| چکیده انگلیسی مقاله |
The cumulative rate of death of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has necessitated better recognizing the risk factors of the disease and the COVID-19-induced mortality. This cross-sectional study aimed to determine the potential risk factors that predict COVID-19-related mortality concentrating on the initial recorded laboratory tests. We extracted admission’s medical records of a total of 136 deaths related to COVID-19 and 272 discharged adult inpatients (≥18 years old) related to four referral centers from February 24th to April 12th, 2020, in Isfahan, Iran, to figure out the relationship between the laboratory findings and mortality beyond demographic and clinical findings. We applied the independent sample t test and a chichi square test with SPSS software to compare the differences between the survivor and non-survivor patients. A P value of less than 0.05 was considered significant. Our results showed that greater length of hospitalization (P≤0.001), pre-existing chronic obstructive pulmonary disease (P≤0.001), high pulse rate, hypoxia (P≤0.001), and high computed tomography scan score (p < 0.001), in addition to high values of some laboratory parameters, increase the risk of mortality. Moreover, high neutrophil/lymphocyte ratio (OR, 1.890; 95% CI, 1.074-3.325, P=0.027), increased creatinine levels (OR, 15.488; 95% CI, 0.801-299.479, P=0.07), and elevated potassium levels (OR, 13.400; 95% CI, 1.084-165.618, P=0.043) independently predicted in-hospital death related to COVID-19 infection. These results emphasized the potential role of impaired laboratory parameters for the prognosis of fatal outcomes in adult inpatients. |
| کلیدواژههای انگلیسی مقاله |
COVID-19, Risk factors, Mortality, Medical laboratory science, What&,rsquo s Known The increasing growth of COVID-19-related mortality has highlighted the need to recognize the risk factors associated with severe COVID-19 infection. Recent epidemiological studies have investigated the relationship between various risk factors and the fatal risk of COVID-19. There is a lack of well-documented data regarding the association between impaired laboratory parameters and mortality risks related to COVID-19 infection. What&,rsquo s New We identified certain clinical risk factors, including a history of chronic obstructive pulmonary disease COPD, hypoxia during hospitalization, and initial computed tomography scan (CT) scores, which independently increase the odds of COVID-19-related mortality. We provided an independent COVID-19-related mortality prediction model based on the initial recorded laboratory tests on the data of multi-center hospitals. IntroductionThe outbreak of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a threat to global public health. 1, In general, due to the rapid spread of COVID-19 through human-to-human communication, the prevalence is currently on an increasing trend. In this regard, the WHO&,rsquo s latest global data recorded, as of 14 March 2021, just about 141.5 million confirmed cases of COVID-19. 2, Additionally, recent statistics determined that in the Middle East, a high death rate of COVID-19 cases was observed in Iran (58.61%) and Turkey (30.86%). 3, Furthermore, The COVID-19 epidemic model predicted mortality of 11.7% of in-hospital mortality in patients with COVID-19 using a case-control study in Isfahan. 4, , 5, These outcomes highlighted the need to better recognize the risk factors associated with severe COVID-19 infection. 6, Recently, studies have specified that the average COVID-19-related deaths have been found in the older population and male gender. 7, Additionally, released epidemiological data by the Centers of Disease Control and Prevention (CDC) has revealed that several pre-existing comorbidities, including cardiovascular disease, hypertension, diabetes, respiratory disease, and cancers, are related to increased fatality risk. 8, In addition to the clinical and epidemiological characteristics, fluctuations in laboratory parameters are recently reported in COVID-19 to affect patients and have worse outcomes. 9, However, limited data are focusing on laboratory parameters beyond the epidemiology and clinical features of patients in the prognosis of COVID-19-related mortality. This short report aimed to determine the potential risk factors that predict COVID-19-related mortality concentrating on the initial recorded laboratory tests based on the data of multi-center population-based cohort study.MethodsThis cross-sectional study was conducted to determine the potential risk factors that predict COVID-19-related mortality. Therefore, we obtained the medical recorded information of 136 death cases caused by COVID-19 (&,ge 18 years old) related to four referral centers from February 24th to April 12th, 2020, in Isfahan, Iran. To determine the relationship between the demographic, clinical, and laboratory findings and mortality, we analyzed the medical information of 272 discharged inpatients and compared it to the information of those, who experienced death in the hospital. Similar to previous studies, the diagnosis of COVID-19 relied on positive real-time reverse transcriptase-polymerase chain reaction (RT-PCR). 