Evidence map›Paper›PMID 39528966›Full record

ArticleBMC medical research methodology2024

On the assessment of the ability of measurements, nowcasts, and forecasts to track changes.

Jonas Rieger, Bolin Liu, Bernd Saugel, Oliver Grothe

Abstract read
In one paragraph

Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Jonas RiegerInstitute for Operations Research, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, 76131, Germany. jonas.rieger@kit.edu.
Bolin LiuInstitute for Operations Research, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, 76131, Germany.
Bernd SaugelDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, Hamburg, 20246, Germany.
Oliver GrotheInstitute for Operations Research, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, 76131, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeasurements, nowcasts, or forecasts ideally should correctly reflect changes in the values of interest. In this article, we focus on how to assess the ability of measurements, nowcasts, or forecasts to correctly predict the direction of changes in values - which we refer to as the ability to track changes (ATC).

methodsWe review and develop visual techniques and quantitative measures to assess ATC. Extensions for noisy data and estimation uncertainty are implemented using bootstrap confidence intervals and exclusion areas.

resultsWe exemplarily illustrate the proposed methods to assess the ability to track changes for nowcasting during the COVID-19 pandemic, patient admissions to an emergency department, and non-invasive blood pressure measurements. The proposed methods effectively evaluate ATC across different applications.

conclusionsThe developed ATC assessment methods offer a comprehensive toolkit for evaluating the ATC of measurements, nowcasts, and forecasts. These techniques provide valuable insights into model performance, complementing traditional accuracy measures and enabling more informed decision-making in various fields, including public health, healthcare management, and medical diagnostics.

Indexed as

COVID-19ForecastingSARS-CoV-2Emergency Service, HospitalHumansPandemics

Identifiers

PMID39528966
PMCPMC11555927

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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.