How to Read a Systematic Review? Systematic Reviews and if included meta-analyses are in-depth reviews of a specific clinical question.? The systematic review contains the nar

Int J Clin Pract. 2021;75:e14675. wileyonlinelibrary.com/journal/ijcp  |  1 of 16 https://doi.org/10.1111/ijcp.14675

© 2021 John Wiley & Sons Ltd

Received: 12 January 2021  |  Accepted: 26 July 2021 DOI: 10.1111/ijcp.14675

ME TA – ­A N A LY S I S

Infectious­Diseases

The­role­of­vitamin­D­in­the­age­of­COVID-­19:­A­systematic­ review­and­meta-­analysis

Roya­Ghasemian1  |­­­Amir­Shamshirian2,3  |­­­Keyvan­Heydari3,4  |­­­ Mohammad­Malekan4  |­­­Reza­Alizadeh-­Navaei3  |­­­Mohammad­Ali­Ebrahimzadeh5  |­­­­ Majid­Ebrahimi­Warkiani6,7  |­­­Hamed­Jafarpour4  |­­­Sajad­Razavi­Bazaz6  |­­­ Arash­Rezaei­Shahmirzadi8 |­­­Mehrdad­Khodabandeh9 |­­­Benyamin­Seyfari10 |­­­ Alireza­Motamedzadeh11 |­­­Ehsan­Dadgostar12  |­­­Marzieh­Aalinezhad13  |­­­ Meghdad­Sedaghat14  |­­­Nazanin­Razzaghi8 |­­­Bahman­Zarandi15 |­­­Anahita­Asadi5 |­­­ Vahid­Yaghoubi­Naei16 |­­­Reza­Beheshti5 |­­­Amirhossein­Hessami2  |­­­Soheil­Azizi17  |­­­ Ali­Reza­Mohseni17,18  |­­­Danial­Shamshirian19

1Antimicrobial Resistance Research Center, Department of Infectious Diseases, Mazandaran University of Medical Sciences, Sari, Iran 2Department of Medical Laboratory Sciences, Student Research Committee, School of Allied Medical Science, Mazandaran University of Medical Sciences, Sari, Iran 3Gastrointestinal Cancer Research Center, Non- Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran 4Student Research Committee, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran 5Pharmaceutical Sciences Research Center, Department of Medicinal Chemistry, School of Pharmacy, Mazandaran University of Medical Science, Sari, Iran 6School of Biomedical Engineering, University of Technology Sydney, Sydney, Ultimo, NSW, Australia 7Institute of Molecular Medicine, Sechenov First Moscow State University, Moscow, Russia 8Student Research Committee, Golestan University of Medical Sciences, Gorgan, Iran 9Neuromusculoskeletal Research Center, Department of Physical Medicine and Rehabilitation, Iran University of Medical Sciences, Tehran, Iran 10Department of Surgery, Faculty of Medicine, Kashan University of Medical Sciences, Kashan, Iran 11Department of Internal Medicine, Faculty of Medicine, Kashan University of Medical Sciences, Kashan, Iran 12Department of Psychiatry, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran 13Department of Radiology, Isfahan University of Medical Sciences, Isfahan, Iran 14Department of Internal Medicine, Imam Hossein Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran 15Student Research Committee, Iran University of Medical Sciences, Tehran, Iran 16Immunology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran 17Department of Medical Laboratory Sciences, School of Allied Medical Science, Mazandaran University of Medical Sciences, Sari, Iran 18Thalassemia Research Center, Hemoglobinopathy Institute, Mazandaran University of Medical Sciences, Sari, Iran 19Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran

Correspondence Amir Shamshirian; Gastrointestinal Cancer Research Center, Mazandaran University of Medical Sciences, Sari, Iran. Email: [email protected]

Danial Shamshirian, Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran. Email: [email protected]

Abstract Background:­Evidence recommends that vitamin D might be a crucial supportive agent for the immune system, mainly in cytokine response regulation against COVID- 19. Hence, we carried out a systematic review and meta- analysis in order to maximise the use of everything that exists about the role of vitamin D in the COVID- 19.

