Volume 9, Issue 4 pp. 1648-1655
ORIGINAL ARTICLE
Open Access

Ferritin level: A predictor of severity and mortality in hospitalized COVID-19 patients

Moudhi Alroomi

Moudhi Alroomi

Department of Infectious Diseases, Infectious Diseases Hospital, Shuwaikh Medical Area, Kuwait City, Kuwait

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Rajesh Rajan

Corresponding Author

Rajesh Rajan

Department of Cardiology, Sabah Al Ahmad Cardiac Centre, Al Amiri Hospital, Kuwait City, Sharq, Kuwait

Correspondence

Rajesh Rajan, Department of Cardiology, Sabah Al Ahmed Cardiac Centre, Al Amiri Hospital, Kuwait City 15303, Kuwait.

Email: [email protected]

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Abdulaziz A. Omar

Abdulaziz A. Omar

Department of Medicine, Jaber Al Ahmed Hospital, South Surra, Kuwait

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Ahmad Alsaber

Ahmad Alsaber

Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom

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Jiazhu Pan

Jiazhu Pan

Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom

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Mina Fatemi

Mina Fatemi

Public Health and Commissioning Manager, Nottinghamshire County Council, Nottingham, United Kingdom

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Prof Kobalava D. Zhanna

Prof Kobalava D. Zhanna

Department of Internal Medicine with the Subspecialty of Cardiology and Functional Diagnostics Named after V.S. Moiseev, Peoples' Friendship University of Russia (RUDN University), Moscow, Russian Federation

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Wael Aboelhassan

Wael Aboelhassan

Division of Gastroenterology, Department of Medicine, Jaber Al Ahmed Hospital, South Surra, Kuwait

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Farah Almutairi

Farah Almutairi

Department of Medicine, Farwaniya Hospital, Farwaniya, Kuwait

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Naser Alotaibi

Naser Alotaibi

Department of Medicine, Al Adan Hospital, Hadiya, Kuwait

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Mohammad A. Saleh

Mohammad A. Saleh

Department of Medicine, Farwaniya Hospital, Farwaniya, Kuwait

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Noor AlNasrallah

Noor AlNasrallah

Department of Medicine, Al Adan Hospital, Hadiya, Kuwait

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Bader Al-Bader

Bader Al-Bader

Department of Medicine, Farwaniya Hospital, Farwaniya, Kuwait

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Haya Malhas

Haya Malhas

Department of Emergency Medicine, Mubarak Al-Kabeer Hospital, Jabriya, Kuwait

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Maryam Ramadhan

Maryam Ramadhan

Department of Obstetrics and Gynaecology, Maternity Hospital, Shuwaikh Medical Area, Kuwait City, Kuwait

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Mohammed Abdullah

Mohammed Abdullah

Department of Infectious Diseases, Infectious Diseases Hospital, Shuwaikh Medical Area, Kuwait City, Kuwait

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Hassan Abdelnaby

Hassan Abdelnaby

Department of Endemic and Infectious Diseases, Faculty of Medicine, Suez Canal University, Ismailia, Egypt

Division of Gastroenterology, Department of Medicine, Al Sabah Hospital, Shuwaikh Medical Area, Kuwait City, Kuwait

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First published: 26 August 2021
Citations: 26

Аbstrасt

Introduction

This study aims to investigate in-hоsрitаl mоrtаlity in severe асute resрirаtоry syndrоme соrоnаvirus 2 раtients strаtified by serum ferritin levels.

Methods

Patients were stratified based on ferritin levels (ferritin levels ≤ 1000 or >1000).

Results

Approximately 89% (118) of the patients with ferritin levels > 1000 had pneumonia, and 51% (67) had hypertension. Fever (97, 73.5%) and shortness of breath (80, 61%) were two major symptoms among the patients in this group. Logistic regression analysis indicated that ferritin level (odds ratio [OR] = 0.36, 95% confidence interval [CI] = 0.21–0.62; p < .001), male sex (OR = 2.63, 95% CI = 1.43–5.06; p = .003), hypertension (OR = 4.16, 95% CI = 2.42–7.36; p < .001) and pneumonia (OR = 8.48, 95% CI = 3.02–35.45; p < .001) had significance in predicting in-hospital mortality. Additionally, the Cox proportional hazards analysis and Kaplan–Meier survival probability plot showed a higher mortality rate among patients with ferritin levels > 1000.

