Early Warning Scoring System Research Articles

204 Use of Early Warning Scoring System in Acute Medical Care for Deteriorating Hospitalized Patients: Experiences of a Tertiary Hospital

204 Use of Early Warning Scoring System in Acute Medical Care for Deteriorating Hospitalized Patients: Experiences of a Tertiary Hospital

Early prediction of need for invasive mechanical ventilation in the neonatal intensive care unit using artificial intelligence and electronic health records: a clinical study

BackgroundRespiratory support is crucial for newborns with underdeveloped lung. The clinical outcomes of patients depend on the clinician’s ability to recognize the status underlying the presented symptoms and signs. With the increasing number of high-risk infants, artificial intelligence (AI) should be considered as a tool for personalized neonatal care. Continuous monitoring of vital signs is essential in cardiorespiratory care. In this study, we developed deep learning (DL) prediction models for rapid and accurate detection of mechanical ventilation requirements in neonates using electronic health records (EHR).MethodsWe utilized data from the neonatal intensive care unit in a single center, collected between March 3, 2012, and March 4, 2022, including 1,394 patient records used for model development, consisting of 505 and 889 patients with and without invasive mechanical ventilation (IMV) support, respectively. The proposed model architecture includes feature embedding using feature-wise fully connected (FC) layers, followed by three bidirectional long short-term memory (LSTM) layers.ResultsA mean gestational age (GA) was 36.61 ± 3.25 weeks, and the mean birth weight was 2,734.01 ± 784.98 g. The IMV group had lower GA, birth weight, and longer hospitalization duration than the non-IMV group (P < 0.05). Our proposed model, tested on a dataset from March 4, 2019, to March 4, 2022. The mean AUROC of our proposed model for IMV support prediction performance demonstrated 0.861 (95%CI, 0.853–0.869). It is superior to conventional approaches, such as newborn early warning score systems (NEWS), Random Forest, and eXtreme gradient boosting (XGBoost) with 0.611 (95%CI, 0.600–0.622), 0.837 (95%CI, 0.828–0.845), and 0.0.831 (95%CI, 0.821–0.845), respectively. The highest AUPRC value is shown in the proposed model at 0.327 (95%CI, 0.308–0.347). The proposed model performed more accurate predictions as gestational age decreased. Additionally, the model exhibited the lowest alarm rate while maintaining the same sensitivity level.ConclusionDeep learning approaches can help accurately standardize the prediction of invasive mechanical ventilation for neonatal patients and facilitate advanced neonatal care. The results of predictive, recall, and alarm performances of the proposed model outperformed the other models.

Development and validation of the early warning system scores ontology

BackgroundClinical early warning scoring systems, have improved patient outcomes in a range of specializations and global contexts. These systems are used to predict patient deterioration. A multitude of patient-level physiological decompensation data has been made available through the widespread integration of early warning scoring systems within EHRs across national and international health care organizations. These data can be used to promote secondary research. The diversity of early warning scoring systems and various EHR systems is one barrier to secondary analysis of early warning score data. Given that early warning score parameters are varied, this makes it difficult to query across providers and EHR systems. Moreover, mapping and merging the parameters is challenging. We develop and validate the Early Warning System Scores Ontology (EWSSO), representing three commonly used early warning scores: the National Early Warning Score (NEWS), the six-item modified Early Warning Score (MEWS), and the quick Sequential Organ Failure Assessment (qSOFA) to overcome these problems.MethodsWe apply the Software Development Lifecycle Framework—conceived by Winston Boyce in 1970—to model the activities involved in organizing, producing, and evaluating the EWSSO. We also follow OBO Foundry Principles and the principles of best practice for domain ontology design, terms, definitions, and classifications to meet BFO requirements for ontology building.ResultsWe developed twenty-nine new classes, reused four classes and four object properties to create the EWSSO. When we queried the data our ontology-based process could differentiate between necessary and unnecessary features for score calculation 100% of the time. Further, our process applied the proper temperature conversions for the early warning score calculator 100% of the time.ConclusionsUsing synthetic datasets, we demonstrate the EWSSO can be used to generate and query health system data on vital signs and provide input to calculate the NEWS, six-item MEWS, and qSOFA. Future work includes extending the EWSSO by introducing additional early warning scores for adult and pediatric patient populations and creating patient profiles that contain clinical, demographic, and outcomes data regarding the patient.

