ArticleJournal of Korean Neurosurgical Society2024
Trend of Intensive Care Unit Admission in Neurology-Neurosurgery Adult Patients in South Korea : A Nationwide Population-Based Cohort Study.
Article in Journal of Korean Neurosurgical Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe aimed to examine trends in critically ill neurology-neurosurgery (NNS) patients who were admitted to the intensive care unit (ICU) in South Korea and identify risk factors for in-hospital mortality after ICU admission in NNS patients.
methodsThis nationwide population-based retrospective cohort study enrolled adult NNS adult patients admitted to the ICU from 2010 to 2019 extracted from the National Health Insurance Service in South Korea. The critically ill NNS patients were defined as those whose main admission departments were neurology or neurosurgery at ICU admission. The number of ICU admission, age, and total cost for hospitalization from 2010 to 2019 in critically ill NNS patients were examined as trend information. Moreover, multivariable logistic regression modeling was used to identify risk factors for in-hospital mortality among critically ill NNS patients.
resultsWe included 845474 ICU admission cases for 679376 critically ill NNS patients in South Korea between January 1, 2010 to December 31, 2019. The total number of ICU admissions among NNS patients was 79522 in 2010, which increased to 91502 in 2019. The mean age rose from 62.8 years (standard deviation [SD], 15.6) in 2010 to 66.6 years (SD, 15.2) in 2019, and the average total cost for hospitalization per each patient consistently increased from 6206.1 USD (SD, 5218.5) in 2010 to 10745.4 USD (SD, 10917.4) in 2019. In-hospital mortality occurred in 75455 patients (8.9%). Risk factors strongly associated with increased in-hospital mortality were the usage of mechanical ventilator (adjusted odds ratio [aOR], 19.83; 95% confidence interval [CI], 19.42-20.26; p<0.001), extracorporeal membrane oxygenation (aOR, 3.49; 95% CI, 2.42-5.02; p<0.001), and continuous renal replacement therapy (aOR, 6.47; 95% CI, 6.02-6.96; p<0.001). In addition, direct admission to ICU from the emergency room (aOR, 1.38; 95% CI, 1.36-1.41; p<0.001) and brain cancer as the main diagnosis (aOR, 1.30; 95% CI, 1.22-1.39; p<0.001) are also potential risk factors for increased in-hospital mortality.
conclusionIn South Korea, the number of ICU admissions increased among critically ill NNS patients from 2010 to 2019. The average age and total costs for hospitalization also increased. Some potential risk factors are found to increase in-hospital mortality among critically ill NNS patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.