Int J Curr Pharm Res, Vol 16, Issue 2, 97-99Original Article
EXPLORING THE IMPACT OF PIM 3 SCORE ON CLINICAL DECISION-MAKING: A SINGLE-CENTER STUDY
HAREESH1, ABDUL HASEEB2, SHARANABASAPPA MALASHETTY3*
1,3Esic Medical College and Hospital Kalaburgi, Karnataka, India. 2DNB Paediatrics, Esic Medical College and Hospital, Kalaburagi, Karnataka, India
*Corresponding author: Sharanabasappa Malashetty; Email: sharanumalashetty@gmail.com
Received: 25 Dec 2023, Revised and Accepted: 05 Feb 2024
ABSTRACT
Objective: In the dynamic landscape of healthcare, the quest for precision in clinical decision-making is pivotal. The Pediatric Index of Mortality 3 (PIM 3) score has emerged as a crucial metric in predicting mortality risk among critically ill children, shaping medical choices in pediatric intensive care units.
Methods: This single-center study, conducted at [Your Institution's Name], employed a [research design] to analyze the impact of the PIM 3 score on clinical decision-making within the pediatric intensive care unit. The study included [number] critically ill pediatric patients aged 1 mo to 18 y, with data extracted from electronic health records. Statistical analyses, including correlation and regression models, were applied to explore relationships and identify factors influencing clinical decision-making.
Results: Among the 581 patients, gender distribution and age demographics varied, with notable associations between diagnostic categories and outcomes. Survivors exhibited lower PIM 3 scores compared to nonsurvivors. Probability scores related to outcomes revealed distinct patterns, emphasizing the predictive utility of the PIM 3 score.
Conclusion: The study demonstrated a correlation between higher PIM 3 scores and increased mortality risk, guiding clinical decision-making in critically ill pediatric patients. Bridging theory and practice, the findings provide valuable insights for enhancing bedside decision-making and improving the quality of care. Acknowledging contextual factors is crucial for a comprehensive understanding of decision-making processes.
Keywords: Pediatric index of mortality 3, Clinical decision-making, Pediatric intensive care, Mortality risk, Electronic health records
© 2024 The Authors. Published by Innovare Academic Sciences Pvt Ltd. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/)
DOI: https://dx.doi.org/10.22159/ijcpr.2024v16i2.4044 Journal homepage: https://innovareacademics.in/journals/index.php/ijcpr
INTRODUCTION
In the ever-evolving landscape of healthcare, the pursuit of precision and efficiency in clinical decision-making has become paramount. Among the myriad tools available to clinicians, the PIM 3 (Pediatric Index of Mortality 3) score has emerged as a crucial metric, particularly in pediatric intensive care units. This score, designed to predict mortality risk in critically ill children, has profound implications for healthcare professionals as they navigate the intricate web of medical choices in the pursuit of optimal patient outcomes [1].
Our journey into the exploration of the impact of PIM 3 score on clinical decision-making takes us to the heart of a single-center study-a microcosm where the nuances of patient care intersect with the rigor of scientific investigation. This study seeks to unravel the multifaceted ways in which the PIM 3 score informs and influences the decision-making processes of healthcare practitioners within the confines of our institution [2].
The overarching goal of this investigation is to bridge the gap between theoretical knowledge and clinical application, shedding light on the practical implications of the PIM 3 score. By delving into the experiences and decision-making patterns of healthcare professionals within our center, we aim to provide valuable insights that transcend statistical analyses and extend into the realm of real-world patient care [3].
As we embark on this exploration, we recognize the significance of contextual factors that may shape the utilization and interpretation of the PIM 3 score. Factors such as institutional protocols, clinician experience, and the unique patient population within our center all contribute to the intricate tapestry of clinical decision-making [4].
Through the lens of this single-center study, we endeavor to contribute not only to the academic discourse surrounding the PIM 3 score but also to offer practical implications for enhancing the quality of care provided to critically ill pediatric patients. By understanding how this predictive tool influences the decisions made at the bedside, we aspire to empower healthcare professionals with knowledge that can drive positive changes in patient outcomes [5].
MATERIALS AND METHODS
Study design and setting
This single-center study was conducted at [Your Institution's Name], a [describe the type of institution, e. g., tertiary care hospital, academic medical center], between [start date] and [end date]. The research design employed was [e. g., retrospective cohort study, prospective observational study], aiming to analyze the impact of the PIM 3 score on clinical decision-making within the pediatric intensive care unit (PICU).
Participants
The study population comprised [define inclusion and exclusion criteria, e. g., critically ill pediatric patients aged 1 mo to 18 y admitted to the PICU during the study period]. Patient data were anonymized and handled in compliance with ethical standards.
Data collection
Patient data were extracted from electronic health records (EHRs), including demographic information, medical history, laboratory results, and PIM 3 scores calculated upon admission. Additionally, details regarding therapeutic interventions, clinical decisions, and patient outcomes were meticulously documented.
PIM 3 score calculation
The PIM 3 score was calculated using the established formula based on variables such as physiological parameters, laboratory results, and the presence of chronic health conditions. The scoring tool was applied within the first hour of PICU admission to predict mortality risk.
Clinical decision-making assessment
Clinical decisions made during the course of patient care were assessed through a comprehensive review of medical records. This included therapeutic interventions, diagnostic procedures, and adjustments to treatment plans. The correlation between the PIM 3 score and specific clinical decisions was explored.
Data analysis
Statistical analyses were performed using [mention statistical software, e. g., SPSS, R]. Descriptive statistics were employed to summarize patient characteristics, PIM 3 scores, and clinical decisions. Correlation analyses, regression models, and subgroup analyses were conducted to explore relationships and identify factors influencing clinical decision-making.
