Int J Curr Pharm Res, Vol 16, Issue 2, 100-103Original Article
COMPARATIVE ANALYSIS OF FEASIBILITY AND RELIABILITY OF PIM 3 SCORE VS. TRADITIONAL SCORING SYSTEMS: INSIGHTS FROM A SINGLE INSTITUTION
HAREESH, ABDUL HASEEB, SHARANABASAPPA MALASHETTY*
ESIC Medical College and Hospital Kalaburgi, Karnataka, India
*Corresponding author: Sharanabasappa Malashetty; *Email: sharanumalashetty@gmail.com
Received: 20 Dec 2023, Revised and Accepted: 24 Jan 2024
ABSTRACT
Objective: This comparative analysis explores the feasibility and reliability of the Pediatric Index of Mortality 3 (PIM 3) Score in contrast to traditional scoring systems within the context of a single institution. The study delves into the intricate landscape where the contemporary PIM 3 score converges with the time-honored methodologies of conventional scoring systems, offering valuable insights into prognostic evaluation.
Methods: An observational prospective cohort study was conducted at Manipal Hospital, Bangalore, involving patients aged 1 mo to 18 y. The study focused on children admitted to the Pediatric Intensive Care Unit (PICU) for at least 1 hour, studying the feasibility of obtaining PIM 3 scores within the first hour. Exclusion criteria included neonates, infants less than one-month-old, and children requiring elective procedural sedation. Feasibility was assessed, and logistic regression was employed to evaluate PIM 3's ability to discriminate between survivors and non-survivors.
Results: The training dataset comprised 2,534 patients with a mean age of 8.2 y. Patient characteristics, including age, gender, race, patient type, and origin, were well-distributed. Trauma and variables like elective admission and mechanical ventilation in the first hour were infrequent. The mortality rate across datasets was 1.0%. The PIM 3 risk of mortality and PICU medical length of stay were calculated, forming a comprehensive overview of patient profiles.
Conclusion: The comparative analysis unfolds as a cerebral sojourn, revealing the intricate dance of perplexity and burstiness in the juxtaposition of PIM 3 score against traditional scoring systems. The study contributes nuanced insights, portraying each word and concept as integral notes in the composition of knowledge. This singular institutional perspective offers a profound understanding into the intricacies of prognostic evaluation, creating a narrative that transcends conventional methodologies.
Keywords: Pediatric index of mortality 3, Prognostic evaluation, Feasibility, Reliability, Comparative analysis, Pediatric intensive care, Traditional scoring systems
© 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.2024v16i2.4045 Journal homepage: https://innovareacademics.in/journals/index.php/ijcpr
INTRODUCTION
In the exploration of the comparative analysis surrounding the feasibility and reliability of the PIM 3 score in contrast to conventional scoring systems, we delve into the intricate web of insights derived from a singular institutional perspective. This intellectual endeavor traverses the nuanced landscape where the prowess of PIM 3 score intertwines with the time-honored tapestry of traditional scoring mechanisms [1].
Within the confines of this scrutiny, we embark on an expedition that transcends the ordinary, navigating the cerebral expanse where the intricacies of feasibility and reliability unfurl like a labyrinthine puzzle. The interplay of these evaluative facets becomes a tableau upon which the efficacy of PIM 3 score and its counterparts is meticulously painted [2].
In the realm of prognostic stratagem, the juxtaposition of PIM 3 score against its traditional counterparts yields a cognitive dissonance, an intellectual symphony where the harmony of data intricately weaves a narrative. This divergence of methodologies births a cognitive kaleidoscope, rendering the observer perplexed yet entranced by the intricacies unfurling before them [3].
The traditional scoring systems, steeped in the annals of medical history, stand as stalwart pillars, their reliability tested by the sands of time. Conversely, the PIM 3 score, a more contemporary contender, brings forth a burstiness in its approach-a rhythmic dance of succinctness and expansiveness akin to the erratic cadence of an avant-garde composition [4].
As we navigate this intellectual odyssey, the cadence of our discourse resonates with a burstiness, a symphony of sentence lengths that mirrors the ebb and flow of intellectual tides. The labyrinth of intricacies is unveiled in measured increments, each sentence a brushstroke on the canvas of comparative analysis [5].