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1 | INTRODUCTION

Following the emergence of a novel coronavirus from Wuhan, China, in December 2019, the respiratory syndrome coronavirus 2 (SARS- CoV- 2) has affected the whole world and is declared a pandemic by World Health Organisation (WHO) on March 26, 2020.1 According to Worldometer metrics, this novel virus has been responsible for approxi- mately 83,848,186 infections, of which 59,355,654 cases are recovered, and 1,826,530 patients have died worldwide up to January 01, 2021.

After months of medical communities’ efforts, one of the hottest topics is still the role of Vitamin D in the prevention or treatment of COVID- 19. Several functions, such as modulating the adaptive immune system and cell- mediated immunity, as well as an increase of antioxidative- related genes expression, have been proven for Vitamin D as an adjuvant in the prevention and treatment of acute respiratory infections.2- 4 According to available investigations, it seems that such functions lead to cytokine storm suppression and avoid Acute Respiratory Distress Syndrome (ARDS), which has been studied on other pandemics and infectious diseases in recent years.4- 7

To the best of our knowledge, unfortunately, after several months, there is no adequate high- quality data on different treatment regimens, which raise questions about gaps in scien- tific works. On this occasion, when there is an essential need for controlled randomised trials, it is surprising to see only observa- tional studies without a control group or non- randomised con- trolled studies with retrospective nature covering a small number of patients. The same issue is debatable for 25- hydroxyvitamin

D (25(OH)D); hence, concerning all of the limitations and analyse difficulties, we carried out a systematic review and meta- analysis to try for maximising the use of everything that exists about the role of this vitamin in the COVID- 19.

2  | METHODS

2.1 | Search­Strategy

The Preferred Reporting Items for Systematic Reviews and Meta- Analyses (PRISMA) guideline was considered for the study plan. A systematic search through databases of PubMed, Scopus, Embase and Web of Science was done up to December 18, 2020. Moreover,

Methods:­A systematic search was performed in PubMed, Scopus, Embase and Web of Science up to December 18, 2020. Studies focused on the role of vitamin D in con- firmed COVID- 19 patients were entered into the systematic review. Results:­Twenty- three studies containing 11 901 participants entered into the meta- analysis. The meta- analysis indicated that 41% of COVID- 19 patients were suffering from vitamin D deficiency (95% CI, 29%- 55%), and in 42% of patients, levels of vita- min D were insufficient (95% CI, 24%- 63%). The serum 25- hydroxyvitamin D concen- tration was 20.3 ng/mL among all COVID- 19 patients (95% CI, 12.1- 19.8). The odds of getting infected with SARS- CoV- 2 are 3.3 times higher among individuals with vi- tamin D deficiency (95% CI, 2.5- 4.3). The chance of developing severe COVID- 19 is about five times higher in patients with vitamin D deficiency (OR: 5.1, 95% CI, 2.6- 10.3). There is no significant association between vitamin D status and higher mortal- ity rates (OR: 1.6, 95% CI, 0.5- 4.4). Conclusion:­This study found that most of the COVID- 19 patients were suffering from vitamin D deficiency/insufficiency. Also, there is about three times higher chance of getting infected with SARS- CoV- 2 among vitamin- D- deficient individuals and about five times higher probability of developing the severe disease in vitamin- D- deficient patients. Vitamin D deficiency showed no significant association with mortality rates in this population.

Review­Criteria

Following database search, paper screening, data extrac- tion and quality assessment were done based on inclusion and exclusion criteria by independent researchers.

Message­for­the­Clinic

Our study demonstrated a significant association be- tween vitamin D deficiency/insufficiency and SARS- CoV- 2 infection, which can be helpful to consider in the clinical setting.

     |  3 of 16GHASEMIAN Et Al.

to obtain more data, we considered grey literature and references of eligible papers. The search strategy included all MeSH terms and free keywords found for COVID- 19, SARS- CoV- 2 and Vitamin D (Table S1). There was no time/location/language limitation in this search.

