Objective To evaluate the sedative and analgesic efficacy and adverse effect of dexmedetomidine versus propofol on the postoperative patients in intensive care unit (ICU). Methods The relevant randomized controlled trials (RCTs) were searched in The Cochrane Library, MEDLINE, PubMed, SCI, SpringerLinker, ScinceDirect, CNKI, VIP, WanFang Data and CBM from the date of their establishment to November 2011. The quality of the included studies was evaluated after the data were extracted by two reviewers independently, and then the meta-analysis was performed by using RevMan 5.1. Results Ten RCTs involoving 793 cases were included. The qualitative analysis results showed: within a certain range of dosage as dexmedetomidine: 0.2-2.5 μg/(kg·h), and propofol: 0.8-4 mg/(kg·h), dexmedetomidine was similar to propofol in sedative effect, but dexmedetomidine group needed smaller dosage of supplemental analgesics during the period of sedative therapy. The results of meta-analysis showed: the percentage of patients needing supplemental analgesics in dexmedetomidine group was less than that in propofol group during the period of sedative therapy (OR=0.24, 95%CI 0.08 to 0.68, P=0.008). Compared with the propofol group, the duration of ICU stay was significantly shorter in the dexmedetomidine group (WMD= –1.10, 95%CI –1.88 to –0.32, P=0.006), but the mechanical ventilated time was comparable between the two groups (WMD=0.89, 95%CI –1.15 to 2.93, P=0.39); the incidence of adverse effects had no significant difference between two groups (bradycardia: OR=3.57, 95%CI 0.86 to 14.75, P=0.08; hypotension: OR=1.00, 95%CI 0.30 to 3.32, P=1.00); respiratory depression seemed to be more frequently in propofol group, which however needed further study. Mortalities were similar in both groups after the sedative therapy (OR=1.03, 95%CI 0.54 to 1.99, P=0.92). Conclusion Within an exact range of dosage, dexmedetomidine is comparable with propofol in sedative effect. Besides, it has analgesic effect, fewer adverse effects and fewer occurrences of respiratory depression, and it can save the extra dosage of analgesics and shorten ICU stay. Still, more larger-sample, multi-center RCTs are needed to provide more evidence to support this outcome.
Objective To explore the distribution characteristics and prognostic risk factors of critically ill patients who has long-term hospitalization in intensive care unit ( ICU) . Methods A retrospective study was carried out to evaluate 119 critically ill patients from January 2003 to July 2009 by extracting data from computerized hospital information system. The patients were divided into a survival group and a non-survival group based on discharging outcomes. A binary logistic regression analysis wasintroduced to investigate potential risk factors of prognosis. Results Age, type of payment, entity of disease,and length of ICU stay were significantly different between the two groups ( P lt; 0. 05) in independent-Samples T test. Logistic regressions indicated that age, length of ICU stay and plasma infusion were independent predictors for worse outcome. Conclusions Age, length of ICU stay and plasma infusion may directly influence the prognosis of patients with prolonged stay in ICU. Intensive therapies should be emphasized for those patients at high risk.
ObjectiveTo systematically evaluate the efficacy of high-flow nasal cannula oxygen therapy (HFNC) in post-extubation intensive care unit (ICU) patients.MethodsThe PubMed, Embase, Cochrane Library, CNKI, WanFang, VIP Databases were searched for all published available randomized controlled trials (RCTs) or cohort studies about HFNC therapy in post-extubation ICU patients. The control group was treated with conventional oxygen therapy (COT) or non-invasive positive pressure ventilation (NIPPV), while the experimental group was treated with HFNC. Two reviewers separately searched the articles, evaluated the quality of the literatures, extracted data according to the inclusion and exclusion criteria. RevMan5.3 was used for meta-analysis. The main outcome measurements included reintubation rate and length of ICU stay. The secondary outcomes included ICU mortality and hospital acquired pneumonia (HAP) rate.ResultsA total of 20 articles were enrolled. There were 3 583 patients enrolled, with 1 727 patients in HFNC group, and 1 856 patients in control group (841 patients with COT, and 1 015 with NIPPV). Meta-analysis showed that HFNC had a significant advantage over COT in reducing the reintubation rate of patients with postextubation (P<0.000 01), but there was no significant difference as compared with that of NIPPV (P=0.21). It was shown by pooled analysis of two subgroups that compared with COT/NIPPV, HFNC had a significant advantage in reducing reintubation rate in patients of postextubation (P<0.000 01). There was no significant difference in ICU mortality between HFNC and COT (P=0.38) or NIPPV (P=0.36). There was no significant difference in length of ICU stay between HFNC and COT (P=0.30), but there had a significant advantage in length of ICU stay between HFNC and NIPPV (P<0.000 01). It was shown by pooled analysis of two subgroups that compared with COT/NIPPV, HFNC had a significant advantage in length of ICU stay (P=0.04). There was no significant difference in HAP rate between HFNC and COT (P=0.61) or NIPPV (P=0.23).ConclusionsThere is a significant advantage to decrease reintubation rate between HFNC and COT, but there is no significant difference in ICU mortality, length of ICU stay or HAP rate. There is a significant advantage to decrease length of ICU stay between HFNC and NIPPV, but there is no significant difference in ICU mortality, reintubation rate or HAP rate.
