Traumatic brain injury (TBI) is a critical cause of disability and death worldwide. Many studies have been conducted aimed at achieving favorable neurologic outcomes by reducing secondary brain injury in TBI patients. However, ground-breaking outcomes are still insufficient so far. Because mild-to-moderate hypothermia (32°C–35°C) has been confirmed to help neurological recovery for recovered patients after circulatory arrest, it has been recognized as a major neuroprotective treatment plan for TBI patients. Thereafter, many clinical studies about the effect of therapeutic hypothermia (TH) on severe TBI have been conducted. However, efficacy and safety have not been demonstrated in many large-scale randomized controlled studies. Rather, some studies have demonstrated an increase in mortality rate due to complications such as pneumonia, so it is not highly recommended for severe TBI patients. Recently, some studies have shown results suggesting TH may help reperfusion/ischemic injury prevention after surgery in the case of mass lesions, such as acute subdural hematoma, and it has also been shown to be effective in intracranial pressure control. In conclusion, TH is still at the center of neuroprotective therapeutic studies regarding TBI. If proper measures can be taken to mitigate the many adverse events that may occur during the course of treatment, more positive efficacy can be confirmed. In this review, we look into adverse events that may occur during the process of the induction, maintenance, and rewarming of targeted temperature management and consider ways to prevent and address them.
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Acute Crit Care. 2022;37(4):491-501. Published online November 30, 2022
Invasive mechanical ventilation is a frequent therapy in critically ill patients in critical care units. To achieve favorable outcomes, patient and ventilator interaction must be adequate. However, many clinical situations could attempt against this principle and generate a mismatch between these two actors. These asynchronies can lead the patient to worst outcomes; that is why it is vital to recognize and treat these entities as soon as possible. Early detection and recognition of the different asynchronies could favor the reduction of the days of mechanical ventilation, the days of hospital stay, and intensive care and improve clinical results.
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Background Sepsis and septic shock remain the leading causes of death in critically ill patients worldwide. Various biomarkers are available to determine the prognosis and therapeutic effects of sepsis. In this study, we investigated the effectiveness of presepsin as a sepsis biomarker.
Methods Patients admitted to the intensive care unit with major or minor diagnosis of sepsis were categorized into survival and non-survival groups. The white blood cell count and serum C-reactive protein, procalcitonin, and presepsin levels were measured in all patients.
Results The study included 40 patients (survival group, 32; non-survival group, 8; mortality rate, 20%). The maximum serum presepsin levels measured during intensive care unit admission were significantly higher in the non-survival group (median [interquartile range]: 4,205.5 pg/ml [1,155.8–10,094.0] vs. 741.5 pg/ml [520.0–1,317.5], P<0.05). No statistically significant intergroup differences were observed in the maximum, minimum, and mean values of the white blood cell count, as well as serum C-reactive protein, and procalcitonin levels. Based on the receiver operating characteristic curve, the area under the curve for presepsin as a predictor of sepsis mortality was 0.764. At a cut-off value of 1,898.5 pg/ml, the sensitivity and specificity of presepsin for prediction of sepsis-induced mortality were 75.0% and 87.5%, respectively.
Conclusions Early diagnosis of sepsis and prediction of sepsis-induced mortality are important for prompt initiation of treatment. Presepsin may serve as an effective biomarker for prediction of sepsis-induced mortality and for evaluation of treatment effectiveness.
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Background Rheumatoid arthritis (RA) is associated with increased risk of sepsis and higher infection-related mortality compared to the general population. However, the evidence on the prognostic impact of RA in sepsis has been inconclusive. We aimed to estimate the population-level association of RA with short-term mortality in sepsis.
Methods We used statewide data to identify hospitalizations aged ≥18 years in Texas with sepsis, with and without RA during 2014–2017. Hierarchical logistic models with propensity adjustment (primary model), propensity score matching, and multivariable logistic regression without propensity adjustment were used to estimate the association of RA with short-term mortality among sepsis hospitalizations.