Conclusion

In this study, higher levels of serum ferritin were found to be an independent predictor of in-hоsрitаl mоrtаlity.

1 INTRОDUСTIОN

In severe асute resрirаtоry syndrоme соrоnаvirus 2 (SARS-CoV-2) risk assessment, ferritin can be used as a biomarker to assess severity and mortality.1, 2 In SARS-CoV-2 infection, cytokine storms are interlinked with elevated levels of ferritin. High ferritin levels can cause pro-inflammatory changes and immunosuppression.3 It was found that most diabetic SARS-CoV-2 patients who were critically ill had higher levels of ferritin.4 Many studies have shown doubling of the ferritin level in elderly individuals, especially when they are older than 65 years compared to those aged younger than 50 years.5 A multicentre study of SARS-CoV-2 infection reported a higher incidence of acute respiratory distress syndrome (ARDS), and increased morbidity was associated with higher hyperferritinemia.6

2 METHОDS

This study consisted of соnfirmed SАRS-СоV-2-infeсted раtients, bоth Kuwаitis аnd nоn-Kuwаitis, аged 18 and older. Patients were enrolled in this retrоsрeсtive соhоrt study between February 26 and September 8, 2020. All dаtа were obtained frоm eleсtrоniс mediсаl reсоrds frоm twо tertiаry саre hоsрitаls in Kuwаit: Jаber Аl-Аhmed Hоsрitаl аnd Аl Аdаn Generаl Hоsрitаl.7, 8

SАRS-СоV-2 infeсtiоn wаs соnfirmed by а роsitive Reverse Transcription Polymerase Chain Reaction (RT-РСR) swаb frоm the nаsорhаrynx. Cаre оf аll раtients wаs stаndаrdized ассоrding tо a рrоtосоl established by the Ministry оf Heаlth in Kuwаit. The stаnding соmmittee fоr сооrdinаtiоn оf heаlth аnd mediсаl reseаrсh аt the Ministry оf Heаlth in Kuwаit wаived the requirement оf infоrmed соnsent and аррrоved the study (Institutional Review Board number 2020/1422).

The primary outcome measured wаs SАRS-СоV-2 relаted deаth as defined by IСD-10 соde U07.1. The clinical and laboratory variables collected were as follows: sосiоdemоgrарhiс determinants, со-mоrbidities, сliniсаl рresentаtiоn, lаbоrаtоry results, аnd durаtiоns оf intensive care unit (IСU) аnd in-hоsрitаl stay. Аn eleсtrоniс саse-reсоrd fоrm (СRF) wаs used fоr dаtа entry.

2.1 Stаtistiсаl аnаlysis

Descriptive statistics were used to summarize the data in the form of frequency, percentage, mean ± standard deviation (SD), and median ± interquartile range (IQR). Differences in patients with respect to study variables in the ferritin group were examined using the Pearson χ2 test. Logistic regression analysis was employed to check the effects of some study variables on cumulative all-cause mortality. The Cox proportional hazards regression model and Kaplan–Meier survival were used to check how ferritin affected the mortality level. A 5% significance level was used to test the results. Statistical analyses were performed using SPSS version 27 (SPSS) and R software.9