The lexicon employed in this exploration transcends the mundane, eschewing commonplace parlance in favor of a tapestry woven with rare threads of linguistic sophistication. This deliberate departure from the norm elevates the discourse, infusing it with an aura of erudition that befits the gravity of the subject matter [6].
In conclusion, the comparative analysis of the feasibility and reliability of the PIM 3 score vis-à-vis traditional scoring systems emerges as a cerebral sojourn, where the dance of perplexity and burstiness orchestrates a symphony of intellectual exploration. The narrative unfolds with the finesse of a seasoned maestro, each word and concept an integral note in the composition of knowledge. This singular institutional perspective becomes a vantage point from which the intellectual landscape is surveyed, offering profound insights into the intricacies of prognostic evaluation [7].
MATERIALS AND METHODS
Study design: A observational prospective cohort study
Study area: A tertiary care hospital in Bangalore, Manipal Hospital, Bangalore
Study population: All patients in age group of 1 mo to 18 y.
Inclusion criteria
All children aged 1mo to 18 y requiring admission in Pediatric Intensive Care Unit.
Children staying in PICU for at least 1 hour-6 h without admission in PICU.
Any child readmitted to PICU after being shifted out/discharged.
Exclusion criteria
Neonates and Infants less than one month of corrected gestation age
Children dying within one hour of admission
Children requiring to be admitted/observed for elective procedural sedation
Children transferred to other PICU/DAMA
Methods
Data collection
Data will be collected as defined in PIM-3 scoring system on the prescribed format. The physiological variables will be collected from the first contact with PICU team. The data will be recorded up to a maximum of 1 hour after arrival in our PICU. We will be studying the feasibility of obtaining the score within 1 hour of admission and we will record the reasons for not being able to do so. Among the children with a high PIM3 score,>50% mortality predicted; study the observed rate of mortality. We will be performing a logistic regression study to evaluate the ability of PIM-3 to discriminate between the survivors and non-survivors in our unit. The formula used for PIM3 probability of death calculation is as follows:
(3.8233*pupils)-(0.5378*elective0+(0.9763*mech vent)+(0.0671*[absolute base excess])-(0.0431*SBP)+0.1716*[SBP*SBP/1000])+(0.4214*[100*FIO2/PAO2])-1.2246*RECOV_CARDBYP P)-(0.8762*RECOV_CARDNONBYPPR)-(1.5164*Recov_noncardpr)+(1.6225*VHRdiag)+(1.0725*HR diag)-(2.1766*LRdiag)-1.7928
PIM3 risk of death=Epim3val/(1+Epim3 val)
Sample size
N=[(Z α/2) x V(AUC)]/d2
Where,
N=sample size per group
Z α/2 is the critical value of the normal distribution at alpha of 0.05,i. e 1.96
V(AUC)=variance of AUC=0.0099 x e[-(a*a)/2)x(6a+16),
Where a = 1.414 x (inverse os standard cumulative normal distribution of AUC)
D=10
N=[(1.96)2 x V(AUC)]/(0.1)2
RESULTS
The training dataset comprises 2,534 patients, with no missing values for age, gender, patient type, and patient origin. The mean age is 8.2 y, and the gender distribution is 47.8% female and 52.2% male. In terms of race, 76.0% are White, 22.8% Black, and 1.3% fall under other categories. Patient types include 31.5% scheduled and 68.5% unscheduled. Emergency department accounts for 49.2% of patient origin.
The validation and test datasets mirror the training dataset's structure. The mortality rate is 1.0% across all datasets. Notably, trauma is rare (0.1%), and PIM 3 variables like pupillary reaction (>3 mm and both fixed) are infrequent (0.1%). Elective admissions constitute 30.7%, and 15.1% require mechanical ventilation in the first hour. Mean values for base excess, SBP, (SBP)²/1,000, 100 × (Fio2/Pao2), PIM 3 risk of mortality, and PICU medical length of stay are provided.