Evaluation of a modified paediatric early warning score for children with congenital heart disease.

Paediatric early warning score systems are used for early detection of clinical deterioration of patients in paediatric wards. Several paediatric early warning scores have been developed, but most of them are not suitable for children with cyanotic CHD who are adapted to lower arterial oxygen saturation. The present study compared the original paediatric early warning system of the Royal College of Physicians of Ireland with a modification for children with cyanotic CHD. Retrospective single-centre study in a paediatric cardiology intermediate care unit at a German university hospital. The distribution of recorded values showed a significant shift towards higher score values in patients with cyanotic CHD (p < 0.001) using the original score, but not with the modification. An analysis of sensitivity and specificity for the factor "requirement of action" showed an area under the receiver operating characteristic for non-cyanotic patients of 0.908 (95% CI 0.862-0.954). For patients with cyanotic CHD, using the original score, the area under the receiver operating characteristic was reduced to 0.731 (95% CI 0.637-0.824, p = 0.001) compared to 0.862 (95% CI 0.809-0.915, p = 0.207), when the modified score was used. Using the critical threshold of scores ≥ 4 in patients with cyanotic CHD, sensitivity and specificity for the modified score was higher than for the original (sensitivity 78.8 versus 72.7%, specificity 78.2 versus 58.4%). The modified score is a uniform scoring system for identifying clinical deterioration, which can be used in children with and without cyanotic CHD.

An unusual presentation of severe preeclampsia presenting with maternal collapse in the post-cesarean section secondary to drug toxicity associated with pituitary hemorrhage: a case report

BackgroundSevere preeclampsia presenting with maternal collapse post-cesarean section secondary to drug toxicity associated with pituitary hemorrhage is rare.Case presentationA 24-year-old primigravida 27 weeks of gestation presented with severe preeclampsia, and underwent emergency cesarean section; postoperatively, she had a sudden maternal collapse and cardiac arrest while on labetalol and magnesium infusion. Following the return of spontaneous circulation (ROSC), the patient was found to have severe bradycardia with prolonged QTc interval and recurrent hypoglycemic episodes. Investigations had revealed low serum cortisol with the brain showing pituitary hemorrhage with features of atypical Sheehan’s syndrome without lactation failure.ConclusionsDrug toxicity is an important cause of maternal collapse and cardiac arrest. Pituitary hemorrhage needs to be suspected in maternal patients with recurrent hypoglycemic episodes with or without postpartum hemorrhage (PPH). Continuous monitoring, use of maternal early warning scoring systems (MEWS), and prudence in the perioperative period/labor room will help in reducing the complications.

Admission Early Warning Score and Neonatal Outcome in a Resource-limited Settings

