHg. The non-invasive MAP was frequently higher than invasive MAP during infancy, and lower in older children.

CONCLUSION

Automated oscillometric blood pressure measurement is unreliable in anesthetized children during cardiac catheterization. Invasive pressure measurement should be considered for high-risk cases.

Prediction of intradialytic hypotension using pre-dialysis features-a deep learning-based artificial intelligence model

BACKGROUND

Intradialytic hypotension (IDH) is a serious complication of hemodialysis (HD) that is associated with increased risks of cardiovascular morbidity and mortality. However, its accurate prediction remains a clinical challenge. The aim of this study was to develop a deep learning-based artificial intelligence (AI) model to predict IDH using pre-dialysis features.

METHODS

Data from 2007 patients with 943 220 HD sessions at seven university hospitals were used. The performance of the deep learning model was compared with three machine learning models (logistic regression, random forest and XGBoost).

RESULTS

IDH occurred in 5.39% of all studied HD sessions. A lower pre-dialysis blood pressure (BP), and a higher ultrafiltration (UF) target rate and interdialytic weight gain in IDH sessions compared with non-IDH sessions, and the occurrence of IDH in previous sessions was more frequent among IDH sessions compared with non-IDH sessions. Matthews correlation coefficient and macro-averaged F1 score were used to evaluate both positive and negative prediction performances. Both values were similar in logistic regression, random forest, XGBoost and deep learning models, developed with data from a single session. When combining data from the previous three sessions, the prediction performance of the deep learning model improved and became superior to that of other models. The common top-ranked features for IDH prediction were mean systolic BP (SBP) during the previous session, UF target rate, pre-dialysis SBP, and IDH experience during the previous session.

CONCLUSIONS

Our AI model predicts IDH accurately, suggesting it as a reliable tool for HD treatment.

Continuous Finger-cuff versus Intermittent Oscillometric Arterial Pressure Monitoring and Hypotension during Induction of Anesthesia and Noncardiac Surgery: The DETECT Randomized Trial

BACKGROUND

Finger-cuff methods allow noninvasive continuous arterial pressure monitoring. This study aimed to determine whether continuous finger-cuff arterial pressure monitoring helps clinicians reduce hypotension within 15 min after starting induction of anesthesia and during noncardiac surgery. Specifically, this study tested the hypotheses that continuous finger-cuff-compared to intermittent oscillometric-arterial pressure monitoring helps clinicians reduce the area under a mean arterial pressure of 65 mmHg within 15 min after starting induction of anesthesia and the time-weighted average mean arterial pressure less than 65 mmHg during noncardiac surgery.

METHODS

In this single-center trial, 242 noncardiac surgery patients were randomized to unblinded continuous finger-cuff arterial pressure monitoring or to intermittent oscillometric arterial pressure monitoring (with blinded continuous finger-cuff arterial pressure monitoring). The first of two hierarchical primary endpoints was the area under a mean arterial pressure of 65 mmHg within 15 min after starting induction of anesthesia; the second primary endpoint was the time-weighted average mean arterial pressure less than 65 mmHg during surgery.

RESULTS

Within 15 min after starting induction of anesthesia, the median (interquartile range) area under a mean arterial pressure of 65 mmHg was 7 (0, 24) mmHg × min in 109 patients assigned to continuous finger-cuff monitoring versus 19 (0.3, 60) mmHg × min in 113 patients assigned to intermittent oscillometric monitoring (P = 0.004; estimated location shift: -6 [95% CI: -15 to -0.3] mmHg × min). During surgery, the median (interquartile range) time-weighted average mean arterial pressure less than 65 mmHg was 0.04 (0, 0.27) mmHg in 112 patients assigned to continuous finger-cuff monitoring and 0.40 (0.03, 1.74) mmHg in 115 patients assigned to intermittent oscillometric monitoring (P < 0.001; estimated location shift: -0.17 [95% CI: -0.41 to -0.05] mmHg).

CONCLUSIONS

Continuous finger-cuff arterial pressure monitoring helps clinicians reduce hypotension within 15 min after starting induction of anesthesia and during noncardiac surgery compared to intermittent oscillometric arterial pressure monitoring.

EDITOR’S PERSPECTIVE

Hypotension at heart failure discharge: Should it be a limiting factor for drug titration?

