Evidence map›Paper›PMID 35035677›Full record

ReviewAmerican journal of translational research2021

Hemodynamic characteristics and early warnings in very old patients.

Hui Lian, Xin Ding, Hongmin Zhang, Dawei Liu, Xiaoting Wang

Abstract readReview
In one paragraph

Review in American journal of translational research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

5 authors.

Hui LianDepartment of Health Care, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730, China.
Xin DingDepartment of Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730, China.
Hongmin ZhangDepartment of Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730, China.
Dawei LiuDepartment of Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730, China.
Xiaoting WangDepartment of Health Care and Department of Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences Beijing 100730, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The hemodynamic characteristics of very old patients (VOPs) are unique. With increasing age, patients may experience reduced diastolic function, increased rates of valvular heart disease and coronary atherosclerosis, stiffer vessels, and a reduced heart response to stimulations. Structural and functional modifications are linked to cardiac aging; echocardiography reveals concentric remodeling of the left ventricle, dilation of the left atrium, thickening and calcification of the valves, modification of the large vessels, and abnormal ventricular relaxation. According to a comprehensive understanding of the insufficient compensatory mechanisms of the aging heart, arrythmia should be avoided to the maximum extent and "conservative" fluid therapy should be provided together with appropriate blood pressure control. Considering these factors will improve the success rate of resuscitation and significantly reduce economic loss. In addition, more attention should be paid to the diastolic blood pressure in VOPs.

Indexed as

early warningfluid therapyHemodynamicresuscitationvery old patients

Identifiers

PMID35035677
PMCPMC8748106

What OpenQuestion holds

Textmetadata
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.