OBJECTIVE

To compare the sedation practices of adult intubated patients with COVID-19-related Acute Respiratory Distress Syndrome (C-ARDS) and ARDS from other causes, and their impact on clinical outcomes in a tertiary hospital.

METHODS

We performed a retrospective cohort on the sedation practices of adult intubated patients with C-ARDS and non-C-ARDS admitted to the intensive care unit of a tertiary hospital from January 2021 to December 2021. Electronic medical records were reviewed to obtain sedative use, sedative dosages, clinical outcomes, and complications.

RESULTS

Among the 150 included patients, 112 had C-ARDS, and 38 had non-C-ARDS. The C-ARDS group showed a significant difference with the non-C-ARDS group in terms of BMI (24.11 vs. 21.09 kg/m2, p < 0.001), use of higher PEEP (16 vs. 10, p < 0.001), and prone positioning (40.18% vs 2.63%, p < 0.01). In terms of sedation practice, C-ARDS patients targeted deeper RASS scores (p=0.038), with a significantly higher proportion receiving more than one sedative (82.14% vs. 18.42, p < 0.001) than non-C-ARDS patients. Sedation doses for midazolam (78 mg/d vs. 36 mg/d; p=0.01) and propofol (mean 2626±1312.97 mg/d vs. 1742±380.99 mg/d; p=0.007), were significantly higher among C-ARDS versus non-C-ARDS group. Duration of hospitalization (9 vs. 20 days; p < 0.001) and ventilator use (7 vs. 14.50 days; p < 0.001) were significantly shorter in the C-ARDS group, albeit with a high mortality (100% vs. 89.47%; p=0.004). Shock-requiring pressor was significantly associated with multiple sedation use [OR=15.11 (1.52-2032.89); p=0.017] and combination use of benzodiazepine and non-benzodiazepines [OR=11.51 (1.17-1541.91); p=0.034] in the C-ARDS but not the C-ARDS group.

CONCLUSION

Patients with C-ARDS had higher sedation requirements in terms of dosage and number of sedatives. The use of multiple sedatives was significantly associated with shock-requiring pressor. We recommend the development of a sedation protocol to guide sedation practices and monitoring of complications in the critically ill.

Human ; Covid-19 ; Intensive Care Units

OBJECTIVES

Clinical pathways (CPs) ensure adherence to heart failure (HF) management guidelines. To optimize quality care in a low resource setting, an evidence-based care pathway for the management of acute HF was implemented at the emergency department (ED) of the Philippine General Hospital (PGH), the designated national tertiary hospital and referral center. This study aimed to describe the characteristics of adults with acute HF admitted at the ED and evaluate the quality of care they received, measured using physician adherence to the hospital’s acute heart failure CP.

METHODS

This was a retrospective, descriptive cohort study. We reviewed the inpatient charts of all adult patients with acute HF admitted to the ED of the PGH and referred to the Division of Cardiovascular Medicine between December 1, 2022 and May 31, 2023. Quality of care was assessed based on adherence to quality indicators adapted from routine and conditional order sets detailed in the pathway. Descriptive statistics was utilized to describe patient characteristics, quality of care, and outcomes.

RESULTS

Two hundred thirty-six (236) patients were included, with a mean age of 51.8 years. Majority were male (53.4%); hypertension (61.4%) and ischemic heart disease (53.8%) were the most common comorbidities, and infection the most common precipitant of decompensation (60.6%). There were optimal adherence rates to routine orders, which included referrals to Internal Medicine and Cardiology, baseline vital signs monitoring, fluid intake and output monitoring, chest radiograph, complete blood count, blood urea nitrogen, sodium, potassium, prothrombin time, partial thromboplastin time, arterial blood gas, urinalysis, and N-terminal pro b-type natriuretic peptide. Conditional orders, such as oxygen support, focused echocardiography, thyroid - stimulating hormone, and the use of vasopressors, diuretics, and venous thromboembolism prophylactic agents, were optimally performed when warranted. However, we noted suboptimal adherence to certain resource-intensive conditional orders, such as hourly monitoring of urine output (61.4%), hooking to cardiac monitor (53.8%), and performance of 12-lead ECG within 10 minutes (56.8%). Further, only 43.9% of patients were referred to the intensive care unit. Troponin I, calcium, magnesium, and albumin were ordered in excess.