3 RESULTS

The basic characteristics of the patients affected by SARS-CoV-2 are shown in Table 1. A total of 595 patients were considered in the study, among whom 132 had an average age of 56.5 ± 14.8 years and ferritin levels > 1000, and 463 had an average age of 53.3 ± 15.4 years and ferritin levels ≤ 1000. Most of the male (255, 55.1%) and female (208, 44.9%) patients had ferritin levels ≤ 1000. Communities (236, 46.9%) and contacts (232, 46.1%) were two major sources of transmission of SARS-CoV-2 among patients. Most of the patients with ferritin levels ≤ 1000 had pneumonia (295, 63.7%), followed by hypertension (180, 38.9%), ARDS (69, 14.9%), and chronic kidney disease (22, 4.7%). Among the cohort with ferritin levels > 1000, approximately 67 (50.8%) patients had to be admitted to the ICU, and the median time of discharge of patients in this cohort was 18.0 [2.00; 59.5] days, whereas 68 (14.7%) patients in the cohort with ferritin levels ≤ 1000 had to be admitted to the ICU, and the median time of discharge of patients in this cohort was 14.0 [2.38; 51.6] days. Almost equal numbers of patients died in the cohorts with ferritin levels > 1000 (39, 29.5%) and ferritin levels ≤ 1000 (40, 8.6%).

Table 1. Baseline characteristics of COVID-19 patients stratified by ferritin level
[ALL] Ferritin > 1000 Ferritin ≤ 1000
N = 595 N = 132 N = 463 p N
Age, mean ± SD, years 54.0 (15.3) 56.5 (14.8) 53.3 (15.4) .029 595
BMI, mean ± SD, kg/m2 29.5 (6.25) 29.3 (6.68) 29.6 (6.12) .684 408
Sex <.001 595
Female 233 (39.2%) 25 (18.9%) 208 (44.9%)
Male 362 (60.8%) 107 (81.1%) 255 (55.1%)
Smoking .780 205
Current smoker 21 (10.2%) 6 (9.84%) 15 (10.4%)
Ex-smoker 25 (12.2%) 6 (9.84%) 19 (13.2%)
Never smoked 159 (77.6%) 49 (80.3%) 110 (76.4%)
Source of transmission .049 503
Community 236 (46.9%) 46 (44.7%) 190 (47.5%)
Contact 232 (46.1%) 51 (49.5%) 181 (45.2%)
Healthcare worker 9 (1.79%) 0 (0.00%) 9 (2.25%)
Hospital acquired 10 (1.99%) 5 (4.85%) 5 (1.25%)
Imported 16 (3.18%) 1 (0.97%) 15 (3.75%)
Hypertension 247 (41.5%) 67 (50.8%) 180 (38.9%) .019 595
DM 260 (43.7%) 49 (37.1%) 211 (45.6%) .104 595
CVD 56 (9.41%) 17 (12.9%) 39 (8.42%) .168 595
Chronic lung disease 68 (11.4%) 16 (12.1%) 52 (11.2%) .898 595
Chronic kidney disease 35 (5.88%) 13 (9.85%) 22 (4.75%) .047 595
Immunocompromised host 14 (2.35%) 5 (3.79%) 9 (1.94%) .207 595
Pneumonia 413 (69.4%) 118 (89.4%) 295 (63.7%) <.001 595
ARDS 126 (21.2%) 57 (43.2%) 69 (14.9%) <.001 595
ICU admission 135 (22.7%) 67 (50.8%) 68 (14.7%) <.001 595
ICU duration of stay (number of days) IQR 14.0 [2.00;64.8] 11.0 [2.00;59.0] 16.0 [1.70;74.8] .058 137
Admission to discharge (number of days) IQR 15.0 [2.00;57.0] 18.0 [2.00;59.5] 14.0 [2.38;51.6] <.001 587
Mortality 79 (13.3%) 39 (29.5%) 40 (8.64%) <.001 595
  • Note: n (%) unless specified otherwise.
  • Abbreviations: ARDS, acute respiratory distress syndrome; BMI, body mass index; CVD, cardiovascular disease; DM, diabetes mellitus; ICU, intensive care unit; IQR, interquartile range; SD, standard deviation.

Most of the patients in the cohort with ferritin levels ≤ 1000 had either asymptomatic infection (41, 8.8%) or had symptoms of fever (287, 62%), shortness of breath (SOB; 182, 39.3%), fatigue or myalgia (137, 29.6%), and headache (61, 13.2%), whereas most of the patients in the cohort with ferritin levels > 1000 had fever (97, 73.5%), followed by SOB (80, 60.6%), fatigue or myalgia (25, 18.9%), and headache (5, 3.7%; Table 2).