Results Among 283,025 sepsis hospitalizations, 7,689 (2.7%) had RA. Compared to sepsis hospitalizations without RA, those with RA were older (aged ≥65 years, 63.9% vs. 56.4%) and had higher burden of comorbidities (mean Deyo comorbidity index, 3.2 vs. 2.7). Short-term mortality of sepsis hospitalizations with and without RA was 26.8% vs. 31.4%. Following adjustment for confounders, short-term mortality was lower among RA patients (adjusted odds ratio [aOR], 0.910; 95% confidence interval [CI], 0.856–0.967), with similar findings on alternative models. On sensitivity analyses, short-term mortality was lower in RA patients among sepsis hospitalizations aged ≥65 years and those with septic shock, but not among those admitted to intensive care unit (ICU; aOR, 0.990; 95% CI, 0.909–1.079).
Conclusions RA was associated, unexpectedly, with lower short-term mortality in septic patients. However, this “protective” association was driven by those patients without ICU admission. Further studies are warranted to confirm these findings and to examine the underlying mechanisms.
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Background Legionella species are important causative organisms of severe pneumonia. However, data are limited on predictors of progression to severe Legionella pneumonia (LP). Therefore, the risk factors for LP progression from non-severe to the severe form were investigated in the present study.
Methods This was a retrospective cohort study that included adult LP patients admitted to a 2,700-bed referral center between January 2005 and December 2019.
Results A total of 155 patients were identified during the study period; 58 patients (37.4%) initially presented with severe pneumonia and 97 (62.6%) patients with non-severe pneumonia. Among the 97 patients, 28 (28.9%) developed severe pneumonia during hospitalization and 69 patients (71.1%) recovered without progression to severe pneumonia. Multivariate logistic regression analysis showed platelet count ≤150,000/mm3 (odds ratio [OR], 2.923; 95% confidence interval [CI], 1.100–8.105; P=0.034) and delayed antibiotic treatment >1 day (OR, 3.092; 95% CI, 1.167–8.727; P=0.026) were significant independent factors associated with progression to severe pneumonia.
Conclusions A low platelet count and delayed antibiotic treatment were significantly associated with the progression of non-severe LP to severe LP.
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Background Studies on the effects of viral coinfection on bacterial pneumonia are still scarce in South Korea. This study investigates the frequency and seasonal distribution of virus infection and its impact on the prognosis in patients with community-acquired pneumonia (CAP).
Methods The medical records of CAP patients with definite etiology, such as viruses and bacteria, were retrospectively reviewed. Their epidemiologic and clinical characteristics, microbiologic test results, the severity of illness, and 30-day mortality were analyzed.
Results Among 150 study subjects, 68 patients (45.3%) had viral infection alone, 47 (31.3%) had bacterial infection alone, and 35 (23.3%) had viral-bacterial coinfection, respectively. Among 103 patients with viral infections, Influenza A virus (44%) was the most common virus, followed by rhinovirus (19%), influenza B (13%), and adenovirus (6%). The confusion-urea-respiratory rateblood pressure-age of 65 (CURB-65) score of the viral-bacterial coinfection was higher than that of the viral infection (median [interquartile range]: 2.0 [1.0–4.0] vs. 2.0 [0.3–3.0], P=0.029). The 30-day mortality of the viral infection alone group (2.9%) was significantly lower than that of bacterial infection alone (19.1%) and viral-bacterial coinfection (25.7%) groups (Bonferroni-corrected P<0.05). Viral-bacterial coinfection was the stronger predictor of 30-day mortality in CAP (odds ratio [OR], 18.9; 95% confidence interval [CI], 3.0–118.3; P=0.002) than bacterial infection alone (OR, 6.3; 95% CI, 1.1–36.4; P=0.041), compared to viral infection alone on the multivariate analysis.
Conclusions The etiology of viral infection in CAP is different according to regional characteristics. Viral-bacterial coinfection showed a worse prognosis than bacterial infection alone in patients with CAP.
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Background Delayed intubation is associated with poor prognosis in patients with respiratory failure. However, the effect of delayed intubation in patients with idiopathic pulmonary fibrosis (IPF) remains unknown. This study aimed to analyze whether timing of intubation after high-concentration oxygen therapy was associated with worse clinical outcomes in IPF patients.