Background Neonatal mortality has remained a major public health concern in low- and middle-income countries. Early warning scoring (EWS) systems minimize hospital mortality by providing rapid and efficient care; however, their effectiveness in low- and middle-income countries is unknown. Method This study is a retrospective analysis of neonates admitted to the University College Hospital in Nigeria between January and December 2019. We evaluate the accuracy of significant modified early warning scores (sMEWS) in predicting neonatal in-hospital mortality and associated risk factors. Results The majority (254; 68.5%) of the 371 admitted newborns were late preterm to term, and 54.7% were males; 173 (48.7%) required resuscitation at admission in the emergency department (ED). One hundred and thirty-seven had sMEWS, which decreased to 22 (5.9%) 72 h post-admission. Univariable analysis shows that sMEWS at admission were associated with sepsis, perinatal asphyxia, and the necessity for resuscitation. Multivariable logistic regression indicated that outborns (adjusted odds ratio [AOR]: 2.218; 95% confidence interval [CI], 1.125–4.371), need for resuscitation at admission (AOR: 5.501; CI, 3.350–9.034) and persistence of sMEWS 72 h post-admission (AOR: 9.693; CI, 2.181–43.079), were associated with sMEWS. Significantly associated with excess mortality were sMEWS at admission (AOR: 3.530; CI, 1.721–7.240) and sMEWS 72 h post-admission (AOR: 5.931; CI, 5.944 –64.385). Conclusions The sMEWS performed moderately well as an EWS in a neonatal emergency unit. Excess mortality was associated with the need for resuscitation in the ED and the persistence of sMEWS 72 h post-admission.

Energy efficient selection of spreading factor in LoRaWAN-based WBAN medical systems

Recently, the Internet of Things has been leading the technological revolution in several fields and applications. This revolution affected healthcare services adding more value to the concept of e-health. To improve the quality of these services, remote monitoring allows healthcare professionals to observe and diagnose their patients without being physically present. Since the spreading factor affects the energy consumption, the data rate, the receiver sensitivity and the time on air. A monitoring healthcare system using LoRa technology is proposed on this work to adopt the data transmission in a reliable and energy-efficient way. We propose a method to select the most convenient spreading factor based on the patients medical state. This method takes in consideration the distance to gateway, the packet error rate and the energy consumption requirements.We first determine the criticality level of the patient using the Early Warning Score system. Second, a decision about the optimal spreading factor is taken based on this level. We use a method based on the technique for order preference by similarity to an ideal solution to select a spreading factor. We use real data to show that the results reflect an acceptable increase in energy consumption while applying our selection method. In contrast, the results show that the selection method reduces the error rate especially for patients with a high critical level.

Lama Pengalaman Klinik Perawat Dengan Ketepatan Skoring Virulensi COVID-19 Menggunakan Aplikasi EWSS (Early Warning System Score)

Over time, the COVID-19 virus mutates and can spread rapidly, requiring more accurate treatment. Adequate treatment is essential for healing and reducing the spread of diseases. Moreover, nursing has become the main health workforce in controlling COVID-19. The study aims to test the relationship between nursing clinical experience and the accuracy of COVID-19 virulence scoring using the Early Warning System Score application. The study used a correlation analytic design with a cross sectional approach. The population used in this study was nurses who filled out questionnaires online in East Java. A sample of 311 respondents. The results showed a significant relationship between nursing clinical experience and accuracy of scoring virulence of COVID-19 using the Early Warning System Score application. Treatment of COVID-19 should remain in the evaluation, especially the provision of appropriate nursing care for patients with COVID-19 by nurses. Researchers can add clinical experience-supporting variables to find out the various compensators of nurses’ competence.

Prognostic value of early warning scores in patients presenting to the emergency department with exacerbation of COPD.

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is acondition that frequently presents to the emergency department (ED) and its prognosis is not very well understood. Risk tools that can be used rapidly in the ED are needed to predict the prognosis of these patients. This study comprised aretrospective cohort of AECOPD patients presenting to asingle center between 2015 and 2022. The prognostic accuracy of several clinical early warning scoring systems, Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), NEWS‑2, Systemic Inflammatory Response Syndrome (SIRS) and the quick Sepsis-related Organ Failure Assessment (qSOFA), were compared. The outcome variable was determined as one-month mortality. Of the 598patients, 63(10.5%) had died within 1month after presenting to the ED. Patients who died had more often congestive heart failure, altered mental status, and admission to intensive care, and they were older. Although the MEWS, NEWS, NEWS‑2, and qSOFA scores of those who died were higher than those who survived, there was no difference between the SIRS scores of these two groups. The score with the highest positive likelihood ratio for mortality estimation was qSOFA (8.5, 95% confidence interval [CI] 3.7-19.6). The negative likelihood ratios of the scores were similar, the NEWS score had anegative likelihood ratio of 0.4 (95% CI 0.2-0.8) with the highest negative predictive value of 96.0%. In AECOPD patients, most of the early warning scores that are frequently used in the ED were found to have amoderate ability to exclude mortality and alow ability to predict mortality.

