Evidence map›Paper›PMID 25180494›Full record

ArticlePloS one2014

Predicting early mortality in adult trauma patients admitted to three public university hospitals in urban India: a prospective multicentre cohort study.

Martin Gerdin, Nobhojit Roy, Monty Khajanchi, Vineet Kumar, Satish Dharap, Li Felländer-Tsai, Max Petzold, Sanjeev Bhoi, Makhan Lal Saha, Johan von Schreeb

Erratum issuedAbstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

8 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Scoring severity in trauma: comparison of prehospital scoring systems in trauma ICU patients.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2017
    Article
  5. Observational
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Martin GerdinHealth Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
Nobhojit RoyHealth Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden; Department of Surgery, Bhabha Atomic Research Centre Hospital, Mumbai, India; School of Habitat, Tata Institute of Social Sciences, Mumbai, India.
Monty KhajanchiDepartment of Surgery, King Edward Memorial Hospital, Mumbai, India.
Vineet KumarDepartment of Surgery, Lokmanya Tilak Municipal Medical College and General Hospital, Mumbai, India.
Satish DharapDepartment of Surgery, Lokmanya Tilak Municipal Medical College and General Hospital, Mumbai, India.
Li Felländer-TsaiDivision of Orthopedics and Biotechnology, Department of Clinical Science Intervention and Technology, Karolinska Institutet, Stockholm, Sweden.
Max PetzoldCentre for Applied Biostatistics, Occupational and Environmental Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.
Sanjeev BhoiDepartment of Emergency Medicine, Jai Prakash Narayan Apex Trauma Center, All India Institute of Medical Sciences, New Delhi, India.
Makhan Lal SahaDepartment of Surgery, Institute of Post-Graduate Medical Education and Research and Seth Sukhlal Karnani Memorial Hospital, Kolkata, India.
Johan von SchreebHealth Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn India alone, more than one million people die yearly due to trauma. Identification of patients at risk of early mortality is crucial to guide clinical management and explain prognosis. Prediction models can support clinical judgement, but existing models have methodological limitations. The aim of this study was to derive a vital sign based prediction model for early mortality among adult trauma patients admitted to three public university hospitals in urban India.

methodsWe conducted a prospective cohort study of adult trauma patients admitted to three urban university hospitals in India between October 2013 and January 2014. The outcome measure was mortality within 24 hours. We used logistic regression with restricted cubic splines to derive our model. We assessed model performance in terms of discrimination, calibration, and optimism.

resultsA total of 1629 patients were included. Median age was 35, 80% were males. Mortality between admission and 24 hours was 6%. Our final model included systolic blood pressure, heart rate, and Glasgow coma scale. Our model displayed good discrimination, with an area under the receiver operating characteristics curve (AUROCC) of 0.85. Predicted mortality corresponded well with observed mortality, indicating good calibration.

conclusionThis study showed that routinely recorded systolic blood pressure, heart rate, and Glasgow coma scale predicted early hospital mortality in trauma patients admitted to three public university hospitals in urban India. Our model needs to be externally validated before it can be applied in the clinical setting.

Indexed as

CitiesAdultBlood PressureCalibrationFemaleGlasgow Coma ScaleHeart RateHospitalizationHospitals, PublicHospitals, UniversityHumansIndiaMaleMiddle AgedNonlinear DynamicsPrognosis

Identifiers

PMID25180494
PMCPMC4152220

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Registered trials

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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.