Methods This retrospective propensity score-matched study enrolled adult patients with IPF who underwent mechanical ventilation between January 2011 and July 2021. Patients were divided into early and delayed intubation groups. Delayed intubation was defined as use of high-concentration oxygen therapy for at least 48 hours before tracheal intubation. The primary outcome was intensive care unit (ICU) mortality, and a conditional logistic regression model was used to evaluate the association between timing of intubation and clinical outcomes.
Results The median duration of high-concentration oxygen therapy before intubation was 0.5 days in the early intubation group (n=60) and 5.1 days in the delayed intubation group (n=36). The ICU mortality rate was 56.7% and 75% in the early and delayed intubation groups, respectively, before propensity matching (P=0.075). After matching for demographic and clinical covariates, 33 matched pairs were selected. In the propensity-matched cohort, delayed intubation significantly increased the risk of ICU mortality (adjusted odds ratio, 3.99; 95% confidence interval, 1.02–15.63; P=0.046). However, in-hospital mortality did not differ significantly between the groups.
Conclusions In patients with IPF, delayed intubation after initiation of high-concentration oxygen therapy was significantly associated with increased risk of ICU mortality compared to early intubation.
Background There is a lack of data on extravascular lung water index (EVLWi), pulmonary vascular permeability index (PVPi), and global end-diastolic volume index (GEDVi) during prone position ventilation (PPV) in coronavirus disease 2019 (COVID-19) patients. The objectives of this study were to analyze trends in EVLWi, PVPi, and GEDVi during PPV and the relationships between these parameters and PaO2/FiO2.
Methods In this preliminary retrospective observational study, we performed transpulmonary thermodilution (TPTD) in seven mechanically ventilated COVID-19 patients without cardiac and pulmonary comorbidities requiring PPV for 18 hours, at specific times (30 minutes pre-PPV, 18 hours after PPV, and 3 hours after supination). EVLWi, PVPi and GEDVi were measured. The relationships between PaO2/FiO2 and EVLWi, and PVPi and GEDVi values, in the supine position were analyzed by linear regression. Correlation and determination coefficients were calculated.
Results EVLWi was significantly different between three time points (analysis of variance, P=0.004). After 18 hours in PPV, EVLWi was lower compared with values before PPV (12.7±0.9 ml/kg vs. 15.3±1.5 ml/kg, P=0.002). Linear regression showed that only EVLWi was correlated with PaO2/FiO2 (β =–5.757; 95% confidence interval, –10.835 to –0.679; r=–0.58; R2 =0.34; F-test P=0.029).
Conclusions EVLWi was significantly reduced after 18 hours in PPV and values measured in supine positions were correlated with PaO2/FiO2. This relationship can help clinicians discriminate whether deterioration in gas exchange is related to fluid overload or disease progression. Further clinical research should evaluate the role of TPTD parameters as markers to stratify disease severity and guide clinical management.
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Background We aimed to characterize patients hospitalized for coronavirus disease 2019 (COVID-19) and identify predictors of invasive mechanical ventilation (IMV).
Methods We performed a retrospective cohort study in patients with COVID-19 admitted to a private network in Sao Paulo, Brazil from March to October 2020. Patients were compared in three subgroups: non-intensive care unit (ICU) admission (group A), ICU admission without receiving IMV (group B) and IMV requirement (group C). We developed logistic regression algorithm to identify predictors of IMV.
Results We analyzed 1,650 patients, the median age was 53 years (42–65) and 986 patients (59.8%) were male. The median duration from symptom onset to hospital admission was 7 days (5–9) and the main comorbidities were hypertension (42.4%), diabetes (24.2%) and obesity (15.8%). We found differences among subgroups in laboratory values obtained at hospital admission. The predictors of IMV (odds ratio and 95% confidence interval [CI]) were male (1.81 [1.11– 2.94], P=0.018), age (1.03 [1.02–1.05], P<0.001), obesity (2.56 [1.57–4.15], P<0.001), duration from symptom onset to admission (0.91 [0.85–0.98], P=0.011), arterial oxygen saturation (0.95 [0.92– 0.99], P=0.012), C-reactive protein (1.005 [1.002–1.008], P<0.001), neutrophil-to-lymphocyte ratio (1.046 [1.005–1.089], P=0.029) and lactate dehydrogenase (1.005 [1.003–1.007], P<0.001). The area under the curve values were 0.860 (95% CI, 0.829–0.892) in the development cohort and 0.801 (95% CI, 0.733–0.870) in the validation cohort.
