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

Critical care emphasizes critical thinking, focuses on the triggers that lead to disease progression, and attaches great importance to early diagnosis of diseases and assessment of the compensatory capacity of vital organs. Pregnancy-associated atypical hemolytic uremic syndrome (P-aHUS) is relatively rare in the intensive care unit (ICU). Most cases occur within 10 weeks after delivery. Severe cases can be life-threatening. It characterized by microangiopathic hemolytic anemia, decreased platelet count (PLT), and acute kidney injury (AKI). Early clinical diagnosis is difficult due to its similarity to various disease manifestations. On January 28, 2024, a 26-year-old pregnant woman at 26⁺³ weeks gestation was transferred to the ICU 19 hours post-vaginal delivery due to abdominal pain, reduced urine output, decreased PLT, elevated D-dimer, tachycardia, increased respiratory rate and declined oxygenation. On the day of ICU admission, the critical care physician identified the causes that triggered the acute respiratory and circulatory events based on the "holistic and local" critical care thinking. The condition was stabilized rapidly by improving the capacity overload. In terms of etiological diagnosis, under the guidance of the "point and face" critical care thinking, starting from abnormality indicators including a decrease in hemoglobin (Hb) and PLT and elevated D-dimer and fibrin degradation product (FDP) without other abnormal coagulation indicators, the critical care physician ultimately determined the diagnosis direction of thrombotic microangiopathy (TMA) by delving deeply into the essence of the disease and formulating a laboratory examination plan in a reasonable and orderly manner. In terms of in-depth diagnosis, combining the disease development process, family history, and past history, applying the two-way falsification thinking of "forward and reverse" as well as "questioning and hypothesis", the diagnosis possibilities of preeclampsia, HELLP syndrome [including hemolysis (H), elevated liver function (EL) and low platelet count (LP)], thrombotic thrombocytopenic purpura (TTP), typical hemolytic uremic syndrome (HUS), and autoimmune inflammatory diseases inducing the condition was ruled out. The diagnosis of complement activation-induced P-aHUS was finally established for the patient, according to the positive result of the complement factor H (CFH). Active decision was made in the initial treatment. The plasma exchange was initiated early. "Small goals" were formulated in stages. The "small endpoints" were dynamically controlled in a goal-oriented manner to achieve continuous realization of the overall treatment effect through phased "small goals". On the 5th day of ICU treatment, the trend of microthrombosis in the patient was controlled, organ function damage was improved, and the patient was transferred out of the ICU. It is possible to reach a favorable clinical outcome for critically ill patients by applying a critical care mindset to quickly integrate diagnostic and therapeutic strategies, accurately identifying the triggers and causes that led to the progression of the disease, and using critical care medical techniques for early and effective intervention.
Humans ; Female ; Pregnancy ; Adult ; Atypical Hemolytic Uremic Syndrome/therapy* ; Intensive Care Units ; Pregnancy Complications, Hematologic/therapy* ; Critical Care

OBJECTIVE: To design a portable respiratory device for transporting premature infants and explore its application effect in the in-hospital transportation of extremely premature infants in primary hospitals. METHODS: A prospective randomized controlled trial was conducted. The extremely premature infants born and transferred to neonatal intensive care unit (NICU) with oxygen therapy support from May to October in 2023 were selected and randomly divided into control group and observation group. The infants in the control group received respiratory support and in-hospital transportation using a traditional T-combination resuscitator connected to pure oxygen, and those in the observation group used a portable premature infant transport respiratory device designed and manufactured by medical staff to provide respiratory support and implement in-hospital transportation. The respiratory device for transporting premature infants is made of 304 stainless steel material, mainly consisting of a T-combination resuscitator, an air oxygen mixer, an air tank, a pure oxygen cylinder, a pressure reducing valve, a telescopic rod, a tray, a hook, a bottom plate, and four moving wheels, which can achieve precise control of the fraction of inspired oxygen (FiO₂) during transportation. The achievement rate of first-time target pulse oxygen saturation (SpO₂, achieving a target SpO₂ of 0.90-0.95 was considered as meeting the