BACKGROUND

Medical treatment in Heart Failure (HF) with reduced ejection fraction (HFrEF; LVEF ≤40%) has shifted towards quadruple therapy. Maximum tolerated dose is the goal, yet no hypotension's cut-off point has been specified. In this work, we analyze the impact of intensive drug titration in clinical events, focusing on low blood pressure (BP) patients at hospital discharge.

METHODS AND RESULTS

Retrospective analysis of 713 patients with HFrEF discharged after an acute HF event (mean LVEF 30 ± 5%). Mean SBP was 112.4 ± 16.5 mmHg and 50.6% were discharged on triple therapy. We considered hypotension as a Systolic blood pressure (SBP) <100 mmHg (21.7% of patients, mean SBP was 112.4 ± 16.5 mmHg) and codified the intensity of drug therapy in 5 stages from untreated to very high therapy intensity. The impact of the intensity of treatment was analysed with a propensity score and increasing the intensity was associated in the whole cohort with a reduction of the composite outcome of all-cause mortality and HF readmission, (HR 0.69; CI95% 0.57-0.85, p < 0.001) and benefit in mortality was maintained for SBP < 100 mmHg (HR 0.42; CI95% 0.22-0.82; p = 0.011). Moreover, therapy intensity was clearly associated with lower risk of HF-hospitalization and death after the additional regression, considering SBP as a covariate, in the whole cohort (HR 0.70; CI95% 0.57-0.85; p < 0.001).

CONCLUSIONS

In this retrospective cohort analysis, patients with HFrEF and an acute-HF admission, intensive drug dose titration was related to better outcomes, even in patients with low blood pressure at hospital discharge. Therefore, hypotension is not a contraindication for NHB uptitration.

Development and validation of AI-based triage support algorithms for prevention of intradialytic hypotension

BACKGROUND

Intradialytic hypotension remains one of the most recurrent complications of dialysis sessions. Inadequate management can lead to adverse outcomes, highlighting the need to develop personalized approaches for the prevention of intradialytic hypotension. Here, we sought to develop and validate two AI-based risk models predicting the occurrence of symptomatic intradialytic hypotension at different time points.

METHODS

The models were built using the XGBoost algorithm and they predict the occurrence of intradialytic hypotension in the next dialysis session and in the next month. The initial dataset, obtained from routinely collected data in the EuCliD® Database, was split to perform model derivation, training and validation. Model performance was evaluated by concordance statistic and calibration charts; the importance of features was assessed with the Shapley Additive Explanation (SHAP) methodology.

RESULTS

The final dataset included 1,249,813 dialysis sessions, and the incidence rate of intradialytic hypotension was 10.07% (95% CI 10.02-10.13). Our models retained good discrimination (AUC around 0.8) and a suitable calibration yielding to the selection of three classification thresholds identifying four distinct risk groups. Variables providing the most significant impact on risk estimates were blood pressure dynamics and other metrics mirroring hemodynamic instability over time.

CONCLUSIONS

Recurrent symptomatic intradialytic hypotension could be reliably and accurately predicted using routinely collected data during dialysis treatment and standard clinical care. Clinical application of these prediction models would allow for personalized risk-based interventions for preventing and managing intradialytic hypotension.

Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD

Intradialytic hypotension is common in patients who are on hemodialysis. We applied deep learning techniques to ECGs to predict patients at risk of IDH. The performance of the model was good with an AUC of 0.763 and AUPRC of 0.35.

Predicting intraoperative hypotension: from hope to hype and back to reality

The analysis of arterial pressure waveforms with machine learning algorithms has been proposed to predict intraoperative hypotension. The ability to forecast arterial hypotension 5-15 min ahead of the fall in blood pressure allows clinicians to be pro-active instead of reactive, and could potentially decrease postoperative morbidity. However, the predictive value of machine learning algorithms has been overestimated due to selection bias in several clinical studies, and they might not be superior to mere observation of arterial pressure. Continuous blood pressure monitoring enables immediate detection of hypotension, and giving fluid, vasopressors or inotropes to patients who are not yet (and might never become) hypotensive based on an algorithm is questionable. Finally, recent prospective interventional studies suggest that reducing intraoperative hypotension does not improve postoperative outcomes.

