Ultrasonographic evaluation of diaphragm thickness and excursion: correlation with weaning success in trauma patients: prospective cohort study.

PURPOSE: Prolonged mechanical ventilation (MV) subjects multiple trauma patients to ventilator-induced diaphragmatic dysfunction. There is limited evidence on the predictive role of diaphragm ultrasound (DUS) for weaning success in multiple trauma patients. Therefore, we evaluated Ultrasound of the diaphragm as a valuable indicator of weaning outcomes, in trauma patients. MATERIAL AND METHODS: This prospective cohort study included 50 trauma patients from September 2018 to February 2019. DUS was performed twice: upon ICU admission and the first weaning attempt. The diagnostic accuracy of indexes was evaluated by ROC curves. RESULTS: The study included patients with a mean age of 35.4 ± 17.37, and 78% being male. The median injury severity score was 75 (42-75). The failure group exhibited significantly lower right diaphragmatic excursion (DE) compared to the success group (P = 0.006). In addition, the failure group experienced a significant decrease in both right and left DE from admission to the first attempt of weaning from MV (P < 0.001). Both groups showed a significant decrease in inspiratory and expiratory thickness on both sides during weaning from MV compared to the admission time (P < 0.001). The findings from the ROC analysis indicated that the Rapid shallow breathing index (RSBI) (Sensitivity = 91.67, Specificity = 100), respiratory rate (RR)/DE (Right: Sensitivity = 87.5, Specificity = 92.31), and RR/TF (Thickening Fraction) (Right: Sensitivity = 83.33, Specificity = 80.77) demonstrated high sensitivity and specificity in predicting weaning outcome. CONCLUSION: In the context of patients with multiple trauma, employing DUC and assessing diaphragmatic excursion, thickness, RR/DE index, RR/TF index, and RSBI can aid in determining successful ventilator weaning.

Unintended impact of COVID-19 pandemic on the rate of catheter related nosocomial infections and incidence of multiple drug resistance pathogens in three intensive care units not allocated to COVID-19 patients in a large teaching hospital.

BACKGROUND: The prevalence of resistant hospital infections in the intensive care unit (ICU) increases mortality and antibiotic resistance. COVID-19 pandemic may have unintended impact on nosocomial infections (NI) and the prevalence of resistant microorganism. METHODOLOGY: The present non-interventional study was performed by a pre and a post survey each lasting 8 months before (March-October 2019) and after (March-October 2020) the onset of COVID-19 pandemic in three ICU's, not allocated to COVID-19 patients, in Nemazee Hospital, Shiraz, Iran. The rates of the following nosocomial infections were compared at pre- and post-pandemic period: ventilator associated pneumonia (VAP), central line associated blood stream infection (CLABSI), catheter-associated urinary tract infections (CAUTI) and incidence of multiple drug resistance (MDR) pathogens. RESULTS: Pre-pandemic and pandemic incidence of VAP was 23.5 and 17.2 cases per 1000 device-days, respectively; an absolute decrease of 27%. The main reason for the decrease in the rate of VAP during the pandemic was a significant decrease in the rate of VAP caused by Acinetobacter baumannii; from 39 to 17% in total VAP episodes. The rate of VAP associated with other microorganisms remained relatively unchanged from 14.2 cases in pre-pandemic period to 14.3 cases per 1000 MV-days during the pandemic (P = 0.801). Pre-pandemic incidence of CLABSI was 7.3 cases and, in pandemic period, was 6.5 cases per 1000 device-days (IRR = 0.88, 95% CI 0.43-1.73, P = 0.703). Pre-pandemic incidence of CAUTI was 2 and in pandemic period, was 1.4 cases per 1000 device-days (IRR = 0.70, 95% CI 0.22-1.98, P = 0.469). CONCLUSION: The results of the present study showed a decrease in the incidence of VAP in critically ill non-COVID-19 patients during the pandemic compared to before the pandemic, especially regarding Acinetobacter baumannii.

The Effectiveness of the Intermediate and Therapeutic Doses of Enoxaparin in COVID-19 Patients: A Comparative Study of Factor Xa Inhibition.