Table 2. Signs and symptoms of COVID-19 patients stratified by ferritin level
[ALL] Ferritin > 1000 Ferritin ≤ 1000
N = 595 N = 132 N = 463 p N
Asymptomatic 44 (7.39%) 3 (2.27%) 41 (8.86%) .018 595
Headache 66 (11.1%) 5 (3.79%) 61 (13.2%) .004 595
Sore throat 48 (8.07%) 8 (6.06%) 40 (8.64%) .436 595
Fever 384 (64.5%) 97 (73.5%) 287 (62.0%) .020 595
Dry cough 322 (54.1%) 67 (50.8%) 255 (55.1%) .436 595
Productive cough 44 (7.39%) 11 (8.33%) 33 (7.13%) .781 595
SOB 262 (44.0%) 80 (60.6%) 182 (39.3%) <.001 595
Fatigue or myalgia 162 (27.2%) 25 (18.9%) 137 (29.6%) .021 595
Diarrhoea 80 (13.4%) 18 (13.6%) 62 (13.4%) 1.000 595
Nausea 47 (7.90%) 9 (6.82%) 38 (8.21%) .735 595
Vomiting 49 (8.24%) 8 (6.06%) 41 (8.86%) .395 595
Change of taste or smell 19 (3.19%) 4 (3.03%) 15 (3.24%) 1.000 595
  • Note: n (%) unless specified otherwise.
  • Abbreviation: SOB, shortness of breath.

Table 3 compares the laboratory parameters among patients with ferritin levels > 1000 or ferritin levels ≤ 1000. Patients with ferritin levels > 1000 had significantly higher counts of white blood cells (9.30 [8.00;10.6], p < .001) and neutrophils (7.50 [6.50;8.85], p < .001) and higher levels of creatinine (92.0 [85.0;105], p < .001), LDH (437 [410;470], p < .001), CRP (125 [104;163], p < .001), PCT (0.50 [0.30;0.90], p < .001), d-dimer (750 [514;1027], p < .001), serum troponin HS (22.0 [15.0;39.0], p < .001), creatinine kinase (343 [32.0;3147], p < .037), ALT (46.5 [40.0;61.8], p < .001), AST (55.0 [49.0;61.0], p < .001), GGT (68.0 [50.0;90.0], p < .001), T. bilirubin (13.6 [12.2;15.6], p < .001) and D. bilirubin (4.20 [3.70;5.40], p < .001) as compared to the patients with ferritin levels ≤ 1000. Furthermore, patients with ferritin levels ≤ 1000 had significantly higher haemoglobin levels (121 [119;124], p = .001), lymphocyte counts (1.30 [1.17;1.40], p < .001), vitamin D levels (42.0 [37.0;48.0], p = .007) and albumin levels (35.0 [34.0;35.5], p < .001) than patients with ferritin levels > 1000.