Systolic Time Interval Extraction in Hypertensive and Hypotensive Pig Models Using Wearable Near-Field Radio-Frequency Sensors

Screening and monitoring for cardiovascular diseases (CVDs) can be enabled by analyzing systolic time intervals (STIs). As CVDs have a strong causal correlation with hypertension, it is important to validate STI sensor accuracy in hypertensive hearts to ensure consistent performance in this prevalent cardiac disease state. This work presents STI extraction using a non-invasive near-field radio-frequency (RF) sensor during normotension, hypertension, and hypotension in a pig model. Waveform features of semilunar and atrioventricular valve dynamics during systole were extracted to derive isovolumic contraction time (ICT) and left ventricular ejection time (LVET), benchmarked by a phonocardiogram and aortic catheterization. Study-wide mean relative ICT and LVET errors were -4.4ms and -3.6ms, respectively, demonstrating high accuracy during both normal and abnormal systemic pressures.Clinical relevance- This work demonstrates accurate STI extraction with relative error less than 5 ms from a non-invasive near-field RF sensor during normotensive, hypotensive, and hypertensive systemic pressures, validating the sensor's accuracy as a screening tool during this disease state.

Predictive ability of pulse oximetry-derived indices for hypotension after spinal anaesthesia for caesarean section: protocol for a systematic review and meta-analysis

INTRODUCTION

In general, caesarean sections are performed under spinal anaesthesia. Hypotension after spinal anaesthesia adversely affects both the mother and fetus. Although several studies have used pulse oximetry-derived indices, such as pulse perfusion index (PI) and Pleth variability index (PVI), to predict hypotension after spinal anaesthesia, the predictive ability of the PI and PVI remain controversial.

METHODS AND ANALYSIS

We prepared this protocol following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines. We will conduct searches of MEDLINE, Embase, Web of Science, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Clinicaltrial.gov, European Union Clinical Trials Register (EU-CTR), WHO International Clinical Trials Registry Platform (ICTRP) and University Hospital Medical Information Network Clinical Trials Registry (UMIN) from inception until 8 October 2022. We will include retrospective and prospective observational studies and randomised controlled trials that evaluated the predictive ability of PI and PVI for hypotension after spinal anaesthesia for caesarean section, published in any language. We will exclude case reports, case series and animal studies. Two authors will independently scan and select eligible studies and perform data extraction and assessment of risk of bias. We will estimate predictive ability of PI and PVI as indices of hypotension after spinal anaesthesia for caesarean section using the Reitsma-type bivariate random-effects synthesis model and the hierarchical summary receiver operating characteristic curve. We will assess the quality of evidence using the Grading of Recommendation Assessment, Development and Evaluation approach.

ETHICS AND DISSEMINATION

Ethics approval is not required as the systematic review will use existing published data. The results will be submitted for publication in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42022362596.

Relative contributions of anaemia and hypotension to myocardial infarction and renal injury: Post hoc analysis of the POISE-2 trial

BACKGROUND

Hypotension and postoperative anaemia are associated with myocardial and renal injury after noncardiac surgery, but the interaction between them remains unknown.

OBJECTIVES

To test the hypothesis that a double-hit of postoperative anaemia and hypotension synergistically worsens a 30-day composite of myocardial infarction (MI) and mortality and acute kidney injury (AKI). Characterising the interaction when hypotension and anaemia occur at same time on myocardial infarction and acute kidney injury.

DESIGN

Post hoc analysis of the POISE-2 trial.

SETTING

Patients were enrolled between July 2010 and December 2013 at 135 hospitals in 23 countries.

PATIENTS

Adults at least 45 years old with known or suspected cardiovascular disease. We excluded patients without available postoperative haemoglobin measurements or hypotension duration records. Exposures were the lowest haemoglobin concentration and the average daily duration of SBP less than 90 mmHg within the first four postoperative days.

MAIN OUTCOME MEASURES

The primary outcome was a collapsed composite of nonfatal MI and all-cause mortality during the initial 30 postoperative days; our secondary outcome was AKI.

RESULTS

We included 7940 patients. The mean ± SD lowest postoperative haemoglobin was 10 ± 2 g dl -1 , and 24% of the patients had SBP less than 90 mmHg with daily duration ranging from 0 to 15 h. Four hundred and nine (5.2%) patients had an infarction or died within 30 postoperative days, and 417 (6.4%) patients developed AKI. Lowest haemoglobin concentrations less than 11 g dl -1 , and duration of SBP less than 90 mmHg was associated with greater hazard of composite outcome of nonfatal MI and all-cause mortality, as well as with AKI. However, we did not find significant multiplicative interactions between haemoglobin splines and hypotension duration on the primary composite or on AKI.