Anzhen Risk Evaluation System for Acute Aortic Syndrome (AZSCORE-AAS): protocol for a multicentre prospective cohort study in northern China

IntroductionAcute aortic syndrome (AAS) is a group of acute and critical conditions, including acute aortic dissection (AAD), acute intramural haematoma and penetrating aortic ulcer. High mortality and morbidity rates result...

NURSE-LED proactive rounding and automatic early-warning score systems to prevent resuscitation incidences among Adults in ward-based Hospitalised patients

ObjectivesIn this study, we investigated the impact of critical care outreach implemented to overcome the problem of rapid response system (RRS) activation. The aim was to evaluate the impact of nurse-led proactive rounding on the rate of adverse events in a hospital setting using an automatic early-warning score system, without a call-activated team. MethodsThis observational study was conducted at a university hospital in Japan. Beginning in September 2019, critical care outreach via nurse-led proactive rounding of the general ward was conducted, using an automatic early-warning score system. We retrospectively assessed the computerised records of all inpatient days (N = 497,284) of adult inpatients admitted to the hospital from September 2017 to 2020. We compared the adverse event occurrences before and after implementation of the critical care outreach program. The main outcome measures were: unexpected death in the general ward, code blue (an in-hospital resuscitation request code directed towards all staff via broadcast) for non-intensive care unit inpatients and unexpected intensive care unit admissions from the general ward. The secondary outcome was the proportion of patients who received respiratory rate measurement. ResultsThe incidence rate ratios of the occurrence of unexpected deaths (0.19, 95% confidence interval: 0.04–0.57) and code blue in the general ward (0.15, 95% confidence interval: 0.025–0.50) decreased. There was no change in unexpected intensive care unit admissions from the general ward (1.25, confidence interval: 0.84–1.82). The proportion of patients who received respiratory rate measurement increased (10.2% vs 16.2%). ConclusionOur results suggest that in RRSs, drastic control of the failure of the mechanism to activate a response team may produce positive outcomes. Proactive rounding that bypasses the mechanism to activate a response team component of RRSs may relieve ward nurses of activation failure responsibility and help them overcome the hierarchical hospital structure.

Reliability and validity of Chengdu pediatric emergency triage criteria: case study of a single center in China

BackgroundWe aimed to examine the reliability and validity of Chengdu pediatric emergency triage criteria in order to provide a reference for the development of pediatric emergency triage within other hospitals.MethodsWe developed Chengdu pediatric emergency triage criteria based on the conditions/symptom, vital signs, and the Pediatric Early Warning Score system within our hospital using the Delphi method in 2020. The simulation scenario triage and real-life triage which were conducted in our hospital during January - March 2021, and the retrospective study of triage records extracted from our hospital’s health information system in February 2022, were used to measure the agreement in triage decisions between the triage nurses, and between the triage nurses and the expert team.ResultsFor the 20 simulation cases, the Kappa value of triage decisions between the triage nurses was 0.6 (95% CI 0.352–0.849), and the Kappa value of triage decisions between the triage nurses and the expert team was 0.73 (95% CI 0.540–0.911). For the 252 cases in the real-life triage, the Kappa value of triage decisions between the triage nurses and the expert team was 0.824 (95% CI 0.680–0.962). For the 20,540 cases selected for the retrospective study of triage records, the Kappa value of triage decisions between the triage nurses was 0.702 (95% CI 0.691–0.713); that between Triage Nurse 1 and the expert team was 0.634 (95% CI 0.623–0.647); and that between Triage Nurse 2 and the expert team was 0.725 (95% CI 0.713–0.736). The overall agreement rate in triage decisions between the triage nurses and the expert team in the simulation scenario triage was 80%; that between the triage nurses and the expert team in the real-life triage was 97.6%; and that between the triage nurses in the retrospective study was 91.9%. In the retrospective study, the agreement rates in triage decisions between Triage Nurse 1 and the expert team, and between Triage Nurse 2 and the expert team, were 88.0% and 92.3%, respectively.ConclusionChengdu pediatric emergency triage criteria that developed within our hospital is reliable and valid, and can promote rapid and effective triage by triage nurses.