CONCLUSION

Overall adherence rate of physicians to the hospital’s Acute Heart Failure Pathway was satisfactory. Work is needed to improve adherence to hourly urine output monitoring, consistent hooking to cardiac monitor, and timely performance of 12-lead ECG – an effort that begins with expanding in-hospital diagnostic equipment and human resource supply. We recommend continuous pathway implementation with periodic evaluation and stakeholder feedback to further improve quality of care.

Human ; Male ; Female ; Middle Aged: 45-64 Yrs Old ; Adult ; Albumins ; Blood ; Blood Urea Nitrogen ; Calcium ; Cardiology ; Chart ; Charts ; Cohort Studies ; Critical Care ; Critical Pathways ; Diagnostic Equipment ; Disease ; Diuretics ; Echocardiography ; Electrocardiography ; Emergencies ; Emergency Service, Hospital ; Equipment And Supplies ; Evaluation Studies As Topic ; Feedback ; Heart ; Heart Diseases ; Heart Failure ; Hormones ; Hospitals ; Hospitals, General ; Humans ; Hypertension ; Indicators And Reagents ; Infection ; Infections ; Inpatients ; Intensive Care Units ; Internal Medicine ; Lead ; Magnesium ; Male ; Medicine ; Myocardial Ischemia ; Natriuretic Peptide, Brain ; Natriuretic Peptides ; Nitrogen ; Overall ; Oxygen ; Partial Thromboplastin Time ; Patients ; Peptides ; Philippines ; Physicians ; Potassium ; Prothrombin ; Prothrombin Time ; Quality Of Health Care ; Referral And Consultation ; Sodium ; Statistics ; Tertiary Care Centers ; Thorax ; Thromboembolism ; Thromboplastin ; Thyroid Gland ; Time ; Troponin ; Troponin I ; Universities ; Urea ; Urinalysis ; Urine ; Venous Thromboembolism ; Vital Signs ; Work ; Workforce

OBJECTIVES: To evaluate the correlation of mean arterial oxygen tension (PaO₂) during the first 24 h following intensive care unit (ICU) admission with mortality in critically ill patients with acute kidney injury (AKI) and determine the optimal PaO₂ threshold for devising oxygen therapy strategies for these patients. METHODS: We collected the clinical data of ICU patients with AKI from the MIMIC-IV database. Based on the optimal first 24-h PaO₂ threshold determined by receiver operating characteristic (ROC) curve analysis and the Youden index maximization principle, we classified the patients into hyperoxia group (with PaO₂ ≥137.029 mmHg) and hypoxemia group (PaO₂<137.029 mm Hg). Multivariable logistic regression and propensity score matching were used to evaluate the correlation of first 24-h PaO₂ levels with in-hospital mortality of the patients. RESULTS: Among the 18 335 patients, 46.7% were in the hyperoxia group, who had an overall mortality rate of 16.9%. The optimal PaO₂ threshold (137.029 mm Hg) had a sensitivity of 78.3%, a specificity of 63.7%, and an AUC of 0.76 (95% CI: 0.74=0.78). Hyperoxia within the first 24 h after ICU admission was associated with a significantly lower in-hospital mortality (OR=0.78) and 90-day mortality (OR=0.77), particularly in stage 1 AKI patients. A non-linear relationship was identified between PaO₂ and mortality of the patients (P<0.001). Kaplan-Meier survival curves indicated a significantly increased 90-day survival rate in the patients in hyperoxia group (P<0.001), who also had shorter durations of mechanical ventilation, less vasopressor use, and shorter lengths of hospital/ICU stay. CONCLUSIONS Maintenance of a PaO₂ level ≥137.029 mmHg within 24 h after ICU admission may improve clinical outcomes of critically ill AKI patients, which underscores the importance of targeted oxygen delivery in ICU care.
Humans ; Acute Kidney Injury/blood* ; Male ; Female ; Middle Aged ; Intensive Care Units ; Aged ; Oxygen/blood* ; Hospital Mortality ; Partial Pressure ; Adult ; Databases, Factual

