A proposed ABCD scoring system for patient’s self assessment and at emergency department with symptoms of COVID-19

Salunke, Abhijeet Ashok; Pathak, Subodh Kumar; Dhanwate, Anant Dattatray; Warikoo, Vikas; Nandy, Kunal; Mendhe, Harshal; Kottakota, Viswanth; Shinde, Rahul Madhukar; Patil, Shubham Ashok; Petiwala, Tehsin; Pandya, Shashank

doi:10.1016/j.dsx.2020.07.053

Cited by 9 publications

(7 citation statements)

References 6 publications

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“…Risk factors for mortality in COVID-19 reported in various studies included advanced age [ 2 – 13 ], male gender [ 6 , 7 , 9 , 11 , 13 ] and comorbidities [ 3 , 5 , 6 , 9 – 16 ] like diabetes mellitus, obesity, systemic hypertension, renal diseases, coronary artery disease [ 12 ] and malignancy. Apart from manifestations such as fever [ 8 ], cough [ 8 ], haemoptysis [ 2 ], dyspnoea [ 2 , 6 , 8 ], fatigue [ 8 ], loss of consciousness [ 2 , 6 ], laboratory parameters such as elevation of Neutrophil-to-Lymphocyte Ratio (NLR) [ 2 , 15 ], and increased levels of creatinine [ 3 ], lactate dehydrogenase (LDH) [ 2 – 4 , 10 , 12 ], direct bilirubin [ 2 ] and alanine aminotransferase [ 3 ], which provide early clues to the severity of disease, an increased plasma level of biomarkers like D-dimer [ 3 – 5 , 12 ], C-Reactive Protein (CRP) [ 6 , 7 ], serum ferritin [ 3 ], Interleukin-6 (IL-6) [ 3 ], and procalcitonin (PCT) fortifies these findings[ 3 – 5 ]. With the efficacy of specific antiviral and targeted immunomodulatory therapy still remaining elusive, prediction of mortality and risk stratification offers a rational approach for health resources allocation.…”

Section: Introductionmentioning

confidence: 99%

Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India

Narendran

Senthil²,

Prabakar³

et al. 2022

PLoS ONE

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Background We retrospectively data-mined the case records of Reverse Transcription Polymerase Chain Reaction (RT-PCR) confirmed COVID-19 patients hospitalized to a tertiary care centre to derive mortality predictors and formulate a risk score, for prioritizing admission. Methods and findings Data on clinical manifestations, comorbidities, vital signs, and basic lab investigations collected as part of routine medical management at admission to a COVID-19 tertiary care centre in Chengalpattu, South India between May and November 2020 were retrospectively analysed to ascertain predictors of mortality in the univariate analysis using their relative difference in distribution among ‘survivors’ and ‘non-survivors’. The regression coefficients of those factors remaining significant in the multivariable logistic regression were utilised for risk score formulation and validated in 1000 bootstrap datasets. Among 746 COVID-19 patients hospitalised [487 “survivors” and 259 “non-survivors” (deaths)], there was a slight male predilection [62.5%, (466/746)], with a higher mortality rate observed among 40–70 years age group [59.1%, (441/746)] and highest among diabetic patients with elevated urea levels [65.4% (68/104)]. The adjusted odds ratios of factors [OR (95% CI)] significant in the multivariable logistic regression were SaO2<95%; 2.96 (1.71–5.18), Urea ≥50 mg/dl: 4.51 (2.59–7.97), Neutrophil-lymphocytic ratio (NLR) >3; 3.01 (1.61–5.83), Age ≥50 years;2.52 (1.45–4.43), Pulse Rate ≥100/min: 2.02 (1.19–3.47) and coexisting Diabetes Mellitus; 1.73 (1.02–2.95) with hypertension and gender not retaining their significance. The individual risk scores for SaO2<95–11, Urea ≥50 mg/dl-15, NLR >3–11, Age ≥50 years-9, Pulse Rate ≥100/min-7 and coexisting diabetes mellitus-6, acronymed collectively as ‘OUR-ARDs score’ showed that the sum of scores ≥ 25 predicted mortality with a sensitivity-90%, specificity-64% and AUC of 0.85. Conclusions The ‘OUR ARDs’ risk score, derived from easily assessable factors predicting mortality, offered a tangible solution for prioritizing admission to COVID-19 tertiary care centre, that enhanced patient care but without unduly straining the health system.