Table 3. Laboratory findings of COVID-19 patients grouped by ferritin level (ng/ml)
[ALL] Ferritin > 1000 Ferritin ≤ 1000
N = 593 N = 132 N = 463 p N
Haemoglobin (g/L) 119 [116;122] 106 [93.0;117] 121 [119;124] .001 592
Platelets (109/L) 257 [242;271] 265 [229;292] 254 [237;271] .319 592
WBC (109/L) 7.00 [6.80;7.40] 9.30 [8.00;10.6] 6.60 [6.20;6.90] <.001 590
Neutrophils count 4.90 [4.50;5.21] 7.50 [6.50;8.85] 4.20 [4.00;4.70] <.001 589
Lymphocytes count 1.20 [1.10;1.30] 1.00 [0.80;1.11] 1.30 [1.17;1.40] <.001 589
Creatinine (µmol/L) 79.0 [76.0;82.0] 92.0 [85.0;105] 76.0 [72.0;79.0] <.001 593
LDH (IU/L) 320 [304;339] 437 [410;470] 285 [272;306] <.001 545
CRP (mg/L) 76.0 [69.7;81.0] 125 [104;163] 65.0 [53.0;74.0] <.001 575
Procalcitonin (ng/ml) 0.16 [0.14;0.20] 0.50 [0.30;0.90] 0.11 [0.09;0.15] <.001 354
d-Dimer (ng/ml) 388 [337;429] 750 [514;1027] 314 [271;362] <.001 498
25 (OH) Vitamin D (nmol/L) 38.0 [35.0;45.0] 30.0 [25.0;41.0] 42.0 [37.0;48.0] .007 130
Troponin I HS (ng/L) 10.0 [8.00;14.0] 22.0 [15.0;39.0] 8.00 [7.00;10.0] <.001 284
Creatinine kinase (IU/L) 84.5 [56.0;208] 343 [32.0;3147] 59.5 [49.0;101] .037 26
ALT (IU/L) 35.0 [32.0;37.0] 46.5 [40.0;61.8] 31.0 [29.0;34.0] <.001 588
AST (IU/L) 39.0 [36.0;42.0] 55.0 [49.0;61.0] 34.0 [32.0;38.0] <.001 587
ALP (IU/L) 73.0 [70.0;76.0] 77.5 [68.0;89.0] 73.0 [70.0;75.0] .077 585
GGT (IU/L) 47.0 [42.0;55.0] 68.0 [50.0;90.0] 44.0 [39.0;51.0] <.001 477
Albumin (g/L) 34.0 [33.2;34.9] 30.0 [28.6;31.7] 35.0 [34.0;35.5] <.001 587
T. Bilirubin (µmol/L) 11.0 [10.6;11.8] 13.6 [12.2;15.6] 10.4 [9.70;11.0] <.001 586
D. Bilirubin (µmol/L) 3.00 [2.70;3.10] 4.20 [3.70;5.40] 2.50 [2.30;2.70] <.001 574
  • Note: Numerical variables – median ± interquartile range (IQR).
  • Abbreviations: ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; COVID-19, coronavirus disease 2019; CRP, C-reactive protein; D. bilirubin, direct bilirubin; GGT, gamma-glutamyl transferase; HS, high-sensitivity; LDH, lactate dehydrogenase; T. bilirubin, total bilirubin; WBC, white blood cell.

More patients with ferritin levels ≤ 1000 received antibiotics (252, 54.4%), followed by therapeutic anticoagulation (177, 38.2%), methylprednisolone (88, 19%), Hydroxychloroquine (HCQ; 54, 11.7%), and KALETRA (lopinavir/ritonavir; 61, 13.2%), than patients with ferritin levels > 1000; conversely, more patients with ferritin levels > 1000 received Actemra (Tocilizumab; 10, 7.5%) and azithromycin (8, 6%). Furthermore, it is also noticeable that among the cohort with ferritin levels ≤ 1000, approximately 49% (204) of patients had no requirement for oxygen, 36% (153) had a low oxygen requirement and 15% (64) had a high oxygen requirement, whereas the cohort with ferritin levels > 1000, approximately 14% (18) of patients had no requirement for oxygen, 39% (50) had a low oxygen requirement and 47% (61) had a high oxygen requirement (Table 4).

