Keywords
RDW, Pediatric Intensive Care, Critically Ill Children, Outcome Predictors, Tertiary Care Hospital, Central India
This article is included in the Datta Meghe Institute of Higher Education and Research collection.
Critically ill pediatric patients often present with a broad spectrum of conditions, and early prognostic markers are essential for guiding clinical decisions. Red Cell Distribution Width (RDW), a measure of the variability in red blood cell size, has been associated with various health conditions.
The study will be conducted over two years at a tertiary care hospital in Central India. Critically ill children between the ages of 1 month and 18 years admitted to the PICU will be consecutively enrolled after obtaining informed consent. Demographic data, vital signs, diagnoses, laboratory results, and relevant scores (PELOD-2 and SOFA) will be recorded. Outcome variables will be documented, including ICU stay duration, mechanical ventilation days, ionotrope usage, development of Acute Kidney Injury (AKI), renal replacement therapy, and outcome (death or discharge). Statistical analysis will involve t-tests, chi-square tests, ROC curve analysis, sensitivity, specificity, positive predictive value, and negative predictive value calculations.
The study aims to provide insights into the potential of RDW as a predictor of morbidity and mortality in critically ill pediatric patients. Comparison with established scoring systems will contribute to understanding the practical significance of RDW in clinical decision-making.
RDW, Pediatric Intensive Care, Critically Ill Children, Outcome Predictors, Tertiary Care Hospital, Central India
Critically ill children admitted to the Pediatric Intensive Care Unit (PICU) represent a diverse and vulnerable patient population, spanning a broad spectrum of medical conditions and clinical severity.1 Predicting the course and outcomes of these patients early in their PICU stay is paramount for clinical decision-making, resource allocation, and improved patient care.2
Red Cell Distribution Width (RDW), a routine hematological parameter that reflects the variability in red blood cell size, has recently gained attention as a potential prognostic marker in various clinical settings.3 While RDW is traditionally used to assess anemia, emerging evidence suggests its broader utility in predicting morbidity and mortality in critically ill adults. However, its applicability in the pediatric population, especially in the context of the PICU, still needs to be explored.4
Considering this knowledge gap, this study protocol outlines a prospective observational study designed to investigate the role of RDW as a predictor of outcomes in critically ill children admitted to a tertiary care hospital in Central India. By assessing RDW’s association with morbidity and mortality in this specific patient cohort, we aim to provide valuable insights into its potential as a prognostic tool.
Moreover, this study compares RDW with well-established scoring systems, such as the Pediatric Logistic Organ Dysfunction 2 (PELOD-2) and Sequential Organ Failure Assessment (SOFA) scores, to evaluate its clinical significance. Such a comparative analysis can help clarify RDW’s place in clinical decision-making. The findings of this study are expected to have important implications for PICU healthcare providers, as a reliable prognostic marker could enhance the early identification of patients at higher risk and guide therapeutic interventions. Ultimately, this research aims to contribute to improved patient care and outcomes in the challenging environment of the PICU.
To investigate the utility of Red Cell Distribution Width (RDW) as a predictive marker for the outcome of critically ill children admitted to the Pediatric Intensive Care Unit (PICU).
1. To evaluate RDW as a predictor of morbidity in critically ill children.
2. To assess RDW as a predictor of mortality in critically ill children.
3. To compare the predictive value of RDW with Pediatric Sequential Organ Failure Assessment (pSOFA) and Pediatric Logistic Organ Dysfunction 2 (PELOD2) scores in predicting the outcome of patients in the PICU.
Critically ill children between the ages of 1 month and 18 years were admitted to the Pediatric Intensive Care Unit (PICU) of Acharya Vinoba Bhave Rural Hospital (AVBRH) in Central India set 2023-2024.
The study will be conducted in the Pediatric Intensive Care Unit (PICU) of the Department of Pediatrics at Acharya Vinoba Bhave Rural Hospital (AVBRH), a 1525-bedded tertiary care hospital located in Sawangi (Meghe), Wardha, Maharashtra, Central India.
1. Selection bias: There will be a potential for selection bias in the study, as only critically ill children admitted to the Pediatric Intensive Care Unit (PICU) will be included. This may not represent the entire spectrum of pediatric patients, leading to a bias toward more severe cases.
2. Sampling bias: The study will use consecutive sampling, which may introduce bias if certain patients are systematically excluded or underrepresented during specific periods.
3. Information bias: Information bias could occur due to variations in data collection methods and interpretations of laboratory results, especially when multiple individuals are involved in data collection and recording.
1. Eligibility criteria: Patients who satisfy the predefined inclusion criteria, which include critically ill children aged between 1 month to 18 years and having Pediatric Intensive Care Unit (PICU) stays exceeding 24 hours, are eligible for enrollment in the study. This criterion-based approach is fundamental for maintaining the study’s relevance and applicability to the target population.