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Section: Introductionmentioning

confidence: 99%

Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India

Narendran

Senthil²,

Prabakar³

et al. 2022

PLoS ONE

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“…4 ]. In a study by Salunke et al [ 28 ], a simple scale of ABCD was proposed to assess Covid-19 patients presenting at the emergency department.…”

Section: Resultsmentioning

confidence: 99%

Clinical Audit on Symptomatology of Covid-19 Healthcare Workers and Impact on Quality-of-Life (QOL) Due to Continuous Facemask Usage: A Prospective Study

Radhakrishnan

Sudarsan

Raj

et al. 2021

Indian J Otolaryngol Head Neck Surg

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Covid-19 due to Sars-Cov-2 infection has reached pandemic proportion. Many healthcare workers are involved in managing both COVID-suspected and confirmed cases. It is mandatory for healthcare workers to have droplet and contact precautions by means of Personal protective equipment (PPE), facemask, face shield or eye protection. Prolonged usage of medical mask results in various adverse effects. This study is an attempt to know the common effects of prolonged face mask in healthcare workers and its resultant quality-of-life (QOL). To study the common effects of prolonged face mask and its impact on QOL of healthcare workers during the COVID 19 crisis. This was a prospective cross-sectional study conducted over 6 months among 2750 healthcare workers. A questionnaire requesting demographic details and most common side effects after prolonged usage of face mask was circulated. We also attached a short form-12 (sf-12) questionnaire to assess its impact on QOL. Out of 2750 personnel, 299 were excluded. Male preponderance was noted. Study was conducted on candidates using 3ply mask or above. Age range was between 18 and 65 years with mean age being 37.61 ± 15.23 in mask users < 5 h per day, 32.2 ± 10.02 in 5–10 h group and 30.19 ± 8.15 in 10 h group. 8.48% (n = 174) had comorbidities. QOL impacted. The complaints with face mask use definitely are troublesome with increase in severity with duration of mask usage. This definitely has a proportional impact on the healthcare workers’ QOL.

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“…Research has been done in the field of triage of COVID-19 patients. The study conducted by Salunke et al revealed the use of variables such as age, body temperature, cough and underlying diseases in the triage system (9). In another study, apart from the mentioned variables, patients' blood pressure was also considered (10).…”

Section: Discussionmentioning

confidence: 99%

The proposed scoring system for hospitalization or discharge of patients with COVID-19

Noori

Vahedian

Rezvan

et al. 2021

J Emerg Pract Trauma

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Objective: Since the outbreak of coronavirus disease 2019 (COVID-19), the triage of patients diagnosed with corona virus has been a very important issue. The aim of this study was to introduce a triage scoring system according to the clinical and para-clinical findings of patients in order to be admitted or discharged with COVID-19. Methods: After confirming the positive polymerase chain reaction (PCR) test for patients, we used a scoring system which included: the age of patient (less than 40 years and>40 years), early vital signs at the time of admission, lab tests including C-reactive protein (CRP), white blood count (WBC), lactate dehydrogenase (LDH), D-dimer, chest imaging findings, comorbidity and shortness of breath. Results: The clinical score obtained for each variable in this scoring system was a number between 0 and 3. The total score was a minimum of 0 and a maximum of 17. A higher score indicated an increase in the intensity and the need for intensive care. These scores were classified into 3 groups: 0-4, 5-10 and above 10. In the next stage, patients were divided into three groups: mild, moderate and severe. In this regard, patients with mild symptoms were suggested to receive home quarantine and home treatment, patients with moderate symptoms were recommended hospitalization and medical care, and finally patients with severe symptoms were inclined to intensive care. Conclusion: In order to treat and manage patients with COVID-19, it is necessary to pay particular attention to clinical and para-clinical findings and prioritize these findings based on the severity and the condition of patients.

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A proposed ABCD scoring system for patient’s self assessment and at emergency department with symptoms of COVID-19

Cited by 9 publications

References 6 publications

Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India

Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India

Clinical Audit on Symptomatology of Covid-19 Healthcare Workers and Impact on Quality-of-Life (QOL) Due to Continuous Facemask Usage: A Prospective Study

The proposed scoring system for hospitalization or discharge of patients with COVID-19

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