standard) and arterial partial pressure of oxygen (PaO₂) after being transferred to the NICU, as well as the manpower expenditure and time required for transportation of pediatric patients between the two groups were observed. RESULTS: A total of 73 extremely premature infants were enrolled, including 38 in the control group and 35 in the observation group. There was no significant difference in the gender, gestational age at birth, birth weight, mode of delivery, Apgar score at 1 minute and 5 minutes after birth, and oxygen therapy during the transportation between the two groups. The achievement rate of first-time target SpO₂ after NICU in the observation group was significantly higher than that in the control group [94.29% (33/35) vs. 26.32% (10/38), P < 0.05], the PaO₂ control range was better [mmHg (1 mmHg = 0.133 kPa): 85.50±6.36 vs. 103.00±2.83, P < 0.05], manpower expenditure and time required for transportation were significantly reduced [manpower expenditure (number): 2.14±0.35 vs. 3.17±0.34, time required for transportation (minutes): 10.42±0.76 vs. 15.54±0.34, both P < 0.05]. CONCLUSIONS The portable respiratory device for transporting premature infants is used for respiratory support during the transportation of extremely premature infants in primary hospitals. It can improve the achievement rate of target SpO₂, control PaO₂ within the target range, and avoid hypoxia or hyperoxia during transportation. The breathing apparatus is compact, easy to carry, can save labor resources and time during transport, is cost-effective, and is suitable for widespread application in primary hospitals.
Humans ; Infant, Newborn ; Transportation of Patients ; Prospective Studies ; Equipment Design ; Infant, Extremely Premature ; Intensive Care Units, Neonatal ; Infant, Premature

OBJECTIVE: To develop and validate a nomogram model for predicting 30-day mortality among elderly patients with sepsis-associated liver dysfunction (SALD), to identify high-risk patients and improve prognosis. METHODS: A retrospective cohort study was conducted using data extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database for elderly patients with SALD who were first admitted to the intensive care unit (ICU) of Beth Israel Deaconess Medical Center between 2008 and 2019, including basic characteristics, severity scores, underlying diseases, infection foci, 24-hour vital signs, initial laboratory indicators, 24-hour complications, and prognosis related indicators. Patients were randomly assigned to training group and validation group in a ratio of 7 : 3. The training group used the LASSO regression analysis, as well as multivariate Logistic regression analysis to screen for independent risk factors for 30-day mortality. A nomogram prediction model was constructed, and receiver operator characteristic curve (ROC curve), calibration curves, and decision curve analysis (DCA) were used to evaluate the model, and validate the model using the validation cohort. RESULTS: A total of 630 elderly patients with SLAD were included in the study, including 441 in the training group and 189 in the validation group. Oxford acute severity of illness score (OASIS) for training group [odds ratio (OR) = 1.060, 95% confidence interval (95%CI) was 1.034-1.086], 24-hour pulse oxygen saturation (SpO₂; OR = 0.876, 95%CI was 0.797-0.962), initial mean corpuscular volume (MCV; OR = 1.043, 95%CI was 1.009-1.077), initial red blood cell distribution width (RDW; OR = 1.237, 95%CI was 1.123-1.362), initial blood glucose (OR = 1.008, 95%CI was 1.004-1.013), and initial aspartate aminotransferase (AST; OR = 1.000, 95%CI was 1.000-1.001) were independent risk factors for 30-day mortality in patients (all P < 0.05). Based on the above variables, a nomogram model was constructed, and the ROC curve showed that the area under the curve (AUC) of the model in the training group was 0.757 (95%CI was 0.712-0.803), with a sensitivity of 65.05% and a specificity of 74.90%; the AUC of the model in the validation group was 0.712 (95%CI was 0.631-0.792), with a sensitivity of 58.67% and a specificity of 81.58%. The calibration curves of the training and validation groups show that both the fitted curves were close to the standard curves. The Hosmer-Lemeshow test: the training group (χ ² = 6.729, P = 0.566), the validation group (χ ² = 13.889, P = 0.085), indicating that the model can fit the observed data well. The DCA curve shows that when the threshold probability of the training group was 16% to 94% and the threshold probability of the validation group was 27% to 99%, the net benefit of the model was good. CONCLUSIONS OASIS, 24-hour SpO₂, initial MCV, initial RDW, initial blood glucose and initial AST are independent risk factors for 30-day mortality in elderly patients with SALD. The nomogram based on these six variables demonstrates good predictive performance.