ObjectiveTo explore the development and application of a novel ventilator alarm management model in critically ill patients receiving invasive mechanical ventilation (MV) in the intensive care unit (ICU) using machine learning (ML) and Internet of Medical Things (IoMT). The study aims to identify alarms’ intervention requirements. MethodsA retrospective cohort study and ML analysis were conducted, including adult patients receiving invasive MV in the ICU at West China Hospital from February 10, 2024, to July 22, 2024. A total of 76 ventilator alarm-related parameters were collected through the IoMT system. Feature selection was performed using a stratified approach, and six ML algorithms were applied: Gaussian Naive Bayes, K-Nearest Neighbors, Linear Discriminant Analysis, Support Vector Machine, Categorical Boosting (CatBoost), and Logistic Regression. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC-ROC). ResultsA total of 107 patients and their associated ventilator alarm records were included. Thirteen highly relevant features were selected from the 76 parameters for model training through stratified feature selection. The CatBoost model demonstrated the best predictive performance, with an AUC-ROC of 0.984 7 and an accuracy of 0.912 3 in the training set. External validation of the CatBoost model yielded an AUC-ROC of 0.805 4. ConclusionThe CatBoost-based ML model successfully constructed in this study has high accuracy and reliability in predicting the ventilator alarms in ICU patients, providing an effective tool for ventilator alarm management. The CatBoost-based ML method exhibited remarkable efficacy in predicting the necessity of ventilator intervention in critically ill ICU patients. Further large-scale multicenter studies are recommended to validate its clinical application value and promote model optimization and implementation.
ObjectiveTo systematically review the risk factors associated with sleep disorders in ICU patients.MethodsWe searched The Cochrane Library, PubMed, EMbase, Web of Science, CNKI, Wanfang Data, VIP and CBM databases to collect cohort studies, case-control studies and cross-sectional studies on the risk factors associated with sleep disorders in ICU patients from inception to October, 2018. Two reviewers independently screened literature, extracted data and evaluated the bias risk of included studies. Then, meta-analysis was performed by using RevMan 5.3 software.ResultsA total of 9 articles were included, with a total of 1 068 patients, including 12 risk factors. The results of meta-analysis showed that the combined effect of equipment noise (OR=0.42, 95%CI 0.26 to 0.68, P=0.000 4), patients’ talk (OR=0.53, 95%CI 0.42 to 0.66, P<0.000 01), patients’ noise (OR=0.39, 95%CI 0.21 to 0.74, P=0.004), light (OR=0.29, 95%CI 0.18 to 0.45, P<0.000 01), night treatment (OR=0.36, 95%CI 0.26 to 0.50, P<0.000 01), diseases and drug effects (OR=0.17,95%CI 0.08 to 0.36, P<0.000 01), pain (OR=0.37, 95%CI 0.17 to 0.82, P=0.01), comfort changes (OR=0.34,95%CI 0.17 to 0.67,P=0.002), anxiety (OR=0.31,95%CI 0.12 to 0.78, P=0.01), visit time (OR=0.72, 95%CI 0.53 to 0.98, P=0.04), economic burden (OR=0.63, 95%CI 0.48 to 0.82, P=0.000 5) were statistically significant risk factors for sleep disorders in ICU patients.ConclusionCurrent evidence shows that the risk factors for sleep disorders in ICU patients are environmental factors (talking voices of nurses, patient noise, and light), treatment factors (night treatment), disease factors (disease itself and drug effects, pain,) and psychological factors (visiting time, economic burden). Due to the limited quality and quantity of included studies, more high quality studies are needed to verify the above conclusions.