2. Informed consent: Enrollment into the study occurs only after obtaining written informed consent from the patient (if of an appropriate age and capacity) or from their legal guardians. This practice is essential for ensuring the ethical conduct of the research, respecting patient autonomy, and upholding the principles of informed and voluntary participation in medical research.
3. Consecutive sampling: To minimize the potential for selection bias and enhance the representativeness of the study population, consecutive sampling is employed. This systematic approach ensures that eligible patients are enrolled in the study continuously and unbiasedly throughout the two-year study period.
4. Data collection: Each patient undergoes a comprehensive data collection process once enrolled. This involves gathering detailed information, including demographic data, vital signs, specific diagnoses, results of laboratory tests, and the calculation of scores such as Pediatric Logistic Organ Dysfunction 2 (PELOD-2) and Sequential Organ Failure Assessment (SOFA). The data collected for each patient forms the basis for the subsequent Red Cell Distribution Width (RDW) analysis and its association with various outcome variables.
The data collection process described in the study will be a systematic and methodical approach aimed at gathering critical information from critically ill children who will be admitted to the Pediatric Intensive Care Unit (PICU) at Acharya Vinoba Bhave Rural Hospital (AVBRH) in Central India.
Upon a patient’s admission to the PICU, a structured process will be initiated to ensure consistent data collection. Patients who will meet the inclusion criteria, including those aged between 1 month and 18 years and expected to stay in the PICU for more than 24 hours, will be enrolled in the study after obtaining informed consent, either from the patient (if of an appropriate age) or their legal guardians.
The data collection process will encompass several key aspects:
1. Demographic data: Detailed demographic information, including age, gender, and weight, will be meticulously recorded for each enrolled patient. This information will be fundamental for characterizing the study population and analyzing how RDW may relate to patient profiles.
2. Clinical assessment: Vital signs, such as heart rate, blood pressure, respiratory rate, and temperature, will be carefully monitored and documented. This clinical assessment will aid in understanding the patients’ overall health status upon admission to the PICU.
3. Diagnosis: The specific diagnosis or reason for admission to the PICU will be noted. This information will help categorize and analyze patient populations with different underlying conditions, which may affect the study’s outcomes.
4. Laboratory investigations: A comprehensive set of laboratory tests will be conducted, including a complete blood count, Red Cell Distribution Width (RDW), Kidney Function Test (KFT), Liver Function Test (LFT), C-reactive protein (CRP), and blood culture. These tests will provide valuable insights into the patients’ hematological and organ function status, as well as the presence of any infectious agents.
5. Additional investigations: Supplementary investigations, such as serum lactate and 2D echocardiography, will be performed when necessary to collect further clinical data relevant to the patient’s condition.
6. Scoring systems: The Pediatric Logistic Organ Dysfunction 2 (PELOD-2)5 and Sequential Organ Failure Assessment (SOFA)6 scores will be calculated within 24 hours of PICU admission. These scoring systems will be instrumental in assessing organ dysfunction’s severity and disease progression.
7. Outcome variables: Crucial outcome variables, including the length of ICU stay, the number of days of mechanical ventilation, ionotrope usage, the development of Acute Kidney Injury (AKI), the need for renal replacement therapy, and the outcome (death or discharge), will be meticulously documented.
The study protocol specifies a sample size of 129. This means that the study aims to include 129 critically ill children meeting the inclusion criteria (aged between 1 month to 18 years and with PICU stays exceeding 24 hours). This sample size has been determined to provide sufficient statistical power to assess the relationship between Red Cell Distribution Width (RDW) and the outcomes of interest in critically ill children in the Pediatric Intensive Care Unit (PICU) at Acharya Vinoba Bhave Rural Hospital (AVBRH) in Central India.
1. Morbidity: This refers to being diseased or unhealthy. In the context of the study, researchers are interested in understanding how RDW is related to the morbidity or disease severity of critically ill children in the Pediatric Intensive Care Unit (PICU).
2. Mortality: In this context, mortality refers to death among critically ill children during their PICU stay. Researchers aim to investigate whether RDW can serve as a predictor of mortality in this population.
3. Length of ICU stay: This outcome variable measures each patient’s duration in the Pediatric Intensive Care Unit. Researchers seek to determine whether RDW is associated with longer or shorter ICU stays.
4. Mechanical ventilation days: This outcome assesses the number of days a patient requires mechanical ventilation during their stay in the PICU. Researchers aim to examine whether RDW is linked to a greater need for mechanical ventilation.
5. Ionotrope usage: Ionotropes are medications that support the heart’s function. Researchers will explore the relationship between RDW and the usage of ionotropes in critically ill children.
6. Acute Kidney Injury (AKI): This outcome focuses on developing acute kidney injury during the PICU stay. Researchers intend to investigate whether RDW is associated with a higher likelihood of AKI.
