Predictors of mortality in adults with Sickle cell disease admitted to intensive care unit in Bahrain

Predictors of Intensive Care Admission Among Adult Patients with Sickle Cell Disease in Eastern Province of Saudi Arabia

Purpose

Sickle cell disease (SCD) comprises a complex group of hematologic disorders that are collectively the most common monogenic disorder and are associated with increased risk of intensive care unit admission (ICU). The purpose of this study is to investigate factors that predict admission of adult patients with SCD to the ICU.

Patients and Methods

This was a cross-sectional study that enrolled adult patients with SCD from Saudi Arabia.

Results

A total of 107 patients with SCD, with a median age 31.9±12.1 years, were evaluated retrospectively. Regarding predictors of ICU admission, patients who indicated a history of blood transfusions were at 8.047-fold higher risk of ICU admission (OR=8.047; 95% CI=2.392-27.07; p=0.001). Patients who started hydroxyurea were at least 3.071 times more likely to be admitted than those who did not (OR=3.071; 95% CI=1.164-8.104; p=0.023). We also observed three or more hospitalizations per year to be associated with increased risk of ICU admission (OR=3.393; 95% CI=1.285-8.960; p=0.014), with those making 3 to 5 visits annually having at least 10.4 times higher risk (OR=10.38; 95% CI=10.098-98.19; p=0.041) and those with 6 to 10 ER admissions having 18 times higher risk (OR=18.00; 95% CI=2.149-150.8; p=0.008). Finally, patients with high WBC were predicted to have at least 3.34 times higher risk of ICU admission (OR=3.337; 95% CI=1.131-9.846; p=0.029).

Conclusion

SCD is a multi-systemic disease associated with increased morbidity and mortality. Recognition of high-risk features in patients helps to eliminate subjectivity in ICU referral decision. Frequent hospitalization and emergency visits, multiple blood transfusions, and elevated white blood cell count were significantly associated with a higher rate of ICU admission despite hydroxyurea usage.

Predictors of Mortality in Adults With Sickle Cell Disease Admitted to the Intensive Care Unit in King Saud Medical City, Saudi Arabia

Background Sickle cell disease (SCD) is the most common genetic blood disorder in Saudi Arabia. A limited number of studies have been conducted on SCD patients regarding their intensive care unit (ICU) admissions. We aimed to identify the cause of ICU admission in SCD patients and to identify predictors of mortality. Methodology We identified 64 patients with SCD, aged 14 years and older, who were admitted to the ICU of King Saud Medical City, Riyadh, Kingdom of Saudi Arabia, from January 1, 2017, to December 31, 2020. Results Acute chest syndrome was the most frequent primary diagnosis for ICU admission in 29 (45.3%) patients followed by vaso-occlusive crisis in 23 (35.9%) patients. Pregnancy in eight (12.5%) patients was the most prevalent co-existing condition. The median age was 29 years, with males comprising 45.3% and females comprising 54.7% of the study population. Arterial blood gas pH less than 7.2 on ICU admission (p= <0.001), hemodialysis support (p= 0.049), the use of vasopressors (p= 0.016), intubation (p= <0.001), and being intubated within the first 24 hours of ICU stay (p= 0.04) had a statistically significant association with mortality at ICU discharge out of all the variables tested. Mortality on ICU discharge was 7 (10.9%). Conclusion This was a retrospective study carried out in King Saud Medical City. Comparing the results of the study to those of similar ones conducted around the world revealed a low SCD ICU mortality rate. This low mortality may be a result of improved overall ICU care. We recommend a multi-center, prospective study in future.