Objective To investigate the characteristics of ventilator associated pneumonia (VAP)caused by Stenotrophomonas maltophilia(Sm)in ICU。Methods The clinical data of 39 patients with VAP caused by Sm，from Jan 2001 to Dec 2006，were retrospectively investigated．Results In 15 kinds of antibiotics sensitivity test，all cases showed 100％ resistance to 12 kinds of antibiotics except sulfamethoxazole／trimethoprim。ticarcillin／clavulanic acid and ciprofloxacin with sensitivity rate of 46．2％ ， 30．8％ and 12．8％ ．respectively．92．30％ of Sm VAP were CO—infected with other microorganisms and 79．5％ of VAP were late-onset．The use of broad-spectrum antibiotics．especially carbapenem．and prolonged mechanical ventilation more than 7 days were risk factors for Sm VAP．Morbidity of Sm VAP was 87．2％ ．Conclusions Sm VAP has an important role in ICU infections with high morbidity and CO-infection rate．It should be alerted to the possibility of Sm VAP in the case of when prolonged ventilation (gt;7 days)or carbapenem is used．
Objective To analyze morbility，risk factors，etiology，treatment and outcome of nosocomial pulmonary fungal infections in respiratory intensive care unit（RICU）.Methods Forty-seven respiratory RICU patients with nosocomial pulmonary fungal infections between July 2000 and June 2005 were retrospectively analyzed.Results All of the 47 cases were clinically diagnosed as probable nosocomial pulmonary fungal infections，with the morbidity of 10.8% significantly higher than general wards（1.8%，Plt;0.005）.COPD and bacterial pneumonia were the major underlying diseases of respiratory system with a percent of 38.30% and 36.17%，respectively.Forty-one patients (87.2%) had risk factors for fungal infections.Compared with general wards，the proportion of Aspergillosis was higher in RICU without significant difference (Pgt;0.1)；the proportions of Candida glabrata and Candida tropicalis were higher too，but that of Candida krusei was relatively low.The effective rate of antifungal treatment was 79.1% and fluconazol was the most common used antifungal agents.The mortality of fungal infection in RICU was higher than that of general wards but without significant difference（Pgt;0.1）.Conclusion The morbidity of nosocomial pulmonary fungal infection in respiratory RICU is higher than that in general wards.The proportions of infection caused by Aspergilli and some Candida resistant to fluconazol is relatively high.Early and effective treatment is needed in these patients considering the poor prognosis.
ObjevtiveThe morbidity of intensive care unit-acquired swallowing disorder (ICU-ASD) was clarified through meta-analysis by synthesizing previous evidence, in order to provide an evidence-based basis for early identification and intervention of ICU-ASD. Methods A computerized search of PubMed, Embase, Web of Science, The Cochrane Library, CHINAL, China Knowledge Network, Wanfang Data Knowledge Service Platform, and Chinese Science and Technology Journal Database was conducted to retrieve the relevant literature on the morbidity of ICU-ASD published in China and abroad from the database establiment to December 2022. Considering the quality of the included literature, the Chinese database excluded master's theses and non-core journals. Meta-analysis of morbidity was performed using Stata 12.0. Results A total of 19 papers, including 4291 patients, were included. Meta-analysis showed that the overall morbidity of ICU-ASD was 36% [95% confidential interval (CI) 26% - 46%; I2=97.62%, P<0.01]. Subgroup analyses showed that the morbidity of ICU-ASD in Asian, European, South American, and North American was 39% (95%CI 28% - 50%), 23% (95%CI 8% - 44%), 52% (95%CI 46% - 57%), and 39% (95%CI 20% - 61%), respectively; and that the morbidity of male and female ICU-ASD was 36% (95%CI 24% - 48%) and 33% (95%CI 22% - 45%), respectively; the morbidity of ICU-ASD was 41% (95%CI 30% - 52%) and 31% (95%CI 18% - 44%) in the patients with and without hypertension, respectively; the morbidity of ICU-ASD was 58% (95%CI 42% - 73%) and 51% (95%CI 36% - 66%) in the patients with and without respiratory disease respectively; the morbidity of ICU-ASD in the patients with and without diabetes mellitus was 37% (95%CI 24% - 51%) and 39% (95%CI 28% - 51%), respectively; the morbidity of ICU-ASD in the patients with and without renal disease was 40% (95%CI 23% - 59%) and 35% (95%CI 24% - 46%), respectively; the morbidity of ICU-ASD in the patients with intubation caliber ≤7.5 mm and >7.5 mm was 31% (95%CI 19% - 45%) and 37% (95%CI 22% - 54%), respectively; the morbidity of ICU-ASD in the patients with and without heart failure was 58% (95%CI 30% - 84%) and 36% (95%CI 23% - 51%), respectively; and the morbidity of ICU-ASD in patients with and without arrhythmia was 36% (95%CI 11% - 65%) and 31% (95%CI 21% - 42%), respectively; the morbidity of ICU-ASD in the patients with and without neurologic disease was 48% (95%CI 24% - 72%) and 34% (95%CI 15% - 57%), respectively. Begg's test P<0.05, Egger's test P<0.05, suggesting publication bias in the study, and the cut-and-patch method corrected for an overall incidence result of 27% (95%CI 18% - 36%). Conclusions Meta-analysis reveals an overall morbidity of 36% for ICU-ASD and 27% for the cut-and-patch correction. Subgroup analysis reveals that the morbidity of ICU-ASD is significantly higher in patients with hypertension, heart failure, and neurological disorders than in patients without these disorders. Current evidence suggests that the prevalence of ICU-ASD is high and needs to be taken seriously. Timely screening and assessment of swallowing disorders is recommended for intensive care unit patients, especially those with hypertension, heart failure, and neurological disorders.