Performance of Early Warning Scoring Systems Regarding Adverse Events of Unanticipated Clinical Deterioration in Complementary and Alternative Medicine Hospitals

PurposeThis study aims to examine the performance of early warning scoring systems regarding adverse events of unanticipated clinical deterioration in complementary and alternative medicine hospitals. MethodsA medical record review of 500 patients from 5-year patient data in two traditional Korean medicine hospitals was conducted. Unanticipated clinical deterioration events included unexpected in-hospital mortality, cardiac arrest, and unplanned transfers to acute-care conventional medicine hospitals. Scores of the Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), and National Early Warning Score 2 (NEWS2) were calculated. Their performance was evaluated by calculating areas under the receiver-operating characteristic curve for the event occurrence. Multiple logistic regression analyses were performed to determine the factors associated with event occurrence. ResultsThe incidence of unanticipated clinical deterioration events was 1.1% (225/21101). The area under the curve of MEWS, NEWS, and NEWS2 was .68, .72, and .72 at 24 hours before the events, respectively. NEWS and NEWS2, with almost the same performance, were superior to MEWS (p = .009). After adjusting for other variables, patients at low-medium risk (OR = 3.28; 95% CI = 1.02–10.55) and those at medium and high risk (OR = 25.03; 95% CI = 2.78–225.46) on NEWS2 scores were more likely to experience unanticipated clinical deterioration than those at low risk. Other factors associated with the event occurrence included frailty risk scores, clinical worry scores, primary medical diagnosis, prescribed medicine administration, acupuncture treatment, and clinical department. ConclusionsThe three early warning scores demonstrated moderate-to-fair performance for clinical deterioration events. NEWS2 can be used for early identification of patients at high risk of deterioration in complementary and alternative medicine hospitals. Additionally, patient, care, and system factors need to be considered to improve patient safety.

Clinical Study of a New Modified Early Warning Scoring System for Rapidly Evaluating Shock in Adults.

Shock is one of the most common severe syndromes requiring emergency treatment. Acute myocardial infarction guidelines, the surviving sepsis campaign, and low blood volume resuscitation guidelines indicate the prioritization ofearly identification of shock. APACHE II(Acute Physiology and Chronic Health Evaluation II), SOFA (Sequential Organ Failure Assessment), and MEWS (Modified Early Warning System) scores are used to predict mortality in ICU (intensive care unit) patients. However, similar to APACHE II, SOFA cannot be used forrapid assessment. Hence the need for a new scoring system that is simple, faster, and efficacious in predicting and preventing mortality among shock patients. The present study was conducted to evaluate a new MEWS scoring system for early identification and estimate mortality risk in patients with shock. A total of 170 patients with shock meeting the inclusion criteria who presented to the ICU of Ramaiah Hospitals from November 2019 to August 2021 were included in the study. Baseline variables, laboratory parameters, APACHE II score, SOFA score, MEWS score, and new MEWS score were compared between the two groups. Patients were followed up till mortality or discharge from ICU. Among the 170 patients included in the studyseptic shock (69.4%) was the most common type of shock followed by cardiogenic(7.64%) and hypovolemic shock (7.64%). The requirement of inotropic support and mechanical ventilation was associated with significantly higher mortality (55.6% and 52.6% respectively). The AUROC (area under the curve) for SOFA in predicting mortality was 0.738 (p<0.001). The AUROCfor APACHE II score in predicting mortality was 0.758 (p<0.001). The AUROC for MEWS score in predicting mortality was 0.655 (p=0.0002). The AUROC for the new MEWS score in predicting mortality was 0.684 which is more than that of the conventional MEWS score (p <0.001). New MEWS score is better than the MEWS score in predicting mortality. The new MEWS score is a simple, entirely clinical, inexpensive scoring system that can be done within a short time as a patient contact in an emergency. Hence, the new MEWS score can help in the quick identification of patients who are at high risk for developing shock and can be used as a better predictor of mortality.

