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Record W4230654969 · doi:10.14740/jocmr4330

Relationship Between Blood Pressure Levels on Admission and the Onset of Acute Pneumonia in Elderly Patients With Cerebral Hemorrhage

2020· article· en· W4230654969 on OpenAlexvenueno aff
Taishi Ishisaka, Yuta Igarashi, Kumie Kodera, Tazuo Okuno, Takuro Morita, Taroh Himeno, Kazu Hamada, Hiroshi Yano, Toshihiro Higashikawa, Osamu Iritani, Kunimitsu Iwai, Shigeto Morimoto, Masashi Okuro

Bibliographic record

VenueJournal of Clinical Medicine Research · 2020
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBlood pressurePrehypertensionInternal medicinePneumoniaCardiologyDiabetes mellitusDyslipidemiaDiastoleDiseaseEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: We have reported that hypertension on admission in elderly patients with acute cerebral infarction is an independent predictor for the development of acute pneumonia. However, the relationship between blood pressure on admission owing to cerebral hemorrhage and the development of pneumonia has not been fully investigated. In this study, we evaluated the relationship between blood pressure levels on admission and the development of pneumonia in elderly patients with cerebral hemorrhage who were in the acute phase. METHODS: Subjects consisted of 117 elderly patients with cerebral hemorrhage who were in the acute phase and were emergently admitted to the Department of Geriatric Medicine, Kanazawa Medical University between 2005 and 2015 (59 males and 58 females, the mean age ± standard deviation (SD) of 80 ± 8 years, and the range of 65 - 98 years). Blood pressure levels on admission were classified into the following four groups: normal blood pressure/mild hypertension group (systolic blood pressure of < 160 mm Hg and diastolic blood pressure of < 100 mm Hg), moderate hypertension group (systolic hypertension of 160 - 179 mm Hg or diastolic blood pressure of 100 - 109 mm Hg), severe hypertension group (systolic hypertension of 180 - 199 mm Hg or diastolic blood pressure of 110 - 119 mmHg), and serious hypertension group (systolic blood pressure of ≥ 200 mm Hg or diastolic blood pressure of ≥ 120 mm Hg). Between the two groups (group of patients with acute pneumonia and group of those with absence of pneumonia), age, sex, body mass index (BMI), history of stroke, history of heart disease, chronic kidney disease, diabetes, dyslipidemia, prehypertension, blood pressure on admission, Japan Coma Scale (JCS) on admission, white blood cell count, C-reactive protein (CRP), albumin, bleeding sites, bleeding amount, and the presence or absence of centerline shift on brain computed tomography (CT) images were retrospectively evaluated. Furthermore, factors related to cerebral hemorrhage in the development of acute pneumonia in patients with cerebral hemorrhage were verified. RESULTS: Of the 117 patients, 30 (25.6%) had acute pneumonia. Age, sex, bleeding amount, midline shift, blood pressure classification on admission, JCS, white blood cell count, CRP, albumin, diabetes were adopted as confounding factors in the development of acute pneumonia. Results of multiple logistic regression analysis showed significant differences between these two groups in the following four items: CRP, white blood cell count, JCS, and blood pressure classification on admission. After adjustment of these confounding factors, the incidence of acute pneumonia in the blood pressure groups other than serious hypertension group was set as 1, and the odds ratio of pneumonia onset in serious hypertension group was revealed to be 5.54, with the 95% confidence interval of 1.49 - 20.6. CONCLUSIONS: We found that serious hypertension on admission is a risk factor for the development of acute pneumonia in elderly patients with cerebral hemorrhage who are in the acute phase.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.168
GPT teacher head0.453
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2020
Admission routes1
Has abstractyes

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