Humans ; Sepsis/complications* ; Retrospective Studies ; Nomograms ; Aged ; Prognosis ; Risk Factors ; Liver Diseases/mortality* ; Intensive Care Units ; ROC Curve ; Male ; Female ; Logistic Models

OBJECTIVE: To investigate the potential mechanisms of sepsis pathogenesis in intensive care unit (ICU), with a specific focus on the role of skin microbiota, and to evaluate the causal relationships between skin microbiota and ICU sepsis using Mendelian randomization (MR). METHODS: A two-sample MR analysis was performed using skin microbiota genome-wide association study (GWAS) summary data from German population cohorts as exposures, combined with ICU sepsis susceptibility and 28-day mortality GWAS summary data from the IEU OpenGWAS database as outcomes. The primary causal effect estimates were generated using the inverse variance weighted (IVW) method, supplemented by validation through MR-Egger and weighted median approaches. Heterogeneity and pleiotropy tests, along with sensitivity analyses, were conducted to evaluate the robustness of the results. RESULTS: Regarding risk of ICU sepsis, IVW analysis showed that order Pseudomonadales [odds ratio (OR) = 0.93, 95% confidence interval (95%CI) was 0.88-0.98], family Flavobacteriaceae (OR = 0.93, 95%CI was 0.90-0.96), and genus Acinetobacter (OR = 0.96, 95%CI was 0.93-0.99) were significantly negatively correlated with the risk of ICU sepsis (all P < 0.05). There was a significant positive correlation between the risk of ICU sepsis and the presence of β-Proteobacteria (OR = 1.05, 95%CI was 1.00-1.11) and Actinobacteria (OR = 1.05, 95%CI was 1.00-1.11), both P < 0.05. Regarding 28-day mortality of ICU sepsis, IVW analysis showed that phylum Bacteroidetes (OR = 0.92, 95%CI was 0.86-0.99), family Streptococcaceae (OR = 0.92, 95%CI was 0.85-0.98), family Flavobacteriaceae (OR = 0.90, 95%CI was 0.83-0.97), genus Streptococcus (OR = 0.92, 95%CI was 0.86-0.99), ASV016 [Enhydrobacter] (OR = 0.92, 95%CI was 0.87-0.98), and ASV042 [Acinetobacter] (OR = 0.92, 95%CI was 0.88-0.97) were significantly negatively correlated with the 28-day mortality of ICU sepsis (all P < 0.05); family Moraxellaceae (OR = 1.09, 95%CI was 1.00-1.18) and ASV008 [Staphylococcus] (OR = 1.08, 95%CI was 1.03-1.14) was significantly positively correlated with the 28-day mortality of ICU sepsis (both P < 0.05). Sensitivity analysis and MR-PRESSO showed no heterogeneity, pleiotropy, or horizontal pleiotropy between skin microbiota and ICU sepsis risk and 28-day mortality rate. Analysis of confounding factors showed that single nucleotide polymorphisms (SNPs) associated with relevant skin bacteria could independently and causally affect the risk of ICU sepsis or ICU sepsis related mortality rate, independent of other confounding factors. The Steiger test results indicated that the established causal relationship was not due to reverse causality. CONCLUSIONS Skin microbiota composition may influence both sepsis susceptibility and 28-day mortality in ICU settings. Family Flavobacteriaceae demonstrated protective effects against sepsis onset and mortality. These findings provide new perspectives for early detection and management strategies.
