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The Effect of Nocturia on Sleep Quality in Patients with Benign Prostatic Obstruction and Their Female Partners

2022· article· en· W4294752747 on OpenAlexaff
Çağdaş Şenel, Merve Yumrukuz Şenel, Ahmet Asfuroğlu, İbrahim Can Aykanat, Hikmet Fırat

Bibliographic record

VenueJournal of Turkish Sleep Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsYukon University
Fundersnot available
KeywordsNocturiaMedicineSleep qualityUrologySleep (system call)Internal medicineComputer scienceUrinary systemInsomniaPsychiatry

Abstract

fetched live from OpenAlex

Objective: Previous studies showed that nocturia has a negative effect on patients' sleep quality. However, studies that focused on the sleep quality of patients' partners are limited. In this study, we evaluated the impact of nocturia on sleep quality in patients with benign prostatic obstruction (BPO) and their female partners. Materials and Methods: We included 50 BPO patients with nocturia (group 1), 50 patients without nocturia (group 2) and their female partners. Lower urinary tract symptoms of the patients were evaluated by international prostate symptom score, serum prostate-specific antigen, uroflowmetry and urinary ultrasonography. The sleep quality of the patients and their partners were assessed by Pittsburgh sleep quality index (PSQI). The demographic and evaluation outcomes of the participants were recorded. Results: The mean age of the patients and their partners were 637.9 and 57.48.5 years, respectively, with no statistical significance. The patients and their partners in group 1 had significantly higher global PSQI compared with those in group 2. The percentage of poor sleep in patients and partners in group 1 was higher than that in group 2. Conclusion: Nocturia negatively affects the sleep quality of patients with BPO and their partners.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.316
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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