BACKGROUND: Management of anticoagulant therapy in COVID-19 patients is critical. Low-molecular-weight heparin (LMWH) thromboprophylaxis is already recommended, and anti-Factor Xa (anti-FXa) monitoring has been used to titrate LMWH doses. METHODS: Through a cross-sectional study, we evaluated anti-FXa activity in patients admitted to the ICU, receiving intermediate dose (30, 40, 50 mg, subcutaneously [SC], twice daily) or therapeutic dose (1 mg/kg, SC, Q12h) of enoxaparin to find whether the patients in these two groups achieved anti-FXa levels in the accepted thromboprophylaxis range. RESULTS: The occurrence of deep vein thrombosis was 26% in the therapeutic-dose group and 17% in the intermediate-dose group. D-dimer values were nearly 3.5-fold higher in those who received a therapeutic dose of anticoagulants than in those who received intermediate-dose thromboprophylaxis. Patients in the therapeutic-dose group had significantly higher IL-6 levels (p ≤ 0.001). More than one-third of the patients in the therapeutic-dose group (n = 8; 42.18%) and approximately half of the patients in the intermediate-dose group (n = 12; 52.2%) achieved the target range level of anti-FXa. Patients who received therapeutic doses were more likely to have anti-FXa levels above the expected range (47.4 vs 13% in the intermediate-dose group; p < 0.05). CONCLUSION: Therapeutic dose of enoxaparin in critically ill COVID-19-infected patients did not reduce the incidence of thromboembolic events and, on the other hand, may predispose these patients to increased risk of bleeding by increasing anti-FXa activity above the desired level. Administration of intermediate-dose thromboprophylaxis is suggested to achieve anti-FXa levels in the accepted thromboprophylaxis range.

Which criteria is a better predictor of ICU admission in trauma patients? An artificial neural network approach.

PURPOSE: One of the most critical concerns in the intensive care unit (ICU) section is identifying the best criteria for entering patients to this part. This study aimed to predict the best compatible criteria for entering trauma patients in the ICU section. METHOD: The present study was a historical cohort study. The data were collected from 2448 trauma patients referring to Shahid Rajaee Hospital between January 2015 and January 2017 in Shiraz, Iran. The artificial neural network (ANN) models with cross-validation and logistic regression (LR) with a backward method was used for data analysis. The final analysis was performed on a total of 958 patients who were transferred to the ICU section. RESULTS: Based on the present results, the motor component of the GCS score at each cutoff point had the highest importance. The results also showed better performance for the AUC and accuracy rate for ANN compared with LR. CONCLUSION: The most critical indicators in predicting the optimal use of ICU services in this study were the Motor component of the GCS. Results revealed that the ANN had a better performance than the LR in predicting the main outcomes of the traumatic patients in both the accuracy and AUC index. Trauma section surgeons and ICU specialists will benefit from this study's results and can assist them in making decisions to predict the patient outcomes before entering the ICU.

Comparison of chest CT scan findings between COVID-19 and pulmonary contusion in trauma patients based on RSNA criteria: Established novel criteria for trauma victims.