CONCLUSION

Postoperative anaemia and hypotension were meaningfully associated with both our primary composite and AKI. However, lack of significant interaction suggests that the effects of hypotension and anaemia are additive rather than multiplicative.

TRIAL REGISTRATION

Clinicaltrials.gov: NCT01082874.

Adverse Events During Apnea Testing for the Determination of Death by Neurologic Criteria: A Single-Center, Retrospective Pediatric Cohort

OBJECTIVES

To report the prevalence of adverse events in children undergoing apnea testing as part of the determination of death by neurologic criteria (DNC).

DESIGN

Single-center, retrospective study.

SETTING

Academic children's hospital that is a Level I Trauma Center.

PATIENTS

All children who underwent apnea testing to determine DNC from July 2013 to June 2020.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We abstracted the medical history, blood gases, ventilator settings, blood pressures, vasoactive infusions, intracranial pressures, chest radiographs, and echocardiograms for all apnea tests as well as any ancillary test. Adverse events were defined as hypotension, hypoxia, pneumothorax, arrhythmia, intracranial hypertension, and cardiac arrest. Fifty-eight patients had 105 apnea tests. Adverse events occurred in 21 of 105 apnea tests (20%), the most common being hypotension (15/105 [14%]) and hypoxia (4/105 [4%]). Five of 21 apnea tests (24%) with adverse events were terminated prematurely (three for hypoxia, one for hypotension, and one for both hypoxia and hypotension) but the patients did not require persistent escalation in care. In the other 16 of 21 apnea tests (76%) with adverse events, clinical changes were transient and managed by titrating vasoactive infusions or completing the apnea test.

CONCLUSIONS

In our center, 20% of all apnea tests were associated with adverse events. Only 5% of all apnea tests required premature termination and the remaining 15% were completed and the adverse events resolved with medical care.

A Machine Learning Approach for Predicting Real-time Risk of Intraoperative Hypotension in Traumatic Brain Injury

BACKGROUND

Traumatic brain injury (TBI) is a major cause of death and disability. Episodes of hypotension are associated with worse TBI outcomes. Our aim was to model the real-time risk of intraoperative hypotension in TBI patients, compare machine learning and traditional modeling techniques, and identify key contributory features from the patient monitor and medical record for the prediction of intraoperative hypotension.

METHODS

The data included neurosurgical procedures in 1005 TBI patients at an academic level 1 trauma center. The clinical event was intraoperative hypotension, defined as mean arterial pressure <65 mm Hg for 5 or more consecutive minutes. Two types of models were developed: one based on preoperative patient-level predictors and one based on intraoperative predictors measured per minute. For each of these models, we took 2 approaches to predict the occurrence of a hypotensive event: a logistic regression model and a gradient boosting tree model.

RESULTS

The area under the receiver operating characteristic curve for the intraoperative logistic regression model was 0.80 (95% confidence interval [CI]: 0.78-0.83), and for the gradient boosting model was 0.83 (95% CI: 0.81-0.85). The area under the precision-recall curve for the intraoperative logistic regression model was 0.16 (95% CI: 0.12-0.20), and for the gradient boosting model was 0.19 (95% CI: 0.14-0.24). Model performance based on preoperative predictors was poor. Features derived from the recent trend of mean arterial pressure emerged as dominantly predictive in both intraoperative models.

CONCLUSIONS

This study developed a model for real-time prediction of intraoperative hypotension in TBI patients, which can use computationally efficient machine learning techniques and a streamlined feature-set derived from patient monitor data.

Safety and tolerability of Sacubitril/Valsartan in heart failure patient with reduced ejection fraction

BACKGROUND

Angiotensin receptor blocker and a neprilysin inhibitor (ARNI) has emerged as an innovative therapy for patients of heart failure with reduced ejection fraction (HFrEF). The purpose of this study was to assess the safety and tolerability of Sacubitril/Valsartan in patient with HFrEF in Pakistani population.

METHODS

This proof-of-concept, open label non-randomized clinical trial was conducted at a tertiary care cardiac center of Karachi, Pakistan. Patients with HFrEF were prescribed with Sacubitril/Valsartan and followed for 12 weeks for the assessment of safety and tolerability. Safety measures included incidence of hypotension, renal dysfunction, hyperkalemia, and angioedema.