Acute chest syndrome in adult patients with sickle cell disease: The relationship with the time to onset after hospital admission

Data on acute chest syndrome (ACS) in adult sickle cell disease patients are scarce. In this study, we describe 105 consecutive ACS episodes in 81 adult patients during a 32-month period and compare the characteristics as a function of the time to onset after hospital admission for a vaso-occlusive crisis (VOC), that is early-onset episodes (time to onset ≤24 h, 42%) versus secondary episodes (>24 h, 58%; median [interquartile range] time to onset: 2 [2-3] days). The median age was 27 [22-34] years, 89% of the patients had an S/S or S/β⁰ -thalassaemia genotype; 81% of the patients had a history of ACS (median: 3 [2-5] per patient), only 61% were taking a disease-modifying treatment at the time of the ACS. Fever and chest pain were noted in respectively 54% and 73% of the episodes. Crackles (64%) and bronchial breathing (32%) were the main abnormal auscultatory findings. A positive microbiological test was found for 20% of episodes. Fifty percent of the episodes required a blood transfusion; ICU transfer and mortality rates were respectively 29% and 1%. Secondary and early-onset forms of ACS did not differ significantly. Disease-modifying treatments should be revaluated after each ACS episode because the recurrence rate is high.

Phenotypes of sickle cell intensive care admissions: an unsupervised machine learning approach in a single-center retrospective cohort

Sickle cell disease (SCD) is associated with multiple known complications and increased mortality. This study aims to further understand the profile of intensive care unit (ICU) admissions of SCD patients. In this single-center retrospective cohort (approval number 0926-11), we evaluated SCD-related ICU admissions at our hospital in São Paulo, Brazil. Admissions were clustered using clinical data and organ dysfunction at ICU admission. A hierarchical clustering method was used to distinguish phenotypes. From 140 admissions obtained, 125 were included. The mean age was 30 years, 48% were male, and SS genotype was predominant (71.2%). Non-surgical causes of admissions accounted for 85.6% (n = 107). The mean Sequential Organ Failure Assessment score (SOFA) was 4 (IQR 2-7). Vasopressors were required by 12% and mechanical ventilation by 17.6%. After analysis of the average silhouette width, the optimal number of clusters was 3: cluster 1 (n = 69), cluster 2 (n = 25), cluster 3 (n = 31). Cluster 1 had a mean age of 29 years, 87% of SS genotype, and mean SOFA of 4. Cluster 2 had a mean age of 37 years, 80% of SS genotype, and mean SOFA of 8. Cluster 3 had a mean age of 26 years, 29% of SS genotype, and mean SOFA of 3. The need for mechanical ventilation was 11.6%, 44%, and 9.7%, respectively. Mortality was significantly higher in cluster 2 (44%, p = 0.012). This cohort of critical SCD admissions suggested the presence of three different profiles. This can be informative in the ICU setting to identify SCD patients at higher risk of worse outcomes.

Nationwide retrospective study of critically ill adults with sickle cell disease in France

Little is known about patients with sickle cell disease (SCD) who require intensive care unit (ICU) admission. The goals of this study were to assess outcomes in patients admitted to the ICU for acute complications of SCD and to identify factors associated with adverse outcomes. This multicenter retrospective study included consecutive adults with SCD admitted to one of 17 participating ICUs. An adverse outcome was defined as death or a need for life-sustaining therapies (non-invasive or invasive ventilation, vasoactive drugs, renal replacement therapy, and/or extracorporeal membrane oxygenation). Factors associated with adverse outcomes were identified by mixed multivariable logistic regression. We included 488 patients admitted in 2015-2017. The main reasons for ICU admission were acute chest syndrome (47.5%) and severely painful vaso-occlusive event (21.3%). Sixteen (3.3%) patients died in the ICU, mainly of multi-organ failure following a painful vaso-occlusive event or sepsis. An adverse outcome occurred in 81 (16.6%; 95% confidence interval [95% CI], 13.3%-19.9%) patients. Independent factors associated with adverse outcomes were low mean arterial blood pressure (adjusted odds ratio [aOR], 0.98; 95% CI 0.95-0.99; p = 0.027), faster respiratory rate (aOR, 1.09; 95% CI 1.05-1.14; p < 0.0001), higher haemoglobin level (aOR, 1.22; 95% CI 1.01-1.48; p = 0.038), impaired creatinine clearance at ICU admission (aOR, 0.98; 95% CI 0.97-0.98; p < 0.0001), and red blood cell exchange before ICU admission (aOR, 5.16; 95% CI 1.16-22.94; p = 0.031). Patients with SCD have a substantial risk of adverse outcomes if they require ICU admission. Early ICU admission should be encouraged in patients who develop abnormal physiological parameters.

