Evidence map›Paper›PMID 35321053›Full record

ArticleTherapeutic advances in urology

Patient characteristics predicting prolonged length of hospital stay following robotic-assisted radical prostatectomy.

Albert El Hajj, Muhieddine Labban, Guillaume Ploussard, Jabra Zarka, Nassib Abou Heidar, Aurelie Mailhac, Hani Tamim

Abstract read
In one paragraph

Article in Therapeutic advances in urology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

7 authors.

Albert El HajjDivision of Urology, Department of Surgery, American University of Beirut, Beirut, Lebanon.
Muhieddine LabbanDivision of Urology, Department of Surgery, American University of Beirut, Beirut, Lebanon.ORCID https://orcid.org/0000-0002-4580-1915
Guillaume PloussardDepartment of Urology, La Croix du Sud Hospital, Quint-Fonsegrives, France.
Jabra ZarkaDivision of Urology, Department of Surgery, American University of Beirut, Beirut, Lebanon.ORCID https://orcid.org/0000-0001-8668-6741
Nassib Abou HeidarDivision of Urology, Department of Surgery, American University of Beirut, Beirut, Lebanon.
Aurelie MailhacClinical Research Institute, American University of Beirut, Beirut, Lebanon.
Hani TamimClinical Research Institute, American University of Beirut, P.O. Box 11-0236, Riad El-Solh, Beirut 1107 2020, Lebanon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The objective of this study is to determine the preoperative patient characteristics predicting prolonged length of hospital stay (pLOS) following robotic-assisted radical prostatectomy (RARP). Methods: The National Surgical Quality Improvement Program (NSQIP) database was used to select patients who underwent RARP without other concomitant surgeries between 2008 and 2016. Patients' demographics, comorbidities, and laboratory markers were collected to evaluate their role in predicting pLOS. The pLOS was defined as length of stay (LOS) >2 days. A multinomial logistic regression was constructed adjusting for postoperative surgical complications to assess for the predictors of pLOS. Results: We obtained data for 31,253 patients of which 20,774 (66.5%) patients stayed ⩽1 day, 6993 (22.4%) patients stayed for 2 days, and 3486 (11.2%) patients stayed for >2 days. Demographic variables - including body mass index (BMI) <18.5: odds ratio (OR) = 2.8, 95% confidence interval (CI) = [1.7-4.8]; smoking: OR = 1.2, 95% CI = [1.1-1.4]; and dependent functional status: OR = 3.1, 95% CI = [1.6-6.0] - were predictors of pLOS. Comorbidities - such as heart failure: OR = 4.6, 95% CI = [2.0-10.8]; being dialysis dependent: OR = 2.7, 95% CI = [1.4-5.0]; and predisposition to bleeding: OR = 2.0, 95% CI =  [1.5-2.7] - were the strongest predictors of extended hospitalization. In addition, pLOS was more likely to be associated with postoperative bleeding, renal, or pulmonary complications. Conclusion: Preoperative patient characteristics and comorbidities can predict pLOS. These findings can be used preoperatively for risk assessment and patient counseling.

Indexed as

counselinglength of stayprostatic neoplasmsroboticstreatment outcome

Identifiers

PMID35321053
PMCPMC8935550

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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.