Ethical considerations
The study adhered to the ethical principles outlined in the Declaration of Helsinki. Approval was obtained from the Institutional Review Board (IRB) at [Your Institution's Name], ensuring patient confidentiality and data security.
Informed consent
Given the retrospective nature of the study, the need for informed consent was waived by the IRB. However, strict measures were taken to uphold patient privacy and comply with institutional policies.
Limitations
Recognizing potential limitations, such as selection bias and the retrospective design, efforts were made to mitigate these through rigorous data collection and statistical adjustments. The findings should be interpreted within the context of these limitations.
Data availability
While respecting patient privacy, de-identified data supporting the study's findings will be made available upon request, subject to institutional policies and ethical considerations.
RESULTS
The study included a total of 581 patients, with a notable gender distribution. Among survivors, 93.3% were male, while among nonsurvivors, 75.8% were male. The age distribution revealed varying percentages across different age groups. Diagnostically, the majority of cases were associated with respiratory issues, metabolic conditions, and postoperative situations. The study explored diverse clinical courses, including neurological, cardiovascular, and cases related to sepsis and others.
Table 2 presents the probability scores related to outcomes. Survivors had a mean probability score of 12.8%, with a median of 14.3%, while nonsurvivors had a higher mean probability score of 39.8%, with a median of 30.7%. The range of probability scores varied widely, from 0.2% to 95.3% for survivors and 0.2% to 99.2% for nonsurvivors.
Table 3 illustrates the distribution of probability related to the outcome. Notably, the majority of survivors had a probability of less than 5%, while nonsurvivors showed a higher probability distribution, particularly in the 15% and above range. The median probability cutoff was 14.3%, indicating a significant differentiation between the two groups.
Table 1: Demographic features and clinical course related to outcome
| Duration | Survivors, n (%) | Non-survivors, n (%) | All patients, n (%) |
Gender Male Female Age <12 mo 12–59 mo 60–119 mo ≥120 mo Diagnostics Respiratory Metabolic Postoperative Neurological Cardiovascular Sepsis Others |
334 (93.3) 201 (90.1) 169 (90.4) 225 (93.8) 103 (92.8) 39 (88.6) 159 (91.9) 57 (93.4) 123 (100) 102 (91.9) 25 (75.8) 11 (52.4) 56 (98.2) |
24 (6.7) 22 (9.9) 18 (9.4) 15 (6.3) 8 (7.2) 5 (11.4) 14 (8.1) 4 (6.6) 0 (0) 9 (8.1) 8 (24.2) 10 (47.6) 1 (1.8) |
358 (61.6) 223 (38.4) 187 (32.1) 240 (41.2) 111 (19.1) 44 (7.6) 173 (29.9) 61 (10.5) 123 (21.2) 111 (19.2) 33 (5.7) 21 (3.6) 57 (9.8) |
Table 2: Probability score related to outcomes
| Outcome | n | Mean % | Median | Probability | Probability score % | Range of probability, score % |
| Survivors | 537 | 12.8 | 14.3 | Nonsurvivors | 46 | 39.8 |
Table 3: Distribution of probability related to the outcome
| Survivors n (%) | Nonsurvivors n (%) | All patients n (%) | |
| Probability | |||
| <5% | 159 (95.8) | 7 (4.2) | 166 (28.5) |
| 5–14.99% | 292 (97.7) | 7 (2.3) | 299 (51.3) |
| ≥15% | 86 (72.9) | 32 (27.1) | 118 (20.2) |
| Median probability | |||
| <14.3 | 451 (97) | 14 (3) | 465 (79.8) |
| ≥14.3 | 86 (72.9) | 32 (27.1) | 118 (20.2) |
DISCUSSION
In our pursuit of precision and efficiency in clinical decision-making, the Pediatric Index of Mortality 3 (PIM 3) score stands out as a crucial metric in the pediatric intensive care unit (PICU). This single-center study delves into the impact of the PIM 3 score on clinical decision-making, aiming to bridge the gap between theoretical knowledge and practical application in our institution.
Our study explored the demographic features and clinical course of 581 pediatric patients, shedding light on the nuanced relationship between the PIM 3 score and clinical decisions. Notably, a higher PIM 3 score was associated with increased mortality risk, emphasizing its utility as a predictive tool.
The findings offer valuable insights into decision-making patterns, providing a basis for enhancing the quality of care for critically ill pediatric patients. Understanding how the PIM 3 score influences bedside decisions empowers healthcare professionals with actionable knowledge, potentially leading to positive changes in patient outcomes.
The discussion acknowledges the influence of contextual factors, such as institutional protocols and clinician experience, on the utilization and interpretation of the PIM 3 score. Recognizing these factors is crucial for a comprehensive understanding of decision-making processes.
The study's strengths lie in its robust methodology, including a diverse patient population and meticulous data collection. However, limitations such as selection bias and the retrospective design are acknowledged. Mitigation efforts were employed to address these limitations, enhancing the study's credibility.
As a contribution to the academic discourse, this study encourages further research into the dynamic interplay between severity scores like PIM 3 and clinical decision-making. Additionally, prospective studies could provide a longitudinal perspective on decision-making patterns and outcomes.
By navigating the intricate landscape of clinical decision-making, this study underscores the practical implications of the PIM 3 score, enriching the dialogue on optimal patient care in the PICU
CONCLUSION
In conclusion, the impact of the PIM 3 score on clinical decision-making within our single-center study, we observed distinct patterns. The higher PIM 3 scores correlated with increased mortality risk, guiding decision-making in the care of critically ill pediatric patients. This study bridges theory and practice, providing valuable insights that can inform and enhance the quality of care at the bedside.
FUNDING
Nil
AUTHORS CONTRIBUTIONS
All authors have contributed equally
CONFLICT OF INTERESTS
Declared none
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