RESULTS

Among the 120 HFrEF patients, majority were male (79.2%) with means age of 52.73 ± 12.23 years. At the end of 12 weeks, four (3.3%) patients died and eight (6.7%) dropped out of the study. In the remaining 108 patients, 80.6% (87) of the patients were tolerant to the prescribed dose. Functional class improved gradually with 75.0% (81) in class I and 24.1% (26) in class II, and only one (0.9%) patient in class III at the end of 12 weeks. Hyperkalemia remains the main safety concern with incidence rate of 21.3% (23) followed by hypotension in 19.4% (21), and renal dysfunction in 3.7% (4) of the patients.

CONCLUSIONS

Sacubitril/Valsartan therapy in HFrEF patients is safe and moderately tolerated among the Pakistani population. It can be used as first line of treatment for these patients.

TRIAL REGISTRATION

NCT05387967. Registered 24 May 2022-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT05387967.

Preoperative Identification of Patient-Dependent Blood Pressure Targets Associated With Low Risk of Intraoperative Hypotension During Noncardiac Surgery

BACKGROUND

Intraoperative hypotension (IOH) is strongly linked to organ system injuries and postoperative death. Blood pressure itself is a powerful predictor of IOH; however, it is unclear which pressures carry the lowest risk and may be leveraged to prevent subsequent hypotension. Our objective was to develop a model that predicts, before surgery and according to a patient's unique characteristics, which intraoperative mean arterial pressures (MAPs) between 65 and 100 mm Hg have a low risk of IOH, defined as an MAP <65 mm Hg, and may serve as testable hemodynamic targets to prevent IOH.

METHODS

Adult, noncardiac surgeries under general anesthesia at 2 tertiary care hospitals of the University of Pittsburgh Medical Center were divided into training and validation cohorts, then assigned into smaller subgroups according to preoperative risk factors. Primary outcome was hypotension risk, defined for each intraoperative MAP value from 65 to 100 mm Hg as the proportion of a value's total measurements followed by at least 1 MAP <65 mm Hg within 5 or 10 minutes, and calculated for all values in each subgroup. Five models depicting MAP-associated IOH risk were compared according to best fit across subgroups with proportions whose confidence interval was <0.05. For the best fitting model, (1) performance was validated, (2) low-risk MAP targets were identified according to applied benchmarks, and (3) preoperative risk factors were evaluated as predictors of model parameters.

RESULTS

A total of 166,091 surgeries were included, with 121,032 and 45,059 surgeries containing 5.4 million and 1.9 million MAP measurements included in the training and validation sets, respectively. Thirty-six subgroups with at least 21 eligible proportions (confidence interval <0.05) were identified, representing 92% and 94% of available MAP measurements, respectively. The exponential with theta constant model demonstrated the best fit (weighted sum of squared error 0.0005), and the mean squared error of hypotension risk per MAP did not exceed 0.01% in validation testing. MAP targets ranged between 69 and 90 mm Hg depending on the subgroup and benchmark used. Increased age, higher American Society of Anesthesiologists physical status, and female sexindependently predicted ( P < .05) hypotension risk curves with less rapid decay and higher plateaus.

CONCLUSIONS

We demonstrate that IOH risk specific to a given MAP is patient-dependent, but predictable before surgery. Our model can identify intraoperative MAP targets before surgery predicted to reduce a patient's exposure to IOH, potentially allowing clinicians to develop more personalized approaches for managing hemodynamics.

Model for Predicting Complications of Hemodialysis Patients Using Data From the Internet of Medical Things and Electronic Medical Records