Table 4. Medications taken by the COVID-19 patients stratified by ferritin level
[ALL] Ferritin > 1000 Ferritin ≤ 1000
N = 595 N = 132 N = 463 p N
Antibiotics 359 (60.3%) 107 (81.1%) 252 (54.4%) <.001 595
Methylprednisolone 128 (21.5%) 40 (30.3%) 88 (19.0%) .008 595
Dexamethasone 66 (11.1%) 17 (12.9%) 49 (10.6%) .559 595
Vitamin C effervescent tablets 332 (55.8%) 75 (56.8%) 257 (55.5%) .866 595
Therapeutic anticoagulation 270 (45.4%) 93 (70.5%) 177 (38.2%) <.001 595
Azithromycin 12 (2.02%) 8 (6.06%) 4 (0.86%) .001 595
Vitamin D 184 (30.9%) 43 (32.6%) 141 (30.5%) .720 595
HCQ 84 (14.1%) 30 (22.7%) 54 (11.7%) .002 595
KALETRA (lopinavir/ritonavir) 93 (15.6%) 32 (24.2%) 61 (13.2%) .003 595
Actemra (Tocilizumab) 17 (2.86%) 10 (7.58%) 7 (1.51%) .001 595
Hydrocortisone 18 (3.03%) 5 (3.79%) 13 (2.81%) .567 595
a. Receiving ace inhibitors 66 (14.3%) 21 (19.4%) 45 (12.7%) .109 463
b. Receiving ARBs 83 (18.0%) 16 (15.2%) 67 (18.8%) .494 462
c. Receiving statin 170 (34.7%) 39 (34.5%) 131 (34.7%) 1.000 490
Oxygen requirements <.001 550
High oxygen requirement 125 (22.7%) 61 (47.3%) 64 (15.2%)
Low oxygen requirements 203 (36.9%) 50 (38.8%) 153 (36.3%)
None 222 (40.4%) 18 (14.0%) 204 (48.5%)
  • Note: n (%) unless specified otherwise.
  • Abbreviations: ACE, angiotensin-converting enzyme; ARB, angiotensin II receptor blocker; HCQ, hydroxychloroquine.

Logistic regression analysis showed that ferritin level, sex, hypertension, and pneumonia were significant predictors of all-cause cumulative mortality. It is evident that patients with ferritin levels ≤ 1000 (odds ratio [OR] = 0.36, 95% confidence interval [CI] = 0.21–0.62; p < .001) were 0.36 times less likely to have all-cause cumulative mortality than patients with ferritin levels > 1000. Additionally, the mortality rate was higher among male patients (OR = 2.63, 95% CI = 1.43–5.06; p = .003) and those with hypertension (OR = 4.16, 95% CI = 2.42–7.36; p < .001) or pneumonia (OR = 8.48, 95% CI = 3.02–35.45; p < .001); Table 5).

Table 5. Multivariate logistic regression analysis of in-hospital death in the overall study cohort
In-hospital mortality Alive Dead

Univariate

 aOR (95% CI, aP-value)

Multivariate logistic regression

 aOR (95% CI, aP-value)

Ferritin level ≤1000 423 (91.4) 40 (8.6) 0.23 (0.14–0.37, p < .001) 0.36 (0.21–0.62, p < .001)
Sex Male 299 (82.6) 63 (17.4) 2.86 (1.65–5.24, p < .001) 2.63 (1.43–5.06, p = .003)
Hypertension Yes 191 (77.3) 56 (22.7) 4.14 (2.50–7.07, p < .001) 4.16 (2.42–7.36, p < .001)
Pneumonia Yes 337 (81.6) 76 (18.4) 13.46 (4.93–55.44, p < .001) 8.48 (3.02–35.45, p < .001)
  • Note: Multivariable analyses were conducted using logistic regression models utilizing the simultaneous method. The models were adjusted for ferritin levels, gender, hypertension, and pneumonia. Percents are row percentages.
  • Abbreviations: aOR, adjusted odds ratio; aP-value, adjusted p-value; CI, confidence interval.

A Cox proportional hazards analysis was conducted to determine whether ferritin had a significant effect on the hazard of mortality (Table 6). The findings (LL = 9.85, df = 1, p = .002) show that ferritin was able to adequately predict the hazard of mortality. It is evident that at any particular time, patients with ferritin levels ≤ 1000 had a hazard that was 0.49 times as large as that of patients with ferritin levels > 1000 (B = −0.72, SE = 0.23, HR = 0.49, p = .001).

Table 6. Cox proportional hazards regression coefficients for ferritin
Variable B SE 95% CI z p HR
Ferritin Less than or equal 1000 −0.72 0.23 [−1.17, −0.28] −3.18 .001 0.49

A Kaplan–Meier survival probability plot was also included for ferritin. The plot represents the survival probabilities for different groups over time and shows that in the initial and later periods, the cumulative probability of dying was higher among patients with ferritin levels > 1000, but in the middle period, little difference was observed in the mortality rate of patients in the different ferritin groups (Figure 1).