PROPOSE: In this study, we re-assessed the criteria defined by the radiological society of North America (RSNA) to determine novel radiological findings helping the physicians differentiating COVID-19 from pulmonary contusion. METHODS: All trauma patients with blunt chest wall trauma and subsequent pulmonary contusion, COVID-19-related signs and symptoms before the trauma were enrolled in this retrospective study from February to May 2020. Included patients (Group P) were then classified into two groups based on polymerase chain reaction tests (Group Pa for positive patients and Pb for negative ones). Moreover, 44 patients from the pre-pandemic period (Group PP) were enrolled. They were matched to Group P regarding age, sex, and trauma-related scores. Two radiologists blindly reviewed the CT images of all enrolled patients according to criteria defined by the RSNA criteria. The radiological findings were compared between Group P and Group PP; statistically significant ones were re-evaluated between Group Pa and Group Pb thereafter. Finally, the sensitivity and specificity of each significant findings were calculated. The Chi-square test was used to compare the radiological findings between Group P and Group PP. RESULTS: In the Group PP, 73.7% of all ground-glass opacities (GGOs) and 80% of all multiple bilateral GGOs were detected (p < 0.001 and p = 0.25, respectively). Single bilateral GGOs were only seen among the Group PP. The Chi-square tests showed that the prevalence of diffused GGOs, multiple unilateral GGOs, multiple consolidations, and multiple bilateral consolidations were significantly higher in the Group P (p = 0.001, 0.01, 0.003, and 0.003, respectively). However, GGOs with irregular borders and single consolidations were more significant among the Group PP (p = 0.01 and 0.003, respectively). Of note, reticular distortions and subpleural spares were exclusively detected in the Group PP. CONCLUSION: We concluded that the criteria set by RSNA for the diagnosis of COVID-19 are not appropriate in trauma patients. The clinical signs and symptoms are not always useful either. The presence of multiple unilateral GGOs, diffused GGOs, and multiple bilateral consolidations favor COVID-19 with 88%, 97.62%, and 77.7% diagnostic accuracy.

Prediction of Patients with COVID-19 Requiring Intensive Care: A Cross-sectional Study Based on Machine-learning Approach from Iran.

Background: Prioritizing the patients requiring intensive care may decrease the fatality of coronavirus disease-2019 (COVID-19). Aims and objectives: To develop, validate, and compare two models based on machine-learning methods for predicting patients with COVID-19 requiring intensive care. Materials and methods: In 2021, 506 suspected COVID-19 patients, with clinical presentations along with radiographic findings, were laboratory confirmed and included in the study. The primary end-point was patients with COVID-19 requiring intensive care, defined as actual admission to the intensive care unit (ICU). The data were randomly partitioned into training and testing sets (70% and 30%, respectively) without overlapping. A decision-tree algorithm and multivariate logistic regression were performed to develop the models for predicting the cases based on their first 24 hours data. The predictive performance of the models was compared based on the area under the receiver operating characteristic curve (AUC), sensitivity, and accuracy of the models. Results: A 10-fold cross-validation decision-tree model predicted cases requiring intensive care with the AUC, accuracy, and sensitivity of 97%, 98%, and 94.74%, respectively. The same values in the machine-learning logistic regression model were 75%, 85.62%, and 55.26%, respectively. Creatinine, smoking, neutrophil/lymphocyte ratio, temperature, respiratory rate, partial thromboplastin time, white blood cell, Glasgow Coma Scale (GCS), dizziness, international normalized ratio, O2 saturation, C-reactive protein, diastolic blood pressure (DBP), and dry cough were the most important predictors. Conclusion: In an Iranian population, our decision-based machine-learning method offered an advantage over logistic regression for predicting patients requiring intensive care. This method can support clinicians in decision-making, using patients' early data, particularly in low- and middle-income countries where their resources are as limited as Iran. How to cite this article: Sabetian G, Azimi A, Kazemi A, Hoseini B, Asmarian N, Khaloo V, et al. Prediction of Patients with COVID-19 Requiring Intensive Care: A Cross-sectional Study based on Machine-learning Approach from Iran. Indian J Crit Care Med 2022;26(6):688-695. Ethics approval: This study was approved by the Ethical Committee of Shiraz University of Medical Sciences (IR.SUMS.REC.1399.018).

COVID-19 infection among healthcare workers: a cross-sectional study in southwest Iran.