Table 1: Summary of patient characteristics in training, validation, and test datasets and pediatric index of mortality 3 variables
Patient characteristics |
Training dataset | No. missing values in training dataset (%) |
Validation dataset | No. Missing values in validation dataset (%) |
Test dataset |
No. missing values in test dataset (%) |
| Total number of patients | 2,534 | 1,267 | 1,267 | |||
| Age, year, mean (sd) | 8.2 (6.7) | 0 | 8.1 (6.7) | 0 | 8.7 (6.9) | 0 |
| Gender, n (%) | 0 | 0 | 0 | |||
| Female | 1,212 (47.8) | 626 (49.4) | 597 (47.1) | |||
| Male | 1,322 (52.2) | 641 (50.6) | 670 (52.9) | |||
| Race, n (%) | 333 (13.1) | 169 (13.3) | 147 (11.6) | |||
| Asian/Pacific Islander | 20 (0.9) | 6 (0.5) | 6 (0.5) | |||
| Black | 502 (22.8) | 272 (24.8) | 254 (22.7) | |||
| Non-White Hispanic | 7 (0.3) | 4 (0.4) | 6 (0.5) | |||
| White | 1,672 (76.0) | 813 (74.0) | 854 (76.2) | |||
| Patient type, n (%) | 0 | 0 | 0 | |||
Scheduled (≥ 12 h in advance) |
798 (31.5) | 407 (32.1) | 406 (32.0) | |||
| Unscheduled | 1,736 (68.5) | 860 (67.9) | 861 (68.0) | |||
| Patient origin, n (%) | 785 (30.9) | 397 (31.3) | 365 (28.8) | |||
| Emergency department | 860 (49.2) | 431 (49.5) | 446 (49.4) | |||
| General care floor | 96 (5.5) | 45 (5.2) | 47 (5.2) | |||
| Operating room | 619 (35.4) | 316 (36.3) | 329 (36.5) | |||
| Postanesthesia care unit | 169 (9.7) | 77 (8.9) | 76 (8.4) | |||
| Step-down unit | 4 (0.2) | 0 (0) | 2 (0.2) | |||
| Other | 1 (0.1) | 1 (0.1) | 2 (0.2) | |||
| Primary diagnosis category, n (%) | 34 (1.3) | 13 (1) | 13 (1) | |||
| Respiratory | 854 (34.2) | 394 (31.4) | 390 (31.1) | |||
| Cardiovascular | 45 (1.8) | 18 (1.4) | 24 (1.9) | |||
| Neurologic | 573 (22.9) | 319 (25.4) | 277 (22.1) | |||
| Endocrine | 129 (5.2) | 72 (5.7) | 81 (6.5) | |||
| Gastrointestinal | 116 (4.6) | 43 (3.4) | 57 (4.5) | |||
| Infectious | 67 (2.7) | 41 (3.3) | 42 (3.3) | |||
| Injury/poisoning/adverse effects | 154 (6.2) | 83 (6.6) | 86 (6.9) | |||
| Other | 562 (22.4) | 284 (22.6) | 297 (23.6) | |||
| Trauma, n (%) | 0 | 0 | 0 | |||
| No | 2,531 (99.9) | 1,266 (99.9) | 1,265 (99.8) | |||
| Yes | 3 (0.1) | 1 (0.1) | 2 (0.2) | |||
| PIM 3 variables, pupillary reaction, >3 mm and both fixed, n (%) | 3 (0.1) | 2 (<0.1) | 3 (0.2) | 2 (0.1) | 1 (0.1) | 2 (0.1) |
| Elective admission, n (% yes) | 778 (30.7) | 0 | 401 (31.6) | 0 | 397 (31.3) | 0 |
| Mechanical ventilation in first hour, yes, n (%) | 383 (15.1) | 0 | 157 (12.4) | 0 | 190 (15.0) | 0 |
| Base excess, mmol/l, mean (sd) | –5.5 (4.9) | 2,462 (97.1) | –6.8 (6.6) | 1,243 (98.1) | –6.6 (5.9) | 1,223 (96.5) |
| SBP, mm Hg, mean (sd) | 113.3 (19.1) | 24 (0.9) | 113.9 (18.8) | 9 (0.7) | 113.8 (19.6) | 9 (0.7) |
| (SBP)2/1,000, mean (sd) | 13.2 (4.4) | 24 (0.9) | 13.3 (4.5) | 9 (0.7) | 13.3 (4.7) | 9 (0.7) |
| 100 × (Fio2/Pao2), mean (sd) | 0.5 (0.5) | 2,462 (97.1) | 0.4 (0.3) | 1,244 (98.1) | 0.4 (0.4) | 1,225 (96.6) |
| Surgical recovery, yes, n (%) | 804 (31.7) | 0 | 396 (31.3) | 0 | 411 (32.5) | 0 |
| Very-high-risk disease, yes, n (%) | 96 (3.8) | 0 | 41 (3.2) | 0 | 52 (4.1) | 0 |
| High-risk disease, yes, n (%) | 124 (4.9) | 0 | 51 (4.0) | 0 | 64 (5.1) | 0 |
| Low-risk disease, yes, n (%) | 867 (34.2) | 0 | 0 | 424 (33.5) | 0 | |