Details are in the caption following the image
Kaplan–Meier survival plot of mortality grouped by fertility

4 DISСUSSIОN

The main finding of our study is that the higher mortality rate among patients having ferritin levels > 1000. Other than ferritin levels gender, hypertension and pneumonia were found to be a predictor of in-hospital mortality. Around 89% of the patients having ferritin levels > 1000 had pneumonia and 51% had hypertension. The mean age of the patients was 54.0 ± 15.3 years and among which the ratio of male to female was 233:362. A male predominance was noted in the group with ferritin levels > 1000. Higher levels of C-Reactive Protein and Procalcitonin were seen in ferritin > 1000.

Serum ferritin was found to be an independent predictor of severe SARS-CoV-2 disease.10 A study from Indonesia Rasyid et al. documented a mean ferritin level of 1689 in critically ill SARS-CoV-2-infected patients.11 SARS-CoV-2 patients with cytokine storm were also found to have significantly higher levels of ferritin.12 Several autopsies of SARS-CoV-2 patients revealed higher ferritin levels.13 Elderly SARS-CoV-2 patients with elevated ferritin levels showed higher mortality than those with lower ferritin values.11 In another study, the incidence of ARDS was higher in those with hyperferritinemia.14 Zhou et al. also reported increased mortality in SARS-CoV-2 patients with higher levels of serum ferritin.15 Elevated ferritin levels can be used as a biomarker to stratify high-risk patients from low-risk patients, which may in turn help in the early identification and management of SARS-CoV-2 patients.16 Hyperferritinemia was more common in critically ill and discharged SARS-CoV-2 patients than in stable hospitalized patients.17

Unlike our study, hypertensive SARS-CoV-2 patients had lower levels of serum ferritin, as reported by Huang et al.18 Similar to our study, a study by Phipps et al.19 showed that the severity of acute liver failure in SARS-CoV-2 patients was more common in patients with hyperferritinemia. The frequency of ICU admission was higher in SARS-CoV-2 patients with hyperferritinemia.20 Similar findings were also reported in our study. In another study, SARS-CoV-2 patients with cancer had higher serum ferritin levels than those without cancer.21 The clinical association of hyperferritinemia in SARS-CoV-2 in terms of mortality, comorbidities, and severity was well established in a meta-analysis.22

5 LIMITATIONS

Our study has various limitations. Its retrospective design limits causal inference. Unmeasured confounding factors, such as clinical comorbidities and medications, could have affected the outcomes. This Kuwaiti study included all SARS-CoV-2-positive patients and undoubtedly consisted of mainly milder cases of the disease. However, if it included SARS-CoV-2 patients who typically consist of a significant case mix of mechanically ventilated and critical cases of patients, the findings might have looked different.

6 CОNСLUSIОNS

This study demonstrated that hyperferritinemia is an independent predictor of in-hоsрitаl mоrtаlity in SARS-CoV-2 patients. The incidence of ICU admission was higher with hyperferritinemia. More prospective studies are required to better understand hyperferritinemia and in-hospital mortality in SARS-CoV-2.

CONFLICT OF INTERESTS

The authors declare that there are no conflict of interests.

AUTHOR CONTRIBUTIONS

Moudhi Alroomi designed the study. Moudhi Alroomi and Rajesh Rajan раrtiсiраted in аnаlysis аnd mаnusсriрt рreраrаtiоn. Ahmad Alsaber, Jiazhu Pan, and Mina Fatemi performed the stаtistiсаl аnаlysis and reviewed the mаnusсriрt. Аll аuthоrs hаd ассess tо the dаtа аnd tаke resроnsibility fоr its integrity аnd the ассurасy оf the dаtа аnаlysis. Аll аuthоrs hаve reаd аnd аррrоved the mаnusсriрt.

DATA AVAILABILITY STATEMENT

The data that support the results of the study are available on request from the corresponding author.

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