9, , 10, Investigators extracted demographic characteristics, medical history, pre-existing comorbidities, laboratory findings, and clinical outcomes on admission. Written informed consent was obtained from all the patients. This study was approved by the Research Ethics Committee of Isfahan University of Medical Sciences (IR.MUI.MED.REC.1399.680). Statistical AnalysisWe utilized an independent sample t test for continuous data and a Chi square test for categorical data to compare the differences between the survivor and non-survivor patients considering a P value&,lt 0.05 as statistically significant using SPSS (IBM SPSS Statistics 20.0). Continuous and categorical variables were presented as mean&,plusmn SD and number (%), respectively. Univariable and multivariable logistic regression models were employed to explore the potential risk factors associated with mortality. To analyze the association between the laboratory findings with mortality in patients affected by COVID-19, we categorized these according to previous studies. ResultsTable 1, represents the details of baseline characteristics of survivor (n=272) and non-survivor patients (n=136). A total of 408 cases (210 women and 198 men) were included in this study. Compared with the survived patients, those who experienced death were 55-70 years (P&,lt 0.001) and men (P&,lt 0.001). They also tended to have a higher mean length of patients&,rsquo hospital stay (P&,lt 0.001) and a long duration of symptoms onset, the average duration of hospital admission until the onset of symptoms, (P=0.005). Moreover, univariate analysis identified that comorbidities, including hypertension (P&,lt 0.001), diabetes (P&,lt 0.001), COPD (P&,lt 0.001), chronic kidney disease (P=0.007), heart failure (P=0.013), and hyperlipoproteinemia (P=0.024) were significantly different between the two groups. These results are in accordance with those derived from a previous study, which might be on account of the higher prevalence of medical problems in the mentioned disease. 6, Having dyspnea (P&,lt 0.001), diarrhea (P&,lt 0.001), and chills (P&,lt 0.001) were the main clinical death-related symptoms. Furthermore, some laboratory findings and global CT scores remained significantly different between the two groups. As presented in table 2,, the logistic model indicated that a history of COPD, hypoxia, and CT scores increased the odds of COVID-19 mortality. In the multivariate analysis, we also observed that pre-existing pulmonary disease was associated with the risk of mortality. Patients characteristicsTotal (n=408) N (%)Survived (n=272) N (%)Dead (n=136)P valueDemographicsAge &,lt 3539 (9.6)36 (13.2)3 (2.2)&,lt 0.00135-55111 (27.2)104 (38.2)7 (5.1)56-70137 (33.6)93 (34.2)44 (32.4)&,gt 70121 (29.7)39 (14.3)82 (60.3)SexFemale 210 (51.5)163 (59.9)47 (34.6)&,lt 0.001Male198 (48.53)109 (40.07)89 (65.44)Hospital length of stay (days)9.65 (5.17)9.01 (5.22)10.39 (5.04)&,lt 0.001Duration of symptom&,rsquo s onset to hospital admission (days)6.99 (4.78)7.47 (4.72)5.99 (4.77)0.004ComorbiditiesHypertension 158 (38.8)82 (30.1)76 (56.3)&,lt 0.001Heart failure 13 (3.2)4 (1.5)9 (6.6)0.013Chronic obstructive pulmonary disease 43 (10.5)12 (4.4)31 (22.8)&,lt 0.001Diabetes 130 (31.9)68 (25.0)62 (45.9)&,lt 0.001Cancer 12 (2.9)5 (1.8)7 (5.2)0.069Chronic kidney disease 25 (6.1)10 (3.7)15 (11.1)0.007Hyperlipoproteinemia58 (14.3)31 (11.4)27 (20.0)0.024Vital SymptomsChest Pain 74 (20.7)64 (29.0)10 (7.4)&,lt 0.001Sore Throat 77 (21.0)56 (24.2)21 (15.4)0.047Cough 324 (79.8)218 (80.7)106 (77.9)0.515Shortness of Breath 299 (74.8)179 (67.8)120 (88.2)&,lt 0.001Nausea 122 (32.2)98 (40.3)24 (17.6)&,lt 0.001Vomiting 85 (22.3)61 (24.9)24 (17.6)0.123Diarrhea 69 (18.4)61 (25.6)8 (5.9)&,lt 0.001Headache 126 (34.4)103 (44.8)23 (16.9)&,lt 0.001Chills 246 (62.3)194 (74.9)52 (38.2)&,lt 0.001Weakness Fatigue188 (52.1)150 (66.7)38 (27.9)&,lt 0.001Fever Degree (&,deg C)37.66 (0.99)37.61 (0.99)37.76 (1.01)0.153Fever Degree &,gt 38.5 &,deg C66 (16.5)42 (15.8)24 (17.9)0.669Vital Signs (on triage)Systolic blood pressure (mm Hg)128.67(20.01)129.72 (17.75)126.44 (24.04)0.173Diastolic blood pressure (mm Hg)79.18 (34.69)81.87 (40.73)73.48 (13.84)0.024Peripheral capillary oxygen saturation (SpO2) 87.48 (9.37)90.70 (5.37)80.98 (11.99)&,lt 0.001Pulse Rate &,gt 100 119 (29.3)78 (28.9)41 (30.1)0.818Global CT Score (mean&,plusmn SD)10.76 (5.44)9.64 (4.84)13.64 (5.87)&,lt 0.001Data are presented as number (%), mean&,plusmn SD. Independent sample t test was used for continuous variables and Chi square test was used for categorical variables. Level of statistical significance=0.05. N, Number CT, Computed tomography SpO2, Peripheral capillary oxygen saturation |
| نویسندگان مقاله |
Ramin Sami |
Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
Mohammad-Reza Hajian |
Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
Babak Amra |
Bamdad Respiratory and Sleep Research Center, Department of Internal Medicine, Pulmonary and Sleep Ward, Isfahan University of Medical Sciences, Isfahan, Iran
Forogh Soltaninejad |
Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
Marjan Mansourian |
Pediatric Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
Sam Mirfendereski |
Department of Radiology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
Raheleh Sadegh |
Department of Community and Prevention Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
Nilufar Khademi |
Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
Soheila Jalali |
Department of Epidemiology and Biostatistics, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
Nafiseh Shokri-Mashhadi |
Department of Clinical Nutrition, School of Nutrition and Food Sciences, Isfahan University of Medical Sciences, Isfahan, Iran
|