OBJECTIVE: With the novel coronavirus pandemic, the impact on the healthcare system and workers cannot be overlooked. However, studies on the infection status of medical personnel are still lacking. It is imperative to ensure the safety of health-care workers (HCWs) not only to safeguard continuous patient care but also to ensure they do not transmit the virus, therefore evaluation of infection rates in these groups are indicated. METHODS: Demographic and clinical data regarding infected cases among HCWs of Fars, Iran with positive SARS-CoV-2 PCR tests were obtained from 10th March to 17th May 2020. RESULTS: Our data demonstrated a rate of 5.62% (273 out of 4854 cases) infection among HCW, with a mean age of 35 years and a dominance of female cases (146 cases: 53.5%). The majority of infected cases were among nurses (51.3%), while the most case infection rate (CIR) was among physicians (27 positive cases out of 842 performed test (3.2%)). Also, the highest rate of infection was in the emergency rooms (30.6%). Also, 35.5% of the patients were asymptomatic and the most frequent clinical features among symptomatic patients were myalgia (46%) and cough (45.5%). Although 5.5% were admitted to hospitals, there were no reports of ICU admission. Furthermore, 10.3% of the cases reported transmitting the infection to family and friends. Regarding safety precautions, 1.6% didn't wear masks and 18.7% didn't use gloves in work environments. CONCLUSION: HCWs are among the highest groups at risk of infection during the COVID-19 pandemic; therefore, evaluating infection rates and associated features is necessary to improve and adjust protective measures of these vulnerable, yet highly essential group.

Adequacy of maternal anesthesia depth with two sodium thiopental doses in elective caesarean section: a randomized clinical trial.

BACKGROUND: Administration of an optimal dose of anesthetic agent to ensure adequate depth of hypnosis with the lowest risk of adverse effects to the fetus is highly important in cesarean section. Sodium thiopental (STP) is still the first choice for induction of anesthesia in some countries for this obstetric surgery. We aimed to compare two doses of STP with regarding the depth of anesthesia and the condition of newborn infants. METHODS: In this clinical trial, parturient undergoing elective Caesarian section were randomized into two groups receiving either low-dose (5 mg/kg) or high-dose (7 mg/kg) STP. Muscle relaxation was provided with succinylcholine 2 mg/kg and anesthesia was maintained with O2/N2O and sevoflurane. The depth of anesthesia was evaluated using isolated forearm technique (IFT) and bispectral index (BIS) in various phases. Additionally, infants were assessed using Apgar score and neurobehavioral test. RESULTS: Forty parturient were evaluated in each group. BIS was significantly lower in high-dose group at skin incision to delivery and subcutaneous and skin closure. Also, significant differences were noticed in IFT over induction to incision and incision to delivery. Apgar score was significantly lower in high-dose group at 1 min after delivery. Newborn infants in low-dose group had significantly better outcomes in all three domains of the neurobehavioral test. CONCLUSION: 7 mg/kg STP is superior to 5 mg/kg in creating deeper hypnosis for mothers. However, it negatively impacts Apgar score and neurobehavioral test of neonates. STP seems to has dropped behind as an acceptable anesthetic in Cesarean section. TRIAL REGISTRATION: IRCT No: 2016082819470 N45 , 13/03/2019.

Do clinical and paraclinical findings have the power to predict critical conditions of injured patients after traumatic injury resuscitation? Using data mining artificial intelligence.

PURPOSE: The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury. Early recognition of patients is an important case of such decision-making with risk of worse prognosis. This article is to answer if clinical and paraclinical signs can predict the critical conditions of injured patients after traumatic injury resuscitation. METHODS: The study included 1107 trauma patients, 16 years and older. The patients were trauma victims of Levels I and II triage and admitted to the Rajaee (Emtiaz) Trauma Hospital, Shiraz, in 2014-2015. The cross-industry process for data mining methodology and modeling was used for assessing the best early clinical and paraclinical variables to predict the patients' prognosis. Five modeling methods including the support vector machine, K-nearest neighbor algorithms, Bagging and Adaboost, and the neural network were compared by some evaluation criteria. RESULTS: Learning algorithms can predict the deterioration of injured patients by monitoring the Bagging and SVM models with 99% accuracy. The most-fitted variables were Glasgow Coma Scale score, base deficit, and diastolic blood pressure especially after initial resuscitation in the algorithms for overall outcome predictions. CONCLUSION: Data mining could help in triage, initial treatment, and further decision-making for outcome measures in trauma patients. Clinical and paraclinical variables after resuscitation could predict short-term outcomes much better than variables on arrival. With artificial intelligence modeling system, diastolic blood pressure after resuscitation has a greater association with predicting early mortality rather than systolic blood pressure after resuscitation. Artificial intelligence monitoring may have a role in trauma care and should be further investigated.

