Evidence map›Paper›PMID 42622665›Full record

Trial reportThe Journal of international medical research2026

Clinical validation of continuous glucose monitoring in glycemic management of critically ill sepsis patients: A prospective randomized clinical study.

Qin Si, Yifeng Mao, Jian Lan, Wei Lu, Cheng Zheng, Qian Zhu, Xijiang Zhang

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in The Journal of international medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

7 authors.

Qin SiDepartment of Critical Care Medicine, Taizhou Municipal Hospital (Taizhou University Affiliated Municipal Hospital), School of Medicine, Taizhou University, China.
Yifeng MaoDepartment of Critical Care Medicine, Taizhou Municipal Hospital (Taizhou University Affiliated Municipal Hospital), School of Medicine, Taizhou University, China.
Jian LanDepartment of Critical Care Medicine, Taizhou Municipal Hospital (Taizhou University Affiliated Municipal Hospital), School of Medicine, Taizhou University, China.
Wei LuDepartment of Critical Care Medicine, Taizhou Municipal Hospital (Taizhou University Affiliated Municipal Hospital), School of Medicine, Taizhou University, China.
Cheng ZhengDepartment of Critical Care Medicine, Taizhou Municipal Hospital (Taizhou University Affiliated Municipal Hospital), School of Medicine, Taizhou University, China.ORCID 0000-0002-9472-1807
Qian ZhuNursing Department, Taizhou Municipal Hospital (Taizhou University Affiliated Municipal Hospital), School of Medicine, Taizhou University, China.
Xijiang ZhangDepartment of Critical Care Medicine, Taizhou Municipal Hospital (Taizhou University Affiliated Municipal Hospital), School of Medicine, Taizhou University, China.ORCID 0000-0003-0996-7800

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ObjectiveThis study assessed the accuracy, clinical effectiveness, and utility of continuous glucose monitoring compared with conventional methods in critically ill patients with sepsis.MethodsFrom July 2023 to July 2025, 60 patients with sepsis (mean age, 75.6 ± 27.107 years; mean body mass index, 22.4 ± 2.960 kg/m

Indexed as

Blood GlucoseContinuous Glucose MonitoringGlycemic ControlHyperglycemiaSepsisAgedAged, 80 and overCritical IllnessFemaleHumansIntensive Care UnitsMaleMiddle AgedProspective StudiesBlood Glucosecontinuous glucose monitoringcritical illnessglucose controlhyperglycemiaintensive care unitSepsis

Identifiers

PMID42622665
PMCPMC13494316

What OpenQuestion holds

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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.