[Analysis of the current quality of life status and influencing factors of sepsis survivors in intensive care unit].
Bibliographic record
Abstract
OBJECTIVE: To explore the current situation and influencing factors of quality of life of septic patients in intensive care unit (ICU) after discharge, and to provide theoretical basis for clinical early psychological intervention and continuity of care. METHODS: A prospective observational study was conducted. The septic patients who were hospitalized in the department of critical care medicine of the Affiliated Hospital of Jining Medical University and discharged with improvement from January 1 to December 31, 2022 were selected as the research objects. The demographic information, basic diseases, infection site, vital signs at ICU admission, severity scores of the condition within 24 hours after ICU admission, various biochemical indexes, treatment process, and prognostic indexes of all the patients were recorded. All patients were assessed by questionnaire at 3 months of discharge using the 36-item short-form health survey scale (SF-36 scale), the activities of daily living scale (ADL scale), and the Montreal cognitive assessment scale (MoCA scale). Multiple linear regression was used to analyze the factors influencing the quality of life of septic patients after discharge from the hospital. RESULTS: A total of 200 septic patients were discharged with improvement and followed up at 3 months of discharge, of which 150 completed the questionnaire. Of the 150 patients, 57 had sepsis and 93 had septic shock. The total SF-36 scale score of septic patients at 3 months of discharge was 81.4±23.0, and the scores of dimensions were, in descending order, role-emotional (83.4±23.0), mental health (82.9±23.6), bodily pain (82.8±23.3), vitality (81.6±23.2), physical function (81.4±23.5), general health (81.1±23.3), role-physical (79.5±27.0), and social function (78.8±25.2). There was no statistically significant difference in the total SF-36 scale score between the patients with sepsis and septic shock (82.6±22.0 vs. 80.7±23.6, P > 0.05). Incorporating the statistically significant indicators from linear univariate analysis into multiple linear regression analysis, and the results showed that the factors influencing the quality of life of septic patients at 3 months after discharge included ADL scale score at 3 months after discharge [β= 0.741, 95% confidence interval (95%CI) was 0.606 to 0.791, P < 0.001], length of ICU stay (β= -0.209, 95%CI was -0.733 to -0.208, P = 0.001), duration of mechanical ventilation (β= 0.147, 95%CI was 0.122 to 0.978, P = 0.012), total dosage of norepinephrine (β= -0.111, 95%CI was -0.044 to -0.002, P = 0.028), mean arterial pressure (MAP) at ICU admission (β= -0.102, 95%CI was -0.203 to -0.007, P = 0.036) and body weight (β= 0.097, 95%CI was 0.005 to 0.345, P = 0.044). CONCLUSIONS: The quality of life of patients with sepsis at 3 months after discharge is at a moderately high level. The influencing factors of the quality of life of patients with sepsis at 3 months after discharge include the ADL scale score at 3 months after discharge, the length of ICU stay, the duration of mechanical ventilation, the total dosage of norepinephrine, MAP at ICU admission and body weight, and healthcare professionals should enhance the treatment and care of the patients during their hospitalization based on the above influencing factors, and pay attention to early psychological intervention and continued care for such patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".