Evaluation of a Paediatric Early Warning System (PEWS) score on admission to a paediatric intensive care unit to predict mortality risk in a low resource setting, Guinea-Bissau

The Paediatric Early Warning System (PEWS) is a clinical monitoring tool used routinely in emergency and observation rooms to detect rapid deterioration in paediatric patients, allowing timely action

The value of Pediatric Early Warning Score combined with SBAR in neonatal pneumonia nursing: A retrospective cohort study.

To observe the effect of the Pediatric Early Warning System (PEWS) score combined with the situation-background-assessment-recommendation (SBAR) shift communication system in neonates with severe pneumonia in the pediatric intensive care unit. A total of 230 neonates admitted to the pediatric intensive care unit of our hospital from January 2018 to January 2021 were enrolled in this study. Participants were divided into an experimental group (110 patients, PEWS score combined with SBAR shift communication system) and a control group (120 patients, routine diagnosis and treatment and shift change). The early recognition rate, incidence of handover problems, and prognosis of critically ill children in the 2 groups were analyzed. Compared to the control group, the correct recognition rate of disease observation and early recognition rate of critically ill children in the experimental group were significantly higher, and the incidence of handover problems was significantly lower (P < .05). There was no significant difference in the incidence of asphyxia, heart failure, and toxic encephalopathy between both groups. The application of the PEWS score combined with the SBAR shift communication system can facilitate timely identification of deterioration of the condition of children with severe pneumonia, reduce handover problems, and help to implement interventions or rescue according to the changes in a patient's condition, which may be beneficial in improving the patient's prognosis.

Effect of Digital Early Warning Scores on Hospital Vital Sign Observation Protocol Adherence: Stepped-Wedge Evaluation.

Early warning scores (EWS) are routinely used in hospitals to assess a patient's risk of deterioration. EWS are traditionally recorded on paper observation charts but are increasingly recorded digitally. In either case, evidence for the clinical effectiveness of such scores is mixed, and previous studies have not considered whether EWS leads to changes in how deteriorating patients are managed. This study aims to examine whether the introduction of a digital EWS system was associated with more frequent observation of patients with abnormal vital signs, a precursor to earlier clinical intervention. We conducted a 2-armed stepped-wedge study from February 2015 to December 2016, over 4 hospitals in 1 UK hospital trust. In the control arm, vital signs were recorded using paper observation charts. In the intervention arm, a digital EWS system was used. The primary outcome measure was time to next observation (TTNO), defined as the time between a patient's first elevated EWS (EWS ≥3) and subsequent observations set. Secondary outcomes were time to death in the hospital, length of stay, and time to unplanned intensive care unit admission. Differences between the 2 arms were analyzed using a mixed-effects Cox model. The usability of the system was assessed using the system usability score survey. We included 12,802 admissions, 1084 in the paper (control) arm and 11,718 in the digital EWS (intervention) arm. The system usability score was 77.6, indicating good usability. The median TTNO in the control and intervention arms were 128 (IQR 73-218) minutes and 131 (IQR 73-223) minutes, respectively. The corresponding hazard ratio for TTNO was 0.99 (95% CI 0.91-1.07; P=.73). We demonstrated strong clinical engagement with the system. We found no difference in any of the predefined patient outcomes, suggesting that the introduction of a highly usable electronic system can be achieved without impacting clinical care. Our findings contrast with previous claims that digital EWS systems are associated with improvement in clinical outcomes. Future research should investigate how digital EWS systems can be integrated with new clinical pathways adjusting staff behaviors to improve patient outcomes.