Sound level analysis in endotracheal tube obstruction in spontaneous breathing and mechanical ventilation-an animal model study.

Endotracheal tube (ETT) obstruction, either complete or partial, is a serious life threatening complication in intubated patients. Therefore, implementing a practical method to diagnose this condition is vital. Alteration in respiratory sound signals caused by ETT occlusion can be used for early detection of obstruction. This study is aimed to assess changes in respiratory sound signals after creation of different types of tubal obstruction in an animal model experiment. Artificial internal obstructions were created in three different sizes and three different locations by stitching pieces of smaller tubes in ETTs with internal diameter of 8 mm. A microphone was used to record respiratory sounds during both spontaneous breathing and mechanical ventilation in seven anesthetized dogs. The sound intensity levels produced by different grades and degrees of obstructions were measured and compared with those in non-obstructed tubes. During spontaneous breathing, significant decrease in sound intensity level was detected even with the lowest grades of obstruction (p = 0.003, 0.001, and 0.002, proximal, middle and distal obstructions, respectively). However, in mechanical ventilation, significant decrease in sound intensity was observed only in distal tubal obstruction (p = 0.037). The difference among levels of sound intensity produced by different obstruction locations of occlusion was not statistically significant (p ≥ 0.090). Data analysis revealed that sound intensity level decreased significantly when the degree of obstruction increased. In addition, this change in sound level was not related to the location of obstruction. The decrease in sound intensity changes can be used to detect ETT obstruction. However, further studies are needed for clinical application.

The impact of computerized physician order entry on prescription orders: A quasi-experimental study in Iran.

Background: One way to reduce medical errors associated with physician orders is computerized physician order entry (CPOE) software. This study was conducted to compare prescription orders between 2 groups before and after CPOE implementation in a hospital. Methods: We conducted a before-after prospective study in 2 intensive care unit (ICU) wards (as intervention and control wards) in the largest tertiary public hospital in South of Iran during 2014 and 2016. All prescription orders were validated by a clinical pharmacist and an ICU physician. The rates of ordering the errors in medical orders were compared before (manual ordering) and after implementation of the CPOE. A standard checklist was used for data collection. For the data analysis, SPSS Version 21, descriptive statistics, and analytical tests such as McNemar, chi-square, and logistic regression were used. Results: The CPOE significantly decreased 2 types of errors, illegible orders and lack of writing the drug form, in the intervention ward compared to the control ward (p< 0.05); however, the 2 errors increased due to the defect in the CPOE (p< 0.001). The use of CPOE decreased the prescription errors from 19% to 3% (p= 0.001), However, no differences were observed in the control ward (p<0.05). In addition, more errors occurred in the morning shift (p< 0.001). Conclusion: In general, the use of CPOE significantly reduced the prescription errors. Nonetheless, more caution should be exercised in the use of this system, and its deficiencies should be resolved. Furthermore, it is recommended that CPOE be used to improve the quality of delivered services in hospitals.

Early Acute Kidney Injury based on Serum Creatinine or Cystatin C in Intensive Care Unit after Major Trauma.

BACKGROUND: Acute kidney injury (AKI) is a common problem in critically ill patients and is independently associated with increased morbidity and mortality. Recently, serum cystatin C has been shown to be superior to creatinine in early detection of renal function impairment. We compared estimated GFR based on serum cystatin C with estimated GFR based on serum creatinine for early detection of renal dysfunction according to the RIFLE criteria. METHODS: During 9 months, three hundred post trauma patients that were referred to the intensive care unit of a referral trauma hospital were recruited. Serum creatinine and serum cystatin C were measured and the estimated GFR within 24 hours of ICU admission was calculated. The primary outcome was the incidence of AKI according to the RIFLE criteria within 2(nd) to 7(th) day of admission. RESULTS: During the first week of ICU admission, 21% of patients experienced AKI. After adjusting for major confounders, only the patients with first day's serum cystatin level higher than 0.78 mg/l were at higher risk of first week AKI (OR=6.14, 95% CI: 2.5-14.7, P<0.001). First day's serum cystatin C and injury severity score were the major risk factors for ICU mortality (OR=3.54, 95% CI: 1.7-7.4, P=0.001) and (OR=4.6, 95% CI: 1.5-14, P=0.007), respectively. CONCLUSION: Within 24 hours after admission in ICU due to multiple trauma, high serum cystatin C level may have prognostic value in predicting early AKI and mortality during ICU admission. However, such correlation was not seen neither with creatinine nor cystatin C based GFR.