Humans ; Sepsis/mortality* ; Intensive Care Units ; Mendelian Randomization Analysis ; Microbiota ; Skin/microbiology* ; Genome-Wide Association Study ; Risk Factors ; Skin Microbiome

OBJECTIVE: To assess the relationship between blood pressure reactivity index (BPRI) and in-hospital mortality risk in patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: A retrospective cohort study was conducted to collect data from patients admitted to the intensive care unit (ICU) and clinically diagnosed with SA-AKI between 2008 and 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database in the United States. The collected data included demographic characteristics, comorbidities, vital signs, laboratory parameters, sequential organ failure assessment (SOFA) and simplified acute physiology scoreII(SAPSII) within 48 hours of SA-AKI diagnosis, stages of AKI, treatment regimens, mean BPRI during the first and second 24 hours (BPRI_0_24, BPRI_24_48), and outcome measures including primary outcome (in-hospital mortality) and secondary outcomes (ICU length of stay and total hospital length of stay). Variables with statistical significance in univariate analysis were included in LASSO regression analysis for variable selection, and the selected variables were subsequently incorporated into multivariate Logistic regression analysis to identify independent predictors associated with in-hospital mortality in SA-AKI patients. Restricted cubic spline (RCS) analysis was employed to examine whether there was a linear relationship between BPRI within 48 hours and in-hospital mortality in SA-AKI patients. Basic prediction models were constructed based on the independent predictors identified through multivariate Logistic regression analysis, and receiver operator characteristic curve (ROC curve) was plotted to evaluate the predictive performance of each basic prediction model before and after incorporating BPRI. RESULTS: A total of 3 517 SA-AKI patients admitted to the ICU were included, of whom 826 died during hospitalization and 2 691 survived. The BPRI values within 48 hours of SA-AKI diagnosis were significantly lower in the death group compared with the survival group [BPRI_0_24: 4.53 (1.81, 8.11) vs. 17.39 (5.16, 52.43); BPRI_24_48: 4.76 (2.42, 12.44) vs. 32.23 (8.85, 85.52), all P < 0.05]. LASSO regression analysis identified 20 variables with non-zero coefficients that were included in the multivariate Logistic regression analysis. The results showed that respiratory rate, temperature, pulse oxygen saturation (SpO₂), white blood cell count (WBC), hematocrit (HCT), activated partial thromboplastin time (APTT), lactate, oxygenation index, SOFA score, fluid balance (FB), BPRI_0_24, and BPRI_24_48 were all independent predictors for in-hospital mortality in SA-AKI patients (all P < 0.05). RCS analysis revealed that both BPRI showed "L"-shaped non-linear relationships with the risk of in-hospital mortality in SA-AKI patients. When BPRI_0_24 ≤ 14.47 or BPRI_24_48 ≤ 24.21, the risk of in-hospital mortality in SA-AKI increased as BPRI values decreased. Three basic prediction models were constructed based on the identified independent predictors: Model 1 (physiological indicator model) included respiratory rate, temperature, SpO₂, and oxygenation index; Model 2 (laboratory indicator model) included WBC, HCT, APTT, and lactate; Model 3 (scoring indicator model) included SOFA score and FB. ROC curve analysis showed that the predictive performance of the basic models ranked from high to low as follows: Model 3, Model 2, and Model 1, with area under the curve (AUC) values of 0.755, 0.661, and 0.655, respectively. The incorporation of BPRI indicators resulted in significant improvement in the discriminative ability of each model (all P < 0.05), with AUC values increasing to 0.832 for Model 3+BPRI, 0.805 for Model 2+BPRI, and 0.808 for Model 1+BPRI. CONCLUSIONS BPRI is an independent predictor factor for in-hospital mortality in SA-AKI patients. Incorporating BPRI into the prediction model for in-hospital mortality risk in SA-AKI can significantly improve its predictive capability.
