Evidence map›Paper›PMID 39845160›Full record

ArticleSurgery in practice and science2022

Development of the PIP score: A metric for predicting Intensive Care Unit admission among patients undergoing emergency laparotomy.

Daniel W Kitua, Ramadhani H Khamisi, Mohammed S A Salim, Albert M Kategile, Ally H Mwanga, Nashivai E Kivuyo, Deo J Hando, Peter P Kunambi, Larry O Akoko

Abstract read
In one paragraph

Article in Surgery in practice and science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Improving Emergency Response: A Comparative Analysis of Traditional vs Artificial Intelligence-assisted Triage Systems in Health Care and Their Impact.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Daniel W KituaDepartment of Surgery, Muhimbili University of Health and Allied Sciences, United Nations Rd., P.O. Box 65001, Upanga, Dar es Salaam, Tanzania.
Ramadhani H KhamisiDepartment of Surgery, Muhimbili University of Health and Allied Sciences, United Nations Rd., P.O. Box 65001, Upanga, Dar es Salaam, Tanzania.
Mohammed S A SalimMuhimbili National Hospital, Department of Surgery, Malik Rd., Upanga, Dar es Salaam, Tanzania.
Albert M KategileDepartment of Surgery, Muhimbili University of Health and Allied Sciences, United Nations Rd., P.O. Box 65001, Upanga, Dar es Salaam, Tanzania.
Ally H MwangaDepartment of Surgery, Muhimbili University of Health and Allied Sciences, United Nations Rd., P.O. Box 65001, Upanga, Dar es Salaam, Tanzania.
Nashivai E KivuyoDepartment of Surgery, Muhimbili University of Health and Allied Sciences, United Nations Rd., P.O. Box 65001, Upanga, Dar es Salaam, Tanzania.
Deo J HandoDepartment of Surgery, Muhimbili University of Health and Allied Sciences, United Nations Rd., P.O. Box 65001, Upanga, Dar es Salaam, Tanzania.
Peter P KunambiMuhimbili University of Health and Allied Sciences, Department of Clinical Pharmacology, United Nations Rd., Upanga, Dar es Salaam, Tanzania.
Larry O AkokoDepartment of Surgery, Muhimbili University of Health and Allied Sciences, United Nations Rd., P.O. Box 65001, Upanga, Dar es Salaam, Tanzania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Emergency laparotomy cases account for a significant proportion of the surgical caseload requiring postoperative intensive care. However, access to Intensive Care Unit (ICU) services has been limited by the scarcity of resources, lack of guidelines, and paucity of triaging tools. Objective: This study aimed at developing a feasible Methodology: A case-control study utilizing the records of 108 patients who underwent emergency laparotomy was conducted. The primary outcome was the postoperative disposition status. Cases were defined as emergency laparotomy patients admitted to the ICU. The control group constituted patients admitted to the general ward. Logistic regression analysis was performed to identify the perioperative predictors of outcome. The PIP score was developed as a composite of each statistically significant variable remaining in the final logistic regression model. Results: The significant positive predictors of ICU admission included a worsening American Society of Anesthesiologists - Physical Status, decreasing preoperative baseline axillary temperature, increasing preoperative baseline pulse rate, and intraoperative blood-product transfusion. The scoring system incorporating the identified predictors was presented as a numeric scale ranging from zero to four. Two levels of prediction were defined with reference to the optimum cut-off value; a score of <3 (low-intermediate prediction) and a score of ≥3 (high prediction [OR = 37.00, 95% CI = 11.22-122.02, Conclusion: The PIP score proves useful as a feasible postoperative triaging adjunct for emergency laparotomy cases. Nonetheless, further validation studies are required.

Indexed as

Emergency general surgeryEmergency laparotomyIntensive Care Unit (ICU) admissionPost-emergency laparotomy ICU admission Predictive score (PIP score)Postoperative triaging

Identifiers

PMID39845160
PMCPMC11749966

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.