Is sickle cell disease a risk factor for severe COVID-19 outcomes in hospitalized patients? A multicenter national retrospective cohort study

Introduction

Studies that examine the association between sickle cell disease (SCD) and COVID-19 outcomes are lacking. This study aims to determine whether SCD is a risk factor for severe COVID-19 infection in regard to the requirement of noninvasive ventilation/high flow nasal cannula (NIV/HFNC), mechanical ventilation (MV), or death in hospitalized patients.

Methods

Retrospective cohort study included COVID-19 patients admitted to four COVID-19 treatment facilities in Bahrain between February 24, 2020 and July 31, 2020. All SCD patients with COVID-19 were included and compared to a randomly selected sample of non-SCD patients with COVID-19. Data were collected from the medical records. Multivariate logistic regression models were used to control for confounders and estimate the effect of SCD on the outcomes.

Results

1792 patients with COVID-19 were included; 38 of whom were diagnosed with SCD as well. In the SCD group, one (2.6%) patient required NIV/HFNC, one (2.6%) required MV, and one (2.6%) death occurred. In comparison, 56 (3.2%) of the non-SCD patients required NIV/HFNC, 47 (2.7%) required MV, and death occurred in 58 (3.3%) patients. Upon adjusting for confounders, SCD had an odds ratio of 1.847 (95% CI: 0.39-8.83; p = 0.442).

Conclusion

Our results indicate that SCD is not a risk factor for worse COVID-19 outcomes in hospitalized patients.

Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study

Background

Sickle cell disease (SCD) is a genetic disorder of the red blood cells, resulting in multiple acute and chronic complications, including pain episodes, stroke, and kidney disease. Patients with SCD develop chronic organ dysfunction, which may progress to organ failure during disease exacerbations. Early detection of acute physiological deterioration leading to organ failure is not always attainable. Machine learning techniques that allow for prediction of organ failure may enable early identification and treatment and potentially reduce mortality.

Objective

The aim of this study was to test the hypothesis that machine learning physiomarkers can predict the development of organ dysfunction in a sample of adult patients with SCD admitted to intensive care units (ICUs).

Methods

We applied diverse machine learning methods, statistical methods, and data visualization techniques to develop classification models to distinguish SCD from controls.

Results

We studied 63 sequential SCD patients admitted to ICUs with 163 patient encounters (mean age 30.7 years, SD 9.8 years). A subset of these patient encounters, 22.7% (37/163), met the sequential organ failure assessment criteria. The other 126 SCD patient encounters served as controls. A set of signal processing features (such as fast Fourier transform, energy, and continuous wavelet transform) derived from heart rate, blood pressure, and respiratory rate was identified to distinguish patients with SCD who developed acute physiological deterioration leading to organ failure from patients with SCD who did not meet the criteria. A multilayer perceptron model accurately predicted organ failure up to 6 hours before onset, with an average sensitivity and specificity of 96% and 98%, respectively.

Conclusions

This retrospective study demonstrated the viability of using machine learning to predict acute organ failure among hospitalized adults with SCD. The discovery of salient physiomarkers through machine learning techniques has the potential to further accelerate the development and implementation of innovative care delivery protocols and strategies for medically vulnerable patients.

Care of the Critically Ill Pediatric Sickle Cell Patient

Sickle cell disease is the most common inherited disease in the United States. Through the effects of hemolysis and vaso-occlusion, it has the potential to incite critical illness involving multiple organ systems. Children with sickle cell disease are at risk of multiple types of shock resulting in a need for ICU care. Our youngest patients with sickle cell disease are at highest risk of infection due to lack of splenic function, and this can present with septic shock. Hypovolemic shock can occur secondary to severe acute anemia as seen with splenic sequestration or a delayed transfusion reaction. As one ages, the risk of cardiac dysfunction – diastolic and systolic dysfunction as well as pulmonary hypertension – can result in cardiogenic shock. In addition to shock, patients with sickle cell disease are at risk for respiratory failure from acute chest syndrome as well as acute neurologic deterioration from stroke. For these reasons, critical care physicians must be familiar with the unique management of sickle cell complications in order to provide the best possible care for this vulnerable population.