Evidence map›Paper›PMID 28279999›Full record

Observational studyBMJ open2017

Simplified Mortality Score for the Intensive Care Unit (SMS-ICU): protocol for the development and validation of a bedside clinical prediction rule.

Anders Granholm, Anders Perner, Mette Krag, Peter Buhl Hjortrup, Nicolai Haase, Lars Broksø Holst, Søren Marker, Marie Oxenbøll Collet, Aksel Karl Georg Jensen, Morten Hylander Møller

Abstract readMulticenter StudyObservational StudyValidation Study
In one paragraph

Observational study in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Is research from databases reliable? No.Intensive care medicine · 2019
    Article
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

10 authors.

Anders GranholmDepartment of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.ORCID 0000-0001-5799-7655
Anders PernerDepartment of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Mette KragDepartment of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Peter Buhl HjortrupDepartment of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Nicolai HaaseDepartment of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Lars Broksø HolstDepartment of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Søren MarkerDepartment of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Marie Oxenbøll ColletDepartment of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Aksel Karl Georg JensenSection of Biostatistics, University of Copenhagen, Copenhagen, Denmark.
Morten Hylander MøllerDepartment of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMortality prediction scores are widely used in intensive care units (ICUs) and in research, but their predictive value deteriorates as scores age. Existing mortality prediction scores are imprecise and complex, which increases the risk of missing data and decreases the applicability bedside in daily clinical practice. We propose the development and validation of a new, simple and updated clinical prediction rule: the Simplified Mortality Score for use in the Intensive Care Unit (SMS-ICU). METHODS AND ANALYSIS: During the first phase of the study, we will develop and internally validate a clinical prediction rule that predicts 90-day mortality on ICU admission. The development sample will comprise 4247 adult critically ill patients acutely admitted to the ICU, enrolled in 5 contemporary high-quality ICU studies/trials. The score will be developed using binary logistic regression analysis with backward stepwise elimination of candidate variables, and subsequently be converted into a point-based clinical prediction rule. The general performance, discrimination and calibration of the score will be evaluated, and the score will be internally validated using bootstrapping. During the second phase of the study, the score will be externally validated in a fully independent sample consisting of 3350 patients included in the ongoing Stress Ulcer Prophylaxis in the Intensive Care Unit trial. We will compare the performance of the SMS-ICU to that of existing scores. ETHICS AND DISSEMINATION: We will use data from patients enrolled in studies/trials already approved by the relevant ethical committees and this study requires no further permissions. The results will be reported in accordance with the Transparent Reporting of multivariate prediction models for Individual Prognosis Or Diagnosis (TRIPOD) statement, and submitted to a peer-reviewed journal.

Indexed as

Critical CareAdolescentAdultAgedCohort StudiesCritical IllnessDecision Support TechniquesFemaleHospital MortalityHumansIntensive Care UnitsMaleMiddle AgedPoint-of-Care SystemsPrognosisSeverity of Illness IndexINTENSIVE & CRITICAL CARE

Identifiers

PMID28279999
PMCPMC5353313

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.