Does red blood cell transfusion affect clinical outcomes in critically ill patients? A report from a large teaching hospital in south Iran.

BACKGROUND: Despite the beneficial effects, RBC transfusion can be associated with infectious and non-infectious complications in critically ill patients. OBJECTIVES: Investigate current RBC transfusion practices and their effect on the clinical outcomes of patients in intensive care units (ICUs). DESIGN: Retrospective observational study. SETTING: Three mixed medical-surgical adult ICUs of a large academic tertiary hospital. PATIENTS AND METHODS: From March 2018 to February 2020, all adult patients admitted to medical or surgical ICU. Patients who received one or more RBC transfusions during the first month of ICU admission were included in the "transfusion" group, while the remaining patients were assigned to the "non-transfusion" group. MAIN OUTCOME MEASURES: Mortality and length of ICU and hospital stay. SAMPLE SIZE: 2159 patients. RESULTS: Of 594 patients who recieved transfusions, 27% of patients received red blood cell (RBC) products. The mean pre-transfusion hemoglobin (Hb) level was 8.05 (1.46) g/dL. There was a significant relationship between higher APACHE II scores and ICU mortality in patients with Hb levels of 7-9 g/dL (OR adjusted=1.05). Also, ICU mortality was associated with age (OR adjusted=1.03), APACHE II score (OR adjusted=1.08), and RBC transfusion (OR adjusted=2.01) in those whose Hb levels were >9 (g/dl). CONCLUSION: RBC transfusion was associated with an approximately doubled risk of ICU mortality in patients with Hb>9 g/dL. High APACHE II score and age increase the chance of death in the ICU by 8% and 3%, respectively. Hence, ICU physicians should consider a lower Hb threshold for RBC transfusion, and efforts must be made to optimize RBC transfusion practices. LIMITATIONS: Single-center and retrospective study.

High Post-Infection Protection after COVID-19 among Healthcare Workers: A Population-Level Observational Study.

Background: Even though a few years have passed since the coronavirus disease 2019 (COVID-19) outbreak, information regarding certain aspects of the disease, such as post-infection immunity, is still quite limited. This study aimed to evaluate post-infection protection and COVID-19 features among healthcare workers (HCWs), during three successive surges, as well as the rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection, reactivation, re-positivity, and severity. Methods: This cross-sectional population-level observational study was conducted from 20 April 2020 to 18 February 2021. The study population included all HCWs in public or private hospitals in Fars Province, Southern Iran. The infection rate was computed as the number of individuals with positive polymerase chain reaction (PCR) tests divided by the total number of person-days at risk. The re-infection was evaluated after 90 days. Results: A total of 30,546 PCR tests were performed among HCWs, of which 13,749 (61.94% of total HCWs) were positive. Considering the applied 90-day threshold, there were 44 (31.2%) cases of reactivation and relapse, and 97 (68.8% of infected and 1.81% of total HCWs) cases of reinfection among 141 (2.64%) diagnosed cases who experienced a second episode of COVID-19. There was no significant difference in symptoms (P=0.65) or the necessity for ICU admission (P=0.25). The estimated protection against repeated infection after a previous SARS-CoV-2 infection was 94.8% (95% CI=93.6-95.7). Conclusion: SARS-CoV-2 re-positivity, relapse, and reinfection were rare in the HCW population. After the first episode of infection, an estimated 94.8% protection against recurring infections was achieved. A preprint version of this manuscript is available at DOI:10.21203/rs.3.rs-772662/v1 (https://www.researchsquare.com/article/rs-772662/v1).