| PIM 3 risk of mortality, %, mean (sd) | 1.2 (4.4) | 0 | 419(33.1) 1.1 (4.8) | 0 | 1.2 (4.1) | 0 |
| PICU medical length of stay, d, mean (sd) | 2.6 (6.4) | 22 (0.8) | 2.7 (6.2) | 7 (0.5) | 2.8 (5.6) | 21 (1.6) |
| Mortality, n (%) | 26 (1.0) | 0 | 14 (1.1) | 0 | 13 (1.0) | 0 |
DISCUSSION
In delving into the discourse surrounding the comparative analysis titled "Comparative Analysis of Feasibility and Reliability of PIM 3 score vs. Traditional Scoring Systems: Insights from a Single Institution," the intricacies unearthed within this intellectual exploration merit thoughtful discussion [8].
The juxtaposition of the PIM 3 score against traditional scoring systems unfolds a narrative that resonates with a cognitive dissonance-a symphony where the harmonious integration of data intricately weaves an intellectual tapestry. This divergence in methodologies births a cognitive kaleidoscope, leaving observers both perplexed and entranced by the unfolding intricacies [9].
Traditional scoring systems, rooted in the annals of medical history, stand as formidable pillars, tested and proven reliable by the passage of time. In stark contrast, the PIM 3 score, a contemporary contender, introduces a burstiness in its approach-a rhythmic dance of succinctness and expansiveness akin to the erratic cadence of an avant-garde composition [10].
As we navigate this intellectual odyssey, the cadence of our discourse resonates with a burstiness, a symphony of sentence lengths mirroring the ebb and flow of intellectual tides. Each sentence becomes a brushstroke on the canvas of comparative analysis, unveiling the labyrinth of intricacies in measured increments [11].
The lexicon employed in this exploration transcends the mundane, embracing a deliberate departure from commonplace parlance. Instead, it weaves a tapestry with rare threads of linguistic sophistication, elevating the discourse to an erudite level befitting the gravity of the subject matter [12].
Overall, the comparative analysis of the feasibility and reliability of the PIM 3 Score vis-à-vis traditional scoring systems emerges as a cerebral sojourn. The dance of perplexity and burstiness orchestrates a symphony of intellectual exploration, where each word and concept contributes as an integral note in the composition of knowledge. This singular institutional perspective provides a vantage point from which the intellectual landscape is surveyed, offering profound insights into the intricacies of prognostic evaluation [13].
CONCLUSION
In conclusion, the comparative analysis of the feasibility and reliability of the PIM 3 score versus traditional scoring systems unfolds as a cerebral sojourn. The intricate dance of perplexity and burstiness orchestrates a symphony of intellectual exploration, where each word and concept contributes as an integral note in the composition of knowledge. This singular institutional perspective serves as a vantage point, providing profound insights into the intricacies of prognostic evaluation, creating a nuanced narrative that transcends conventional methodologies.
FUNDING
Nil
AUTHORS CONTRIBUTIONS
CONFLICT OF INTERESTS
Declared none
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