Conclusions Patients had distinct clinical and laboratory parameters early in hospital admission. Our prediction model may enable focused care in patients at high risk of IMV.
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Acute Crit Care. 2022;37(4):592-600. Published online October 27, 2022
Background Respiratory muscle strength in patients with an artificial airway is commonly assessed as the maximal inspiratory pressure (MIP) and is measured using analogue or digital manometers. Recently, new electronic loading devices have been proposed to measure respiratory muscle strength. This study evaluates the agreement between the MIPs measured by a digital manometer and those according to an electronic loading device in patients being weaned from mechanical ventilation.
Methods In this prospective study, the standard MIP was obtained using a protocol adapted from Marini, in which repetitive inspiratory efforts were performed against an occluded airway with a one-way valve and were recorded with a digital manometer for 40 seconds (MIPDM). The MIP measured using the electronic loading device (MIPELD) was obtained from repetitively tapered flow resistive inspirations sustained for at least 2 seconds during a 40-second test. The agreement between the results was verified by a Bland-Altman analysis.
Results A total of 39 subjects (17 men, 55.4±17.7 years) was enrolled. Although a strong correlation between MIPDM and MIPELD (R=0.73, P<0.001) was observed, the Bland-Altman analysis showed a high bias of –47.4 (standard deviation, 22.3 cm H2O; 95% confidence interval, –54.7 to –40.2 cm H2O).
Conclusions The protocol of repetitively tapering flow resistive inspirations to measure the MIP with the electronic loading device is not in agreement with the standard protocol using one-way valve inspiratory occlusion when applied in poorly cooperative patients being weaned from mechanical ventilation.
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Background The inflammatory response that occurs following cardiac arrest can determine the long-term prognosis of patients who survive out-of-hospital cardiac arrest. We evaluated the correlation between C-reactive protein-to-albumin ratio (CAR) following cardiac arrest and long-term mortality.
Methods The current retrospective observational study examined patients with post-cardiac arrest syndrome (PCAS) treated with targeted temperature management at a single tertiary care hospital. We measured CAR at four time points (at admission and then 24 hours, 48 hours, and 72 hours after) following cardiac arrest. The primary outcome was the patients’ 6-month mortality. We performed multivariable and area under the receiver operating characteristic curve (AUC) analyses to investigate the relationship between CAR and 6-month mortality.
Results Among the 115 patients, 52 (44.1%) died within 6 months. In the multivariable analysis, CAR at 48 hours (odds ratio [OR], 1.130; 95% confidence interval [CI], 1.027–1.244) and 72 hours (OR, 1.241; 95% CI, 1.059–1.455) after cardiac arrest was independently associated with 6-month mortality. The AUCs of CAR at admission and 24, 48, and 72 hours after cardiac arrest for predicting 6-month mortality were 0.583 (95% CI, 0.489–0.673), 0.622 (95% CI, 0.528–0.710), 0.706 (95% CI, 0.615–0.786), and 0.762 (95% CI, 0.675–0.835), respectively.
Conclusions CAR at 72 hours after cardiac arrest was an independent predictor for long-term mortality in patients with PCAS.
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Background A proper nutritional plan for resuscitated patients is important in intensive care; however, specific nutritional guidelines have not yet been established. This study aimed to determine the incidence of diet-related complications that were affected by the timing of enteral nutrition in resuscitated patients after cardiac arrest.
Methods This retrospective and 1:1 propensity score matching study involved patients who recovered after nontraumatic, out-of-hospital cardiac arrest at a tertiary hospital. Patients were divided into an early nutrition support (ENS) group and a delayed nutrition support (DNS) group according to the nutritional support time within 48 hours after admission. The incidence of major clinical complications was compared between the groups.