Prediction prolonged mechanical ventilation in trauma patients of the intensive care unit according to initial medical factors: a machine learning approach.

The goal of this study was to develop a predictive machine learning model to predict the risk of prolonged mechanical ventilation (PMV) in patients admitted to the intensive care unit (ICU), with a focus on laboratory and Arterial Blood Gas (ABG) data. This retrospective cohort study included ICU patients admitted to Rajaei Hospital in Shiraz between 2016 and March 20, 2022. All adult patients requiring mechanical ventilation and seeking ICU admission had their data analyzed. Six models were created in this study using five machine learning models (PMV more than 3, 5, 7, 10, 14, and 23 days). Patients' demographic characteristics, Apache II, laboratory information, ABG, and comorbidity were predictors. This study used Logistic regression (LR), artificial neural networks (ANN), support vector machines (SVM), random forest (RF), and C.5 decision tree (C.5 DT) to predict PMV. The study enrolled 1138 eligible patients, excluding brain-dead patients and those without mechanical ventilation or a tracheostomy. The model PMV > 14 days showed the best performance (Accuracy: 83.63-98.54). The essential ABG variables in our two optimal models (artificial neural network and decision tree) in the PMV > 14 models include FiO2, paCO2, and paO2. This study provides evidence that machine learning methods outperform traditional methods and offer a perspective for achieving a consensus definition of PMV. It also introduces ABG and laboratory information as the two most important variables for predicting PMV. Therefore, there is significant value in deploying such models in clinical practice and making them accessible to clinicians to support their decision-making.

The clinical and paraclinical effectiveness of four-hour infusion vs. half-hour infusion of high-dose ampicillin-sulbactam in treatment of critically ill patients with sepsis or septic shock: An assessor-blinded randomized clinical trial.

PURPOSE: This study was conducted to determine whether critically ill patients admitted to the intensive care unit (ICU) with sepsis and septic shock may benefit from extended infusion of ampicillin/sulbactam compared with those receiving intermittent infusion. MATERIAL AND METHODS: This randomized assessor-blinded clinical trial was conducted in the ICUs of Nemazee and Shahid Rajaee hospital, Shiraz, Iran, from August 2019 to August 2021. The participants randomly received 9 g Ampicillin/Sulbactam every 8 h by either extended (infused over 4 h) or intermittent (infused over 30 min) intravenous infusion if their estimated glomerular filtration rate based on Cockrorft-Gault formula was higher than 60 ml/min. RESULTS: Totally, 136 patients were enrolled and allocated to the intervention and control groups, each with 68 patients. Clinical cure was significantly higher in the extended group (P = 0.039), but ICU and hospital length of stay did not differ between the groups (P = 0.87 and 0.83, respectively). The ICU (P = 0.031) and hospital (P = 0.037) mortality rates in the extended infusion group were significantly lower than those in the intermittent infusion group. CONCLUSION: These data should be replicated in larger clinical trials before providing any recommendation in favor of this method of administration in clinical practice.

Association Between Neutrophil Density and Survival in Trauma Patients Admitted to the Intensive Care Unit; a Retrospective Cohort Study.

