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Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care-An experience from South India.
Gopalan, Narendran; Senthil, Sumathi; Prabakar, Narmadha Lakshmi; Senguttuvan, Thirumaran; Bhaskar, Adhin; Jagannathan, Muthukumaran; Sivaraman, Ravi; Ramasamy, Jayalakshmi; Chinnaiyan, Ponnuraja; Arumugam, Vijayalakshmi; Getrude, Banumathy; Sakthivel, Gautham; Srinivasalu, Vignes Anand; Rajendran, Dhanalakshmi; Nadukkandiyil, Arunjith; Ravi, Vaishnavi; Hifzour Rahamane, Sadiqa Nasreen; Athur Paramasivam, Nirmal; Manoharan, Tamizhselvan; Theyagarajan, Maheshwari; Chadha, Vineet Kumar; Natrajan, Mohan; Dhanaraj, Baskaran; Murhekar, Manoj Vasant; Ramalingam, Shanthi Malar; Chandrasekaran, Padmapriyadarsini.
  • Gopalan N; Department of Clinical Research, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Senthil S; Department of General Medicine, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Prabakar NL; Department of General Medicine, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Senguttuvan T; Department of Clinical Research, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Bhaskar A; Department of Statistics, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Jagannathan M; Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Sivaraman R; MDRU, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Ramasamy J; Department of General Medicine, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Chinnaiyan P; Department of Statistics, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Arumugam V; Department of Microbiology, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Getrude B; Department of Community Medicine, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Sakthivel G; Department of General Medicine, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Srinivasalu VA; Department of Clinical Research, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Rajendran D; Department of Clinical Research, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Nadukkandiyil A; Division of Epidemiology and Operational Research, ICMR-Vector Control Research Centre, Puducherry, India.
  • Ravi V; Department of General Medicine, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Hifzour Rahamane SN; Department of General Medicine, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Athur Paramasivam N; Department of General Medicine, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Manoharan T; Department of General Medicine, Government Chengalpattu Medical College & Hospital, Chengalpattu, Tamil Nadu, India.
  • Theyagarajan M; Department of Statistics, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Chadha VK; Department of Clinical Research, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Natrajan M; Central Leprosy Teaching & Research Institute, Chengalpattu, Tamil Nadu, India.
  • Dhanaraj B; Department of Clinical Research, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Murhekar MV; Department of Clinical Research, ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Ramalingam SM; ICMR-National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Chennai, Tamil Nadu, India.
  • Chandrasekaran P; ICMR-National Institute of Epidemiology, Chennai, Tamil Nadu, India.
PLoS One ; 17(2): e0263471, 2022.
Article Dans Anglais | MEDLINE | ID: covidwho-1706281
ABSTRACT

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.
Sujets)

Texte intégral: Disponible Collection: Bases de données internationales Base de données: MEDLINE Sujet Principal: Soins de santé tertiaires / Mortalité hospitalière / SARS-CoV-2 / COVID-19 / Hospitalisation Type d'étude: Étude observationnelle / Étude pronostique Limites du sujet: Adulte / Adulte très âgé / Femelle / Humains / Mâle / Adulte d'âge moyen Pays comme sujet: Asie langue: Anglais Revue: PLoS One Thème du journal: Science / Médicament Année: 2022 Type de document: Article Pays d'affiliation: Journal.pone.0263471

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Texte intégral: Disponible Collection: Bases de données internationales Base de données: MEDLINE Sujet Principal: Soins de santé tertiaires / Mortalité hospitalière / SARS-CoV-2 / COVID-19 / Hospitalisation Type d'étude: Étude observationnelle / Étude pronostique Limites du sujet: Adulte / Adulte très âgé / Femelle / Humains / Mâle / Adulte d'âge moyen Pays comme sujet: Asie langue: Anglais Revue: PLoS One Thème du journal: Science / Médicament Année: 2022 Type de document: Article Pays d'affiliation: Journal.pone.0263471