7. Renal Replacement Therapy: Researchers will assess if RDW is linked to the need for renal replacement therapy, a medical procedure to support kidney function in cases of severe renal dysfunction.
8. Outcome (Death or Discharge): This outcome variable categorizes patients into two groups: those who either succumb to their illness and pass away during their PICU stay or those who recover and are discharged. The study aims to determine if RDW can predict these outcomes.
The study protocol delineates the application of specific statistical methods that will be used to analyze the collected data. These methods are pivotal in unraveling the relationships between Red Cell Distribution Width (RDW) and the various outcome variables of interest; for quantitative variables such as age, weight, and laboratory values, unpaired t-tests or Mann-Whitney tests will be employed to compare and identify statistically significant differences among groups. For qualitative variables, including gender and specific diagnostic categories, statistical tests like Chi-square or Fisher’s exact tests will evaluate proportions and assess associations in categorical data. To evaluate the diagnostic accuracy of RDW as a predictor of outcomes, the study will employ the Receiver Operating Characteristic (ROC) curve analysis. This will determine the optimal cut-off value for RDW, balancing sensitivity and specificity, and calculate the area under the curve (AUC) to gauge RDW’s overall performance as a diagnostic marker. Additionally, confidence intervals will provide insight into the range of likely values, while sensitivity, specificity, positive predictive value, and negative predictive value will gauge the diagnostic capability of RDW. A significance level of p < 0.05 will be considered statistically significant in assessing the relationships between RDW and various outcomes by using R studio version 9.1.
The Institutional Ethics Committee of Datta Meghe Institute of Higher Education and Research (DU) has granted its approval to the study protocol (Reference number: DMIHER (DU)/IEC/2022/1076. Date:27-06-2022). Before commencing the study, we will obtain written informed consent from all participants, providing them with a comprehensive explanation of the study’s objectives.
RDW, a measure of the variability in red blood cell size, has garnered growing attention recently as a potential biomarker for various health conditions. Elevated RDW has been associated with inflammation, oxidative stress, and chronic diseases in adult and pediatric populations.7 In critically ill patients, monitoring and predicting outcomes is paramount, and novel biomarkers such as RDW offer a non-invasive and readily available option for assessment.
This study aims to assess whether RDW can predict morbidity and mortality in critically ill children. Morbidity and mortality prediction is a critical aspect of clinical care in the PICU, as early identification of patients at higher risk can lead to tailored interventions and improved outcomes. Several studies have demonstrated the potential of RDW as a prognostic marker for morbidity and mortality in various medical conditions.8 However, its application in the context of critically ill children still needs to be well-established.
In addition to examining RDW’s predictive value, this study will compare it with widely used scoring systems, namely Pediatric Logistic Organ Dysfunction 2 (PELOD-2) and Sequential Organ Failure Assessment (SOFA). These scoring systems assess organ dysfunction and disease severity, and their performance in the PICU setting is well-documented.5,9 A direct comparison with RDW can help elucidate whether this routine hematological parameter offers similar or complementary predictive insights.
RDW may have significant clinical implications if it is a reliable predictor of morbidity and mortality. Physicians can use this readily available parameter to enhance risk stratification and make more informed decisions regarding patient care. Moreover, the comparative analysis with established scoring systems will provide valuable insights into the practical significance of incorporating RDW into clinical practice.
It is essential to acknowledge the limitations of this study, including its single-center design and the specific population of critically ill children. Furthermore, the study will not explore the underlying mechanisms connecting RDW to outcomes, which remain subjects for future investigation.
Views | Downloads | |
---|---|---|
F1000Research | - | - |
PubMed Central
Data from PMC are received and updated monthly.
|
- | - |
Is the rationale for, and objectives of, the study clearly described?
Yes
Is the study design appropriate for the research question?
Partly
Are sufficient details of the methods provided to allow replication by others?
No
Are the datasets clearly presented in a useable and accessible format?
No
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Pediatric Endocrinology, intensive care
Is the rationale for, and objectives of, the study clearly described?
Yes
Is the study design appropriate for the research question?
Yes
Are sufficient details of the methods provided to allow replication by others?
Yes
Are the datasets clearly presented in a useable and accessible format?
Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: anaesthesiology and intensive care
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | ||
---|---|---|
1 | 2 | |
Version 1 11 Mar 24 |
read | read |
Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list:
Sign up for content alerts and receive a weekly or monthly email with all newly published articles
Already registered? Sign in
The email address should be the one you originally registered with F1000.
You registered with F1000 via Google, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Google account password, please click here.
You registered with F1000 via Facebook, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Facebook account password, please click here.
If your email address is registered with us, we will email you instructions to reset your password.
If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance.
Comments on this article Comments (0)