Introduction: Altered immune responses, in particular neutrophil changes, are perceived to play a key role in immune responses to trauma. This study aimed to evaluate the association of neutrophil changes with patients' survival in severe multiple trauma cases. Methods: The current retrospective cohort study was conducted using data from patients admitted in the intensive care unit (ICU) of a trauma center in Shiraz, Iran, between 2016 and 2021. Patients were divided into three groups (i.e., normal, neutropenia, and neutrophilia) based on neutrophil count at the time of ICU admission, and the association of neutrophil count with in-hospital mortality was analyzed. Results: 2176 patients with the mean age of 37.90 ± 18.57 years were evaluated (84.04% male). The median trauma severity based on injury severity score (ISS) in this series was 9 (4 -17). Patients were divided in to three groups of neutrophilia (n = 1805), normal (n = 357), and neutropenia (n = 14). There were not any significant differences between groups regarding age distribution (p = 0.634), gender (p = 0.544), and trauma severity (p = 0.197). The median survival times for the normal, neutropenia, and neutrophilia groups were 49 (IQR: 33 -47) days, 51 (IQR: 8- 51) days, and 38 (IQR: 26 - 52) days, respectively (p = 0.346). The log-rank test showed a statistically significant difference between the three groups adjustment for ISS (p ≤ 0.001). For each unit increase in ISS, the hazard ratio increased by 2%. In ISS 9-17, the hazard ratio increased by 11% compared to ISS<4. Also, in ISS>17, the hazard ratio increased by 76% compared to ISS<4 in ICU-hospitalized patients. Conclusions: In general, the findings of the present study showed that the survival rate of patients in the normal group after ISS adjustment was higher than the other two groups. Also, the Cox model showed that the mortality risk ratio in the neutropenia group was 15 times higher than the normal group.

Trauma and COVID-19: Clinical and Paraclinical similarities between Trauma Patients with Positive and Negative PCR Tests.

Objective: To compare clinical and paraclinical similarities between trauma patients with positive RT-PCR tests (PCR+ve) and the RT-PCR negative ones (PCR -ve). Methods: This a case-control study, where cases had a PCR+ve and controls had a negative result. Two groups were compared regarding (para) clinical values. Multivariable binary logistic regression analysis investigated the variables predicting COVID-19 and the mortality rate. Results: Both groups were similar regarding the clinical findings and comorbidities (p>0.05). PCR+ve group had lower lymphocyte count (1.41 [1.45] vs. 1.66 [1.61], p=0.030), CPK level (411 [928.75] vs. 778 [1946.5]. p=0.006) and CRP level (17 [42.5] vs. 24 [50.75], p=0.004). However, none of these findings were significant in the multivariable analysis. Finally, PCR+ve group had increased odds of death (OR=2.88; 95% CI=1.22-7.41). Conclusion: Unlike our primary hypothesis, the study failed to mark any significant (para) clinical features guiding us to detect COVID-19 earlier in trauma patients. Moreover, the PCR+ve group is at increased mortality risk. A larger, multicentric prospective study should be designed to address this issue.

Pharmacokinetic assessment of vancomycin in critically ill patients and nephrotoxicity prediction using individualized pharmacokinetic parameters.

Introduction: Therapeutic drug monitoring (TDM) and pharmacokinetic assessments of vancomycin would be essential to avoid vancomycin-associated nephrotoxicity and obtain optimal therapeutic and clinical responses. Different pharmacokinetic parameters, including trough concentration and area under the curve (AUC), have been proposed to assess the safety and efficacy of vancomycin administration. Methods: Critically ill patients receiving vancomycin at Nemazee Hospital were included in this prospective study. Four blood samples at various time intervals were taken from each participated patient. Vancomycin was extracted from plasma samples and analyzed using a validated HPLC method. Results: Fifty-three critically ill patients with a total of 212 blood samples from June 2019 to June 2021 were included in this study. There was a significant correlation between baseline GFR, baseline serum creatinine, trough and peak concentrations, AUCτ, AUC24h, Cl, and Vd values with vancomycin-induced AKI. Based on trough concentration values, 66% of patients were under-dosed (trough concentration <15 µg/ml) and 18.9% were over-dosed (trough concentration ≥20 µg/ml). Also, based on AUC24h values, about 52.2% were under-dosed (AUC24h < 400 µg h/ml), and 21.7% were over-dosed (AUC24h > 600 µg h/ml) that emphasizes on the superiority of AUC-based monitoring approach for TDM purposes to avoid nephrotoxicity occurrence. Conclusion: The AUC-based monitoring approach would be superior in terms of nephrotoxicity prediction. Also, to avoid vancomycin-induced AKI, trough concentration and AUCτ values should be maintained below the cut-off points.