Evidence map›Paper›PMID 31259256›Full record

ArticleOpen medicine (Warsaw, Poland)2019

Using Post Transplant 1 Week Tc-99m DPTA Renal Scan as Another Method for Predicting Renal Graft Failure.

Ari Chong, Jung-Min Ha, Nam Kyu Choi, Min Ho Shin

Open access · goldAbstract read
In one paragraph

Article in Open medicine (Warsaw, Poland), 2019. 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
0.2field-weighted citation impact, top 49% of its field
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, 2 citations in OpenAlex.

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 at 1 institution in 1 country.

Ari ChongDepartment of Nuclear Medicine, Chosun University Hospital, 588 Seoseok-dong, dong-gu, Gwangju, Republic of Korea, 501-757.
Jung-Min HaDepartment of Nuclear Medicine, Chosun University Hospital, 588 Seoseok-dong, dong-gu, Gwangju, Republic of Korea, 501-757.
Nam Kyu ChoiDepartment of Surgery, Chosun University Hospital, Gwangju, Korea.
Min Ho ShinDepartment of Surgery, Chosun University Hospital, Gwangju, Korea.
Chosun University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aims of this study were to determine whether post transplant renal scan performed at around 1 week can predict graft failure, and to identify the best predictive factors among easy-to-measure variables. MATERIALS AND

methodsWe retrospectively evaluated patients who underwent Tc-99m DTPA renal scan at approximately 1 week after renal transplantation. They were separated into two categories at 3 months after the operation; graft failure and non-failure. Graft failure was confirmed by biopsy (rejection). Non-failure was confirmed either by biopsy or clinical follow-up with serum creatine (Cr). Scan parameters including glomerular filtration rate (GFR), Hilson perfusion index, peaks of the iliac and graft perfusion curves were analyzed. Clinical variables including age, sex, height, weight, systolic blood pressure, serum Cr, type of donated kidney, side of transplant, and immunosuppressant were also analyzed.

resultsAmong total 45 patients, graft failure was present in 11 cases. The serum Cr level was significantly higher in the failure group. Among scan variables, only the GFR was significantly different between groups. GFR of <44.48 mL/min was predictive of graft failure (sen 88.9%). Serum Cr level >2.13 mg/dL was also predictive (sen 72.7%).

conclusionGFR on renal scan at approximately 1 week after kidney transplant can predict graft failure.

Indexed as

Kidney Function TestsKidney TransplantationRadionuclide Imaging

Identifiers

PMID31259256
PMCPMC6592150
OpenAlexW2954047054

What OpenQuestion holds

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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.