Intelligent models for predicting hemodialysis-related complications, i.e., hypotension and the deterioration of the quality or obstruction of the AV fistula, based on machine learning (ML) methods were established to offer early warnings to medical staff and give them enough time to provide pre-emptive treatment. A novel integration platform collected data from the Internet of Medical Things (IoMT) at a dialysis center and inspection results from electronic medical records (EMR) to train ML algorithms and build models. The selection of the feature parameters was implemented using Pearson's correlation method. Then, the eXtreme Gradient Boost (XGBoost) algorithm was chosen to create the predictive models and optimize the feature choice. 75% of collected data are used as a training dataset and the other 25% are used as a testing dataset. We adopted the prediction precision and recall rate of hypotension and AV fistula obstruction to measure the effectiveness of the predictive models. These rates were sufficiently high at approximately 71%-90%. In the context of hemodialysis, hypotension and the deterioration of the quality or obstruction of the arteriovenous (AV) fistula affect treatment quality and patient safety and may lead to a poor prognosis. Our prediction models with high accuracies can provide excellent references and signals for clinical healthcare service providers. Clinical and Translational Impact Statement-With the integrated dataset collected from IoMT and EMR, the superior predictive results of our models for complications of hemodialysis patients are demonstrated. We believe, after enough clinical tests are implemented as planned, these models can assist the healthcare team in making appropriate preparations in advance or adjusting the medical procedures to avoid these adverseevents.

A 67-Year-Old Woman With Fluctuating Hypertension and Hypotension After Elective Surgery

CASE PRESENTATION

A 67-year-old woman with hypertension, type 2 diabetes mellitus, and hypothyroidism presented for an elective blepharoplasty. She underwent monitored anesthesia care with propofol and dexmedetomidine. No inhaled gases or neuromuscular blockade were administered during the procedure.

Hypobaric Unilateral Spinal Anesthesia Versus General Anesthesia for Hip Fracture Surgery in the Elderly: A Randomized Controlled Trial

BACKGROUND

Hypotension during surgery is frequent in the elderly population and is associated with acute kidney and myocardial injury, which are, themselves, associated with increased 30-day mortality. The present study compared the hemodynamic effects of hypobaric unilateral spinal anesthesia (HUSA) to general anesthesia (GA) in patients ≥70 years of age undergoing hip fracture surgery.

METHODS

We conducted a single-center, prospective, randomized study. In the HUSA group, patients were positioned with the operated hip above, and the hypobaric anesthetic solution was composed of 9 mg ropivacaine, 5 µg sufentanil, and 1 mL of sterile water. Anesthesia was adjusted for the GA group. Mean arterial pressure (MAP) was measured with a noninvasive blood pressure upper arm cuff every 3 minutes. Hypotension was treated with a bolus of ephedrine and then a continuous intravenous of norepinephrine to obtain a MAP ≥65 mm Hg. Primary outcome was the occurrence of severe hypotension, defined as a MAP <65 mm Hg for >12 consecutive minutes.

RESULTS

A total of 154 patients were included. Severe hypotension was more frequent in the GA group compared to the HUSA group (odds ratio, 5.6; 95% confidence interval, 2.7-11.7; P < .001). There was no significant difference regarding the short-term outcomes between the HUSA and GA groups: acute kidney injury (respectively, 5.1% vs 11.3%; P = .22), myocardial injury (18.0% vs 14.0%; P = .63), and 30-day mortality (2.4% vs 4.7%; P = .65).

CONCLUSIONS

HUSA leads to fewer episodes of severe intraoperative hypotension compared to GA in an elderly population undergoing hip fracture surgery.

Ketamine is not associated with more post-intubation hypotension than etomidate in patients undergoing endotracheal intubation

INTRODUCTION

Emergency department (ED) patients undergoing emergent tracheal intubation often have multiple physiologic derangements putting them at risk for post-intubation hypotension. Prior work has shown that post-intubation hypotension is independently associated with increased morbidity and mortality. The choice of induction agent may be associated with post-intubation hypotension. Etomidate and ketamine are two of the most commonly used agents in the ED, however, there is controversy regarding whether either agent is superior in the setting of hemodynamic instability. The goal of this study is to determine whether there is a difference in the rate of post-intubation hypotension who received either ketamine or etomidate for induction. Additionally, we provide a subgroup analysis of patients at pre-existing risk of cardiovascular collapse (identified by pre-intubation shock index (SI) > 0.9) to determine if differences in rates of post-intubation hypotension exist as a function of sedative choice administered during tracheal intubation in these high-risk patients. We hypothesize that there is no difference in the incidence of post-intubation hypotension in patients who receive ketamine versus etomidate.