MORTALITY PROFILE AND ITS CORRELATION WITH BPEWS SCORE IN PEDIATRIC INTENSIVE CARE UNIT OF TERTIARY CARE CENTRE

Introduction: The care of critically ill children remains one of the most demanding and challenging aspects in the field of Pediatrics. In spite of availability of well-equipped Pediatric Intensive Care Units (PICU), deaths do occur. Aims/objective:To study the mortality profiles and its correlation to the Bedside Pediatric Early Warning System Score (BPEWS) in children who expired within 48 hours of admission.Inclusion criteria:children aged1 month to 12 years who expired within 48 hours of admission in PICU of a tertiary care center.Methods:Approval from the institutional ethics committee was obtained prior to commencement of the study.Retrospective data of consecutive children aged 1 month to 12 years who expired within 48 hours, was collected from the hospital's Medical Records Section. The variables necessary for BPEWS Score calculator were noted and the BPEWS Score was calculated. Result: 84% patients were below five years of age with mean age of 2.6 year and 57% were females. Mean duration of stay was 19.68 hours. Mean distance from health facility was 8.31 km. Respiratory system was affected in the majority of patients (47%). More than forty percent of children were undernourished. Mean BPEWS score was 17.36 in the age group of 1 to 5 year, which depicts poor outcome. Conclusion: Majority of early deaths (within 48hrs) occurred in patients less than five years of age.Higher BPEWS (&gt;8) was associated with shorter duration of stay of patients and poor outcome

A retrospective and comparative study between quick sequential organ failure assessment, CURB-65, and early warning scorings in COVID-19 patients to predict the disease severity and outcome

Background: Predicting the severity of COVID-19 infection in advance is the key to success of its treatment outcome. Various scoring systems are used to detect the severity of this disease but this study targets three simple scoring systems based on the vital parameters and basic routine laboratory tests. Aims and Objectives: The aim of the study was to assess the predictability of three scoring systems (Quick sequential organ failure assessment [q SOFA], CURB-65, and Early Warning scoring system) for disease severity at presentation in a rural-based tertiary care center. Materials and Methods: An observational, descriptive, retrospective, and cross-sectional study was conducted at Diamond Harbour Government Medical College Covid Hospital from January 2021 to January 2022 to assess the predictability of q SOFA, CURB-65, and Early Warning scoring system for disease severity at presentation. Results: The total number of participants was 561 among total admitted 1367 patients. A short descriptive analysis obtained from the variables to analyze the scorings howed among total sample collected, 57% were male and 43% were female. In this study, 87% of patients were survived and the rest 13% succumbed (death). There is no statistically significant difference in mortality between both genders. Age, pulse rate, and respiratory rate have a significant correlation with the outcome and altered sensorium is also highly associated with mortality. The accuracy was also found to be little higher for National Early Warning score (NEWS) score than CURB-65 scoring and q SOFA scoring (0.919, 0.914 and 0.907). Although all the scoring systems have high sensitivity (&gt;90%) (CURB 65: Most sensitive [0.99]), the specificities of all three scoring systems are below 50%. Among these three-scoring systems, NEWS showed the highest specificity (0.492) than q SOFA (0.423) and CURB 65 (0.394). Conclusion: We suggest NEWS score and CURB-65 as a better predictor for in-hospital mortality in COVID-19 patients as it is significantly sensitive and reasonably specific. It can be recommended in less equipped hospitals where only basic laboratory facilities are available. qSOFA can be utilized where no laboratory facility is available like in safe home and isolation centers.

Implementation of Early Warning Scoring System (EWSS) to Improve ‘ICU without Walls’

Implementation of Early Warning Scoring System (EWSS) to Improve ‘ICU without Walls’