OBJECTIVES: To investigate the association of serum albumin level after human albumin infusion with 28-day mortality in critically ill patients with acute kidney injury (AKI) and its impact on 90-day outcomes of the patients. METHODS: We conducted a retrospective cohort study based on the MIMIC IV database (2008-2019), including 5918 AKI patients treated with albumin in the ICU. Based on serum albumin levels within 72 h after albumin infusion, the patients were divided into low (<30 g/L), medium (30-35 g/L), and high albumin (>35 g/L) groups. Restricted cubic spline regression and multivariate logistic regression were used to analyze the association of albumin levels with patient mortality, and the results were verified in a external validation cohort consisting of 110 sepsis-induced AKI patients treated in Nanfang Hospital between 2017 and 2022 using survival analysis and multivariate adjustment. RESULTS: In the MIMIC training cohort, multivariate logistic regression showed no significant differences in 28-day mortality of the patients with different albumin levels (P>0.05). However, restricted cubic spline analysis indicated a non-linear dose-response relationship between albumin levels and 28-day mortality (threshold effect: risk increased when albumin levels >3.6 g/dL). Secondary endpoint analysis revealed that the patients with high albumin levels had a shorter duration of mechanical ventilation (P<0.001) but a longer ICU stay (P<0.001). In the validation cohort, albumin levels ≥30 g/L were significantly associated with a reduced 28-day mortality rate (P<0.05). CONCLUSIONS The association between increased serum albumin levels following albumin infusion and 28-day mortality of critically ill patients with AKI exhibits a cohort dependency and can be influenced by multiple factors including disease type and severity, infusion strategies, and statistical methods.
Humans ; Acute Kidney Injury/therapy* ; Critical Illness/mortality* ; Retrospective Studies ; Serum Albumin/analysis* ; Male ; Female ; Intensive Care Units ; Middle Aged ; Logistic Models ; Aged

BACKGROUND: Hospitalization in neonatal intensive care units (NICU) exposes preterm infants to adverse stimuli, including continuous 24-hour lighting. There is currently no standardized NICU layout advised for the best development of preterm neonates. This meta-analysis aimed to assess the impact of cycled light (CL) exposure on clinical outcomes in premature infants admitted to NICU as synthesized in previous studies. MATERIALS AND METHODS: This meta-analysis protocol was developed following the preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) statement. A search was performed in PubMed/MEDLINE, EMBASE, Scopus, and Cochrane databases using the MeSH/key words: ―light exposure‖ AND pre-term AND cycled AND (RCT OR trials OR ―randomized controlled trial). The pooled Mean Difference with corresponding 95% CI was computed for weight gain, duration until start of enteral feeding, and duration of ICU stay using the Mantel–Haenszel random-effect model. RESULTS: Nine studies were included. The pooled mean difference showed that among preterm infants who had cycled light exposure, average daily weight gain (MD=6.24 grams, 95%CI=1.36 to 11.13, p=0.01) was significantly higher than those with continuous light exposure. The average time to start enteral feeding (MD=-3.84 days, 95%CI=-7.56 to -0.13, p=0.04) and average ICU stay (MD=-8.43 days, 95%CI=-12.54 to -4.31, p<0.0001) among neonates who had cycled light exposure were significantly shorter. CONCLUSION Benefits were seen in preterm infants when exposed to cycled light as opposed to continuous light. CL exposed infants showed a daily weight gain that was 6.24 grams higher, on average, and began enteral feeding nearly 4 days sooner. It led to a decrease in the duration of ICU stay by around 8 to 9 days on average. Further trials to determine the impact of cycled light exposure on morbidity and mortality among preterm neonates is recommended.
Human ; Male,Female ; Systematic review ; Meta-analysis ; Infant, Premature ; Intensive care units, Neonatal ; Intensive care, Neonatal ; Light ; Lighting ; Critical care

Humans ; Milk, Human ; Milk Banks/standards* ; Intensive Care Units, Neonatal ; Infant, Newborn ; China ; Consensus

The intensive care unit (ICU) is a highly equipment-intensive area with a wide variety of medical devices, and the accuracy and timeliness of medical equipment data collection are highly demanded. The integration of the Internet of Things (IoT) into ICU medical devices is of great significance for enhancing the quality of medical care and nursing, as well as for the advancement of digital and intelligent ICUs. This study focuses on the construction of the IOT for ICU medical devices and proposes innovative solutions, including the overall architecture design, devices connection, data collection, data standardization, platform construction and application implementation. The overall architecture was designed according to the perception layer, network layer, platform layer and application layer; three modes of device connection and data acquisition were proposed; data standardization based on Integrating the Healthcare Enterprise-Patient Care Device (IHE-PCD) was proposed. This study was practically verified in the Chinese People's Liberation Army General Hospital, a total of 122 devices in four ICU wards were connected to the IoT, storing 21.76 billion data items, with a data volume of 12.5 TB, which solved the problem of difficult systematic medical equipment data collection and data integration in ICUs. The remarkable results achieved proved the feasibility and reliability of this study. The research results of this paper provide a solution reference for the construction of hospital ICU IoT, offer more abundant data for medical big data analysis research, which can support the improvement of ICU medical services and promote the development of ICU to digitalization and intelligence.
Intensive Care Units ; Internet of Things ; Humans ; Internet ; Data Collection