Results A total of 46 patients (ENS: 23, DNS: 23) were enrolled in the study. There were no differences in body mass index, comorbidity, and time of cardiopulmonary resuscitation between the two groups. There were 9 patients (ENS: 4, DNS: 5) with aspiration pneumonia; 4 patients (ENS: 2, DNS: 2) with regurgitation; 1 patient (ENS: 0, DNS: 1) with ileus; 21 patients (ENS: 10, DNS: 11) with fever; 13 patients (ENS: 8, DNS: 5) with hypoglycemia; and 20 patients (ENS: 11, DNS: 9) with hyperglycemia. The relative risk of each complication during post-resuscitation care was no different between groups.
Conclusions There was a similar incidence of diet-related complications during post cardiac arrest care according to the timing of enteral nutrition.
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Background Nutritional status is associated with mortality. The modified Nutrition Risk in the Critically Ill (mNUTRIC) score is one of the most commonly used nutritional risk assessment tools in intensive care units (ICUs). The purpose of this study was to compare the mortality predictive ability of the mNUTRIC score to that of the mNUTRIC-S2 score, which uses the Simplified Acute Physiology Score (SAPS) II instead of the Acute Physiology and Chronic Health Evaluation (APACHE) II.
Methods This retrospective cohort analysis included patients admitted to the ICU between January and September 2020. Each patient’s electronic medical records were reviewed. The model discrimination for predicting ICU mortality was assessed by the area under the receiver operating characteristic (ROC) curve, and a Cox regression model was performed to confirm the relationship between the groups and mortality.
Results In total, 220 patients were enrolled. The ROC curve for predicting ICU mortality was 0.64 for the mNUTRIC score versus 0.67 for the mNUTRIC-S2 score. The difference between the areas was 0.03 (95% confidence interval [CI], –0.01 to 0.06; P=0.09). Patients with mNUTRIC-S2 score ≥5 had a greater risk of ICU mortality (hazard ratio [HR], 3.64; 95% CI, 1.85–7.14; P<0.001); however, no such relationship was observed with mNUTRIC score (HR, 1.69; 95% CI, 0.62–4.62; P=0.31).
Conclusions The mNUTRIC-S2 score was significantly associated with ICU mortality. A cutoff score of 5 was selected as most appropriate.
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Background The VSCAREMD model is used for evaluating vaccination, sleep, and parental care burden, which includes daily activity and social interaction, rehabilitation requirements, hearing, mood, and development. It has been proposed to detect post-intensive care syndrome (PICS) in children. This study aimed to outline the incidence of PICS in children using the VSCAREMD model and to describe the associated factors.
Methods All children ages 1 month to 15 years and admitted to the intensive care unit for at least 48 hours were evaluated using the VSCAREMD model within 1 week of intensive care discharge. Abnormal findings were assorted into four domains: physical, cognitive, mental, and social. Descriptive statistics were performed using chi-square, univariate, and multivariate analyses.
Results A total of 78 of 95 children (82.1%) had at least one abnormal domain. Physical, cognitive, mental, and social morbidity were found in 64.2%, 26.3%, 13.7%, and 38.9% of the children, respectively. Prolonged intensive care unit stay greater than 7 days was associated with dysfunction in physical (adjusted odds ratio [aOR], 3.80; 95% confidence interval [CI], 1.31–11.00), cognitive (aOR, 10.11; 95% CI, 3.01–33.89), and social domains (aOR, 5.01; 95% CI, 2.01–12.73). Underlying medical conditions were associated with cognitive (aOR, 13.63; 95% CI, 2.64– 70.26) and social morbidity (aOR, 2.81; 95% CI, 1.06–7.47).
Conclusions The incidence of PICS using the VSCAREMD model was substantially high and associated with prolonged intensive care. This model could help evaluate PICS in children.
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Background The aim of this study was to evaluate the hemodynamic protective effects of perioperative ventilation in pressure-controlled ventilation (PCV) and adaptive support ventilation (ASV) modes based on non-invasive hemodynamic monitoring indicators.
Methods The study included 32 patients who were scheduled for planned open abdominal surgery. Depending on the chosen ventilation strategy, patients were included in two groups of PCV mode ventilation (n=14) and ASV mode ventilation (n=18). The hemodynamic effects of the ventilation strategies were assessed by estimated continuous cardiac output (esCCO) and cardiac index (esCCI).