Humans ; Acute Kidney Injury/mortality* ; Sepsis/complications* ; Retrospective Studies ; Hospital Mortality ; Prognosis ; Blood Pressure ; Intensive Care Units ; Male ; Female ; Length of Stay ; Middle Aged ; Aged ; Adult ; Logistic Models

OBJECTIVE: To construct a longitudinal trajectory model of arterial oxygen tension (PaO₂) within 24 hours after cardiac arrest (CA). METHODS: A retrospective cohort study was conducted. CA patients admitted to the ICU from 2014 to 2015 were selected from the eICU Collaborative Research Database (eICU-CRD). Data about patients' demographic characteristics, history of comorbidities, laboratory test indicators within 24 hours of intensive care unit (ICU) admission [including all PaO₂ data and arterial carbon dioxide tension (PaCO₂)], vasopressor use, and clinical outcomes were extracted from the database. The primary outcome variable was all-cause in-hospital mortality. Group-based trajectory model (GBTM) were built based on the changes in PaO₂ within 24 hours of ICU admission, and patients were grouped according to their initial static PaO₂ values upon ICU admission. Multivariable adjusted Poisson regression analysis was used to compare the in-hospital mortality risk among patients in different PaO₂ dynamic trajectory groups. Sensitivity analyses were performed using multivariable logistic regression and multivariable adjusted Poisson regression without imputation of missing values. RESULTS: A total of 3 866 CA patients were included. Three GBTM trajectory groups were identified based on PaO₂ changes within 24 hours of ICU admission: Group-1 (low level first increased then decreased, 148 cases), Group-2 (sustained low level, 3 040 cases), and Group-3 (first high level then decreased, 678 cases). Significant differences were found among the three groups in age, body weight, maximum serum potassium, maximum PaCO₂, minimum hemoglobin (Hb), vasopressor use, total hospitalization time, ICU stay, and hospital mortality. After incorporating variables with significant differences into the multivariable adjusted Poisson regression model, results showed that compared to Group-2 patients, patients in Group-1 and Group-3 had an increased risk of all-cause in-hospital mortality [Group-1 adjusted relative risk (aRR) = 1.20, 95% confidence interval (95%CI) was 1.02-1.41; Group-3 aRR = 1.11, 95%CI was 1.01-1.24]. Based on initial static PaO₂ values at ICU admission, patients were divided into four groups: PaO₂ < 100 mmHg (1 mmHg = 0.133 kPa; 1 217 cases), PaO₂ 100-200 mmHg (569 cases), PaO₂ 201-300 mmHg (547 cases), and PaO₂ > 300 mmHg (1 082 cases). Multivariable adjusted Poisson regression analysis indicated a significant upward trend in aRR for the latter three groups compared to the PaO₂ < 100 mmHg group. Sensitivity analyses revealed that compared to Group-2, patients in Group-1 and Group-3 had a significantly increased risk of all-cause in-hospital mortality (both P < 0.05). CONCLUSIONS Within 24 hours after return of spontaneous circulation in CA patients, PaO₂ exhibits different dynamic trajectories, and patients with hyperoxia have an increased risk of in-hospital mortality.
Humans ; Retrospective Studies ; Hospital Mortality ; Heart Arrest/blood* ; Prognosis ; Oxygen/blood* ; Intensive Care Units ; Cardiopulmonary Resuscitation ; Male ; Female ; Middle Aged

OBJECTIVE: To construct and validate a prognostic prediction model for children with sepsis using the Phoenix sepsis score (PSS). METHODS: A retrospective case series study was conducted to collect clinical data of children with sepsis admitted to the pediatric intensive care unit (PICU) of the Affiliated Hospital of Guizhou Medical University from January 2022 to April 2024. The data included general information, the worst values of laboratory indicators within the first 24 hours of PICU admission, PSS score, pediatric critical illness score (PCIS), and the survival status of the children within 30 days of admission. The statistically significant indicators in univariate Logistic regression analysis were included in multivariate Logistic regression analysis to screen the risk factors affecting the prognosis of children with sepsis and construct a nomogram model. The receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive performance of the model. The Bootstrap method was used to perform 1 000 repeated sampling internal verification and draw the calibration curve of the model. RESULTS: A total of 199 children with sepsis were included, of which 32 died and 167 survived 30 days after admission. In the univariate Logistic regression analysis, shock, white blood cell count (WBC), international normalized ratio (INR), lactic acid (Lac), PSS score, and PCIS score were identified as statistically significant predictors. These variables were then included in the multivariate Logistic regression analysis, which demonstrated that shock [odds ratio (OR) = 4.258, 95% confidence interval (95%CI) was 1.049-17.288], WBC (OR = 1.124, 95%CI was 1.052-1.210), and PSS score (OR = 1.977, 95%CI was 1.298-3.012) were independent risk factors for mortality in pediatric patients with sepsis (all P < 0.05). A nomogram model was constructed based on these three risk factors, with the model equation as follows: -4.809+1.449×shock+0.682×PSS score+0.117×WBC. The calibration curve results showed that the model's predictions were highly consistent with the actual observations. The ROC curve showed that when the Youden index of the prediction model was 0.792, the sensitivity and specificity were 90.6% and 88.6%, respectively, and the area under the curve (AUC) was 0.957 (95%CI was 0.930-0.984), which was higher than the AUC of shock, WBC, and PSS score alone (0.808, 0.667, 0.908, respectively). CONCLUSIONS Shock, WBC, and PSS score have demonstrated certain predictive value for mortality in children with sepsis. The nomogram model based on the above indicators has important clinical significance for evaluating the prognosis and guiding treatment of children with sepsis.