METHODS

A retrospective cohort study was conducted on a database of 469 patients having undergone emergent intubation with either etomidate or ketamine induction at a large academic health system. Patients were identified by automatic query of the electronic health records from 1/1/2016-6/30/2019. Exclusion criteria were patients <18-years-old, tracheal intubation performed outside of the ED, incomplete peri-intubation vital signs, or cardiac arrest prior to intubation. Patients at high risk for hemodynamic collapse in the post-intubation period were identified by a pre-intubation SI > 0.9. The primary outcome was the incidence of post-intubation hypotension (systolic blood pressure < 90 mmHg or mean arterial pressure < 65 mmHg). Secondary outcomes included post-intubation vasopressor use and mortality. These analyses were performed on the full cohort and an exploratory analysis in patients with SI > 0.9. We also report adjusted odds ratios (aOR) from a multivariable logistic regression model of the entire cohort controlling for plausible confounding variables to determine independent factors associated with post-intubation hypotension.

RESULTS

A total of 358 patients were included (etomidate: 272; ketamine: 86). The mean pre-intubation SI was higher in the group that received ketamine than etomidate, (0.97 vs. 0.83, difference: -0.14 (95%, CI -0.2 to -0.1). The incidence of post-intubation hypotension was greater in the ketamine group prior to SI stratification (difference: -10%, 95% CI -20.9% to -0.1%). Emergency physicians were more likely to use ketamine in patients with SI > 0.9. In our multivariate logistic regression analysis, choice of induction agent was not associated with post-intubation hypotension (aOR 1.45, 95% CI 0.79 to 2.65). We found that pre-intubation shock index was the strongest predictor of post-intubation hypotension.

CONCLUSION

In our cohort of patients undergoing emergent tracheal intubation, ketamine was used more often for patients with an elevated shock index. We did not identify an association between the incidence of post-intubation hypotension and induction agent between ketamine and etomidate. Patients with an elevated shock index were at higher risk of cardiovascular collapse regardless of the choice of ketamine or etomidate.

Predicting intraoperative hypotension using deep learning with waveforms of arterial blood pressure, electroencephalogram, and electrocardiogram: Retrospective study

To develop deep learning models for predicting Interoperative hypotension (IOH) using waveforms from arterial blood pressure (ABP), electrocardiogram (ECG), and electroencephalogram (EEG), and to determine whether combination ABP with EEG or CG improves model performance. Data were retrieved from VitalDB, a public data repository of vital signs taken during surgeries in 10 operating rooms at Seoul National University Hospital from January 6, 2005, to March 1, 2014. Retrospective data from 14,140 adult patients undergoing non-cardiac surgery with general anaesthesia were used. The predictive performances of models trained with different combinations of waveforms were evaluated and compared at time points at 3, 5, 10, 15 minutes before the event. The performance was calculated by area under the receiver operating characteristic (AUROC), area under the precision-recall curve (AUPRC), sensitivity and specificity. The model performance was better in the model using both ABP and EEG waveforms than in all other models at all time points (3, 5, 10, and 15 minutes before an event) Using high-fidelity ABP and EEG waveforms, the model predicted IOH with a AUROC and AUPRC of 0.935 [0.932 to 0.938] and 0.882 [0.876 to 0.887] at 5 minutes before an IOH event. The output of both ABP and EEG was more calibrated than that using other combinations or ABP alone. The results demonstrate that a predictive deep neural network can be trained using ABP, ECG, and EEG waveforms, and the combination of ABP and EEG improves model performance and calibration.

Predicting Hypertensive Events with Time-Series Analysis of Mean Arterial Pressure

We investigated whether a statistical model used previously to predict hypotension from mean arterial pressure (MAP) time series analysis could predict hypertension. We performed a retrospective analysis of minute-by-minute MAP records from two cohorts of intensive care unit (ICU) patients. The first cohort was comprised of surgical and medical ICUs while the second cohort was comprised of acute spinal cord injury (ASCI) patients in a neurological ICU. At each time point with physiological MAP, time series analysis was used to predict the median MAP for the subsequent 20 min. This method was used to predict hypertensive episodes, i.e., intervals of 20 or more minutes where at least half of the MAP measurements were > 105 mmHg. Advance prediction of hypertensive episodes was similar in the two cohorts (69.15% vs. 82.61%, respectively), as was positive predictive value of the hypertension predictions (67.42% vs. 71.57%). The results suggest that the methodology may be useable for predicting hypertension from time-series analysis of MAP. Patients requiring continuous vasopressor infusion are at risk of hypertension and excessive vasoconstriction. We found evidence that time-series analysis previously validated for predicting hypotension may also be usable for predicting hypertension.