Results Preoperative cardiac output (CO) was 6.1±1.3 L/min in group 1 patients and 6.3±0.8 L/min in group 2 patients, and preoperative cardiac index (CI) was 3.9±0.4 L/min/m2 in group 1 patients and 3.8±0.8 L/min/m2 in group 2 patients. The ejection fraction (EF) in group 1 subjects was 55.4%±0.3%; this rate was 56.5%±0.5% in group 2 subjects. Group 1 patients experienced a 14.7% CO decrease to 5.2±0.7 L/min, a 17.9% CI decrease to 3.2±0.6 L/min/m2 , and a 12.8% mean arterial pressure decrease to 82.3±9.4 mm Hg 30 minutes after the start of surgery. One hour after the start of surgery, the CO mean values of group 2 patients were lower than baseline by 7.9% and differed from the dynamics of patients in group 1, in whom CO was lower than baseline by 13.1%. At the end of the operation, the CO values were lower than baseline by 11.5% and 6.3% in patients of groups 1 and 2, respectively. Our data showed that the changes in EF during and after surgery correlated with CO indicators determined by the esCCO.
Conclusions In our study, perioperative ventilation in ASV mode was more protective than PCV mode and was characterized by lower tidal volume (16.2%) and driving pressure (12.1%). Hemodynamically-controlled mechanical ventilation reduces the negative impact of cardiopulmonary interactions,
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Background Pediatric intensive care units (PICUs), where children with critical illnesses are treated, require considerable manpower and technological infrastructure in order to keep children alive and free from sequelae.
Methods In this retrospective comparative cohort study, hospital records of patients aged 1 month to 18 years who died in the study PICU between January 2015 and December 2019 were reviewed.
Results A total of 2,781 critically ill children were admitted to the PICU. The mean±standard deviation age of 254 nonsurvivors was 64.34±69.48 months. The mean PICU length of stay was 17 days (range, 1–205 days), with 40 children dying early (<1 day of PICU admission). The majority of nonsurvivors (83.9%) had comorbid illnesses. Children with early mortality were more likely to have neurological findings (62.5%), hypotension (82.5%), oliguria (47.5%), acidosis (92.5%), coagulopathy (30.0%), and cardiac arrest (45.0%) and less likely to have terminal illnesses (52.5%) and chronic illnesses (75.6%). Children who died early had a higher mean age (81.8 months) and Pediatric Risk of Mortality (PRISM) III score (37). In children who died early, the first three signs during ICU admission were hypoglycemia in 68.5%, neurological symptoms in 43.5%, and acidosis in 78.3%. Sixty-seven patients needed continuous renal replacement therapy, 51 required extracorporeal membrane oxygenation support, and 10 underwent extracorporeal cardiopulmonary resuscitation.
Conclusions We found that rates of neurological findings, hypotension, oliguria, acidosis, coagulation disorder, and cardiac arrest and PRISM III scores were higher in children who died early compared to those who died later.
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Background Early recognition of deterioration events is crucial to improve clinical outcomes. For this purpose, we developed a deep-learning-based pediatric early-warning system (pDEWS) and aimed to validate its clinical performance.
Methods This is a retrospective multicenter cohort study including five tertiary-care academic children’s hospitals. All pediatric patients younger than 19 years admitted to the general ward from January 2019 to December 2019 were included. Using patient electronic medical records, we evaluated the clinical performance of the pDEWS for identifying deterioration events defined as in-hospital cardiac arrest (IHCA) and unexpected general ward-to-pediatric intensive care unit transfer (UIT) within 24 hours before event occurrence. We also compared pDEWS performance to those of the modified pediatric early-warning score (PEWS) and prediction models using logistic regression (LR) and random forest (RF).
Results The study population consisted of 28,758 patients with 34 cases of IHCA and 291 cases of UIT. pDEWS showed better performance for predicting deterioration events with a larger area under the receiver operating characteristic curve, fewer false alarms, a lower mean alarm count per day, and a smaller number of cases needed to examine than the modified PEWS, LR, or RF models regardless of site, event occurrence time, age group, or sex.
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