Humans ; Sepsis/diagnosis* ; Prognosis ; Retrospective Studies ; Logistic Models ; Intensive Care Units, Pediatric ; Nomograms ; Child ; ROC Curve ; Risk Factors ; Male ; Female ; Child, Preschool ; Infant

OBJECTIVE: To investigate the current status of early pain and agitation management in critically ill patients in Guizhou Province. METHODS: A retrospective study was performed using data collected from a quality control activity conducted between April and June 2021 in non-provincial public hospitals with general intensive care unit (ICU) in Guizhou Province. Hospital-level data included hospital name and grade, ICU staffing, and number of ICU beds. Patient-level data included characteristics of patients treated in the general ICU on the day of the survey (e.g., age, sex, primary diagnosis), as well as pain and agitation assessments and the types of analgesic and sedative medications administered within 24 hours of ICU admission. RESULTS: A total of 947 critically ill ICU patients from 145 hospitals were included, among which 104 were secondary-level hospitals and 41 were tertiary-level hospitals. Within 24 hours of ICU admission, 312 (32.9%) critically ill patients received pain assessments, and 277 (29.3%) received agitation assessments. Among the pain assessment tools, the critical care pain observation tool (CPOT) was used in 44.2% (138/312) of critically ill ICU patients, with a significantly higher usage rate in tertiary hospitals compared to secondary hospitals [52.3% (69/132) vs. 38.3% (69/180), P < 0.05]. The Richmond agitation-sedation scale (RASS) was used in 93.8% (260/277) of critically ill ICU patients for agitation assessment, with no significant difference between hospital levels. Among the 947 critically ill patients, 592 (62.5%) received intravenous analgesics within 24 hours, with remifentanil being the most commonly used [42.9% (254/592)]; 510 (53.9%) received intravenous sedatives, with midazolam being the most frequently used [60.8% (310/510)]. Mechanical ventilation data were available for 932 critically ill patients, of whom 579 (62.1%) received mechanical ventilation and 353 (37.9%) did not. Compared with non-ventilated patients, ventilated patients had significantly higher rates of analgesic and sedative use [analgesics: 77.9% (451/579) vs. 38.8% (137/353); sedatives: 71.8% (416/579) vs. 25.8% (91/353); both P < 0.05]. In terms of analgesic selection, ventilated patients were more likely to receive strong opioids than non-ventilated patients [85.8% (95/137) vs. 69.3% (387/451), P < 0.05]. For sedatives, ventilated patients preferred midazolam [66.6% (277/416)], whereas non-ventilated patients more often received dexmedetomidine [45.1 (41/91)]. Blood pressure within 24 hours of ICU admission were available for 822 critically ill patients, of whom 245 (29.8%) had hypotension and 577 (70.2%) did not. Compared with non-hypotensive patients, hypotensive patients had significantly higher rates of analgesic and sedative use [analgesics: 74.7% (183/245) vs. 59.8% (345/577); sedatives: 65.7% (161/245) vs. 51.3% (296/577); both P < 0.05], but there was no significant difference in the choice of analgesic or sedative agents between the two groups. CONCLUSIONS The proportion of critically ill ICU patients in Guizhou Province who received standardized pain and agitation assessments was relatively low. The most commonly used assessment tools were CPOT and RASS, while remifentanil and midazolam were the most frequently used analgesic and sedative agents, respectively. Secondary-level hospitals had a lower rate of using standardized pain assessment tools compared to tertiary-level hospitals. Mechanical ventilation and hypotension were associated with the use of analgesic and sedative medications.
Humans ; Critical Illness ; Intensive Care Units ; Analgesics/therapeutic use* ; Hypnotics and Sedatives/therapeutic use* ; Retrospective Studies ; China ; Pain Measurement ; Pain Management ; Female ; Male ; Critical Care ; Middle Aged