ObjectivesTo assess the efficacy of non-drug interventions on improving sleep quality in ICU patients by network meta-analysis.MethodsThe Cochrane Library, PubMed, EMbase, Web of Science, CNKI, WanFang Data, VIP and CBM databases were electronically searched to collect randomized controlled trials (RCTs) on non-drug interventions on improving sleep quality in ICU patients from inception to December, 2018. Two reviewers independently screened literature, extracted data and assessed risk of bias of included studies, then, network meta-analysis was performed by using the Stata 13.0 software.ResultsA total of 12 RCTs, involving 1 223 patients and 9 non-pharmacological interventions (music therapy, comprehensive nursing intervention, TCM emotions, music therapy+TCM emotions, Chinese medicine pillow therapy, ear acupressure, eye mask+earplugs+music, eye mask+earplugs, regular care) were included. The results of Pittsburgh sleep quality index (PSQI) showed that eye mask+earplugs, eye masks, and comprehensive nursing interventions were superior to conventional care in improving sleep quality in ICU patients, and the rankings were: eye mask+earplugs>eye mask>comprehensive nursing intervention, music therapy+TCM emotional>Chinese medicine emotional>music therapy>general care. The results of Richards-Campbell sleep scale (RCSQ) showed that eye mask+earplugs+music, Chinese medicine pillow therapy, and auricular pressure beans were superior to conventional care, and the rankings were: eye mask+earplugs+music>Chinese medicine pillow therapy>music therapy>ear acupressure beans>general care.ConclusionsThe evidence shows that in improving the sleep quality of ICU patients, eye mask + earplug, eye mask, comprehensive nursing intervention, music therapy + TCM emotional characteristics may all be effective intervention methods. It is suggested that more non-drug interventions should be carried out in the future for enhancing the sleep quality of ICU patients.
ObjectiveTo identify the risk factors of Intensive Care Unit (ICU) nosocomial infection in ICU ward in a first-class hospital in Wuxi, and discuss the effective control measures, in order to provide evidence for making strategies in preventing and controlling nosocomial infection.
MethodsAccording to the principle of random sampling and with the use of case-control study, a sample of 100 nosocomial infection patients were selected randomly from January 2012 to December 2014 as survey group, and another 100 patients without nosocomial infection as control group. The data were input using EpiData 2.0, and SPSS 13.0 was used for statistical analysis; t-test and χ2 test were conducted, and the risk factors were analyzed using multi-variate logistic regression model. The significant level of P-value was 0.05.
ResultsBased on the results of univariate analysis, there were 13 risk factors for ICU nosocomial infection, including diabetes mellitus, hypoproteinemia, being bedridden, surgical operation, immunosuppression, glucocorticoids, organ transplantation, tracheal intubation, length of hospitalization, length of mechanical ventilation, length of central venous catheter, length of urinary catheter, and length of nasogastric tube indwelling. Multi-variate logistic analysis indicated that hospitalization of 7 days or longer[OR=1.106, 95%CI (1.025, 1.096), P=0.001], diabetes mellitus[OR=2.770, 95%CI (1.068, 7.186), P=0.036], surgical operation[OR=7.524, 95%CI (2.352, 24.063), P=0.001], mechanical ventilation of 7 days or longer[OR=1.222, 95%CI (1.116, 1.339), P<0.001], and nasogastric tube indwelling of 7 days or longer[OR=1.110, 95%CI (1.035, 1.190), P=0.003] were considered as independent risk factors for ICU nosocomial infection.
ConclusionHospitalization of 7 days or longer, diabetes mellitus, surgical operation, tracheal intubation of 7 days or longer, and gastric intubation of 7 days or longer are the major risk factors for nosocomial infection in ICU ward. Advanced intervention and comprehensive prevention measures are helpful to reduce the nosocomial infection rate and ensure the safety of medical treatment.