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

PURPOSE: To compare the efficacy of continuous renal replacement therapy (CRRT) using either oXiris or conventional hemopurification filters in the treatment of intra-abdominal sepsis. METHODS: We conducted a retrospective analysis of septic patients with severe intra-abdominal infections admitted to our hospital from October 2019 to August 2023. Patients who meet the criteria for intra-abdominal sepsis based on medical history, symptoms, physical examination, and laboratory/imaging findings were included. EXCLUSION CRITERIA: pregnancy, terminal malignancy, prior CRRT before intensive care unit admission, pre-existing liver or renal failure. Heart rate (HR), mean arterial pressure, oxygenation index, lactic acid level (Lac), platelet count (PLT), neutrophil percentage, serum levels of procalcitonin, C-reactive protein, interleukin (IL)-6, norepinephrine dosage, acute physiology and chronic health evaluation II (APACHE II), and sequential organ failure assessment (SOFA) scores before and after 24 h and 72 h of treatment, as well as ventilator use time, hemopurification treatment time, intensive care unit and hospital lengths of stay, and 14-day and 28-day mortality were compared between patients receiving CRRT using either oXiris or conventional hemofiltration. Statistical analysis was performed using SPSS Statistics 26.0 software, including the construction of predictive models via logistic regression equations and repeated measures ANOVA. RESULTS: Baseline values including time to antibiotic administration, time to source control, and time to initiation of CRRT were similar between the 2 groups (all p>0.05). Patients receiving conventional CRRT exhibited significant changes in HR but of none of the other indexes at the 24 h and 72 h time points (p=0.041, p=0.026, respectively). The oXiris group showed significant improvements in HR, Lac, IL-6, and APACHE II score 24 h after treatment (p<0.05); after 72 h, all indexes were improved except PLT (all p<0.05). Intergroup comparison disclosed significant differences in HR, Lac, norepinephrine dose, APACHE II, SOFA, neutrophil percentage, and IL-6 after 24 h of treatment (p<0.05). Mean arterial pressure, serum levels of procalcitonin, C-reactive protein, SOFA score, and norepinephrine dosage were similar between the 2 groups at 24 h (p>0.05). Except for HR, oxygenation index, and PLT, post-treatment change rates of △ (%) were significantly greater in the oXiris group (p < 0.05). Duration of ventilator use, CRRT time, and intensive care unit and hospital lengths of stay were similar between the 2 groups (p>0.05). The 14-day mortality rates of the 2 groups were similar (p=0.091). After excluding patients whose CRRT was interrupted, 28-day mortality was significantly lower in the oXiris than in the conventional group (25.0% vs. 54.2%; p=0.050). The 28-day mortality rate increased by 9.6% for each additional hour required for source control and by 21.3% for each 1-point increase in APACHE II score. CONCLUSIONS In severe abdominal infections, the oXiris filter may have advantages over conventional CRRT, which may provide an alternative to clinical treatment. Meanwhile, early active infection source control may reduce the case mortality rate of patients with severe abdominal infections.
Humans ; Retrospective Studies ; Female ; Male ; Middle Aged ; Sepsis/mortality* ; Aged ; Adult ; Continuous Renal Replacement Therapy/methods* ; Intraabdominal Infections/mortality* ; APACHE ; Organ Dysfunction Scores ; Intensive Care Units ; Treatment Outcome

The intelligent oxygen management system is a software designed with various algorithms to automatically titrate inhaled oxygen concentration according to specific patterns. This system can be integrated into various ventilator devices and used during assisted ventilation processes, aiming to maintain the patient's blood oxygen saturation within a target range. This paper employs a scoping review methodology, focusing on research related to intelligent oxygen management systems in neonatal intensive care units. It reviews the fundamental principles, application platforms, and clinical outcomes of these systems, providing a theoretical basis for clinical implementation.
Humans ; Intensive Care Units, Neonatal ; Infant, Newborn ; Oxygen/administration & dosage* ; Oxygen Inhalation Therapy/methods* ; Respiration, Artificial