Evidence map›Paper›PMID 32200388›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2020

A New Nomogram Allowing Physicians to Predict Patients at High Risk of Fever Occurring After Prostate Biopsy.

Haoran Xia, Hui Wang, Lei Chen, Jialin Meng, Jun Zhou, Chaozhao Liang

Open access · hybridAbstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Haoran XiaDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China (mainland).
Hui WangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China (mainland).
Lei ChenDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China (mainland).
Jialin MengDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China (mainland).
Jun ZhouDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China (mainland).
Chaozhao LiangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China (mainland).
First Affiliated Hospital of Anhui Medical University · CNAnhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND To facilitate early treatment, we constructed a nomogram to predict risk of postoperative fever before prostate biopsy in patients with high risk of fever. MATERIAL AND METHODS We collected information on patients undergoing prostate biopsy from January 2015 to December 2018 from their medical records, including clinical characteristics and laboratory test results. Finally, after strict screening, the prediction model was established in 440 patients who underwent a transrectal prostate biopsy (TRPB). We divided these patients into a training group and validation group at a ratio of 7: 3, respectively. Univariate analysis and multivariate logistic regression analysis were used to select the predictors and to develop the model. Calibration curve and C-index were used to evaluate the accuracy of the nomogram, while DCA was used to assess the clinical value. RESULTS The individualized predictive nomogram contained 3 clinical features - Biopsy-positive rate (BPR), Hematuria, and Urine WBC - significantly associated with post-biopsy fever. The nomogram had good discriminating ability in both the training group and validation group - the C-index was 0.774 (95% CI=0.717-0.832) in the training group and 0.808 (95% CI=0.706-0.909) in the validation group. Hosmer-Lemeshow test proved a good calibration curve fit. The DCA curve suggested that the nomogram would have good clinical utility. CONCLUSIONS This is the first study to develop a nomogram to predict fever after prostate biopsy via Biopsy-positive rate (BPR), Hematuria, and Urine WBC. Use of this nomogram might help prevent fever and infection, and could facilitate individualized medical treatment after prostate biopsy.

Indexed as

NomogramsAgedAged, 80 and overBiopsy, NeedleFeverHematuriaHumansLeukocyte CountMaleMiddle AgedPostoperative ComplicationsPredictive Value of TestsProstateProstatic DiseasesProstatic NeoplasmsRetrospective Studies

Identifiers

PMID32200388
PMCPMC7111130
OpenAlexW3003683709

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.