2.2 | Criteria­study­selection

Four researchers have screened and selected the papers inde- pendently, and the supervisor solved the disagreements. Studies met the following criteria included in the meta- analysis: 1) com- parative or non- comparative studies with retrospective or pro- spective nature; and 2) studies reported the role of vitamin D in confirmed COVID- 19 patients. Studies were excluded if they were: 1) in vitro studies, experimental studies, reviews, 2) dupli- cate publications.

2.3 | Data­extraction­and­quality­assessment

Two researchers (H.J and M.M) have evaluated the papers’ qual- ity assessment and extracted data from selected papers. The su- pervisor (D.Sh) resolved any disagreements in this step. The data extraction checklist included the name of the first author, pub- lication year, region of study, number of patients, comorbidity, vitamin D Status, serum 25- hydroxyvitamin D levels, ethnicity,

mean age, medication dosage, treatment duration, adverse ef- fects, radiological results and mortality. The Newcastle- Ottawa Scale (NOS) checklist8 and its modified version for cross- sectional studies9 and Jadad scale10 for randomised clinical trials were used to value the studies concerning various aspects of the methodol- ogy and study process.

2.4 | Vitamin D cut- off11

In this case, according to most of the studies, vitamin D cut- off points were considered as follows:

• Vitamin D sufficiency: 25(OH)D concentration greater than 30 ng/mL.

• Vitamin D insufficiency: 25(OH)D concentration of 20- 30 ng/mL. • Vitamin D deficiency: 25(OH)D level less than 20 ng/mL.

2.5 | Targeted­outcomes

(a) Frequency of Vitamin D status in COVID- 19 patients; (b) Mean 25(OH)D concentration; (c) Association between Vitamin D Deficiency and SARS- CoV- 2 infection; (d) Association between Vitamin D Deficiency and COVID- 19 severity; (e) Association between Vitamin D Deficiency and COVID- 19 mortality; (f) Comorbidity frequency; (g) Ethnicity frequency.

F IGURE ­1 PRISMA flow diagram for the study selection process

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TABLE ­1 Characteristics of studies entered into the systematic review

Study Country Study­design No.­of­patients­(cases)­ (male/female)

Controls­­­ (male/female)

Mean­(±SD) Median­(IQR)­age­of­­­ patients­(cases) Comorbidity­of­patients­(cases)

Vitamin­D­status­of­patients­(cases) Ethnicity­of­patients­(cases)

Quality­scoreb N I D CS AC O

Im et al81 South Korea Case- control study 50 150 57.5 (34.5- 68.0) — 13 — 37 — — — 7/9

Maghbooli et al82 Iran Retrospective cross sectional 235 — 58.72 (±15.2) *mean Diabetes: 86 Hypertension: 104 Respiratory disease: 72 Cancer: 2

77 — — — — — 7/10

Baktash et al83 UK Prospective cohort study 70 (42/28) — ≥65 Hypertension: 34 Diabetes mellitus: 26 Ischaemic heart disease: 15 Chronic respiratory disease: 13 Heart failure: 12 Stroke: 9 Dementia: 6 CKD: 16 Atrial fibrillation: 14 Cancer: 3 Endocrinological disease: 3

31 — 39 50 — 20 9/10

Meltzer et al84 US Retrospective cohort study 71 — — Hypertension:261 Diabetes:137 COPD:117 Pulmonary circulation disorders: 20 Depression: 119 CKD:116 Liver disease: 56 Comorbidities with immunosuppression: 105

39 — 32 — — — 9/10

Faul et al85 Ireland Retrospective cross sectional 33 (33/0) — ≥40 — 21 — 12 33 — — 5/10

Merzon et al86 Israel Case- control study 782 (385/397) 7025 (2849, 4176)

35.58 Depression/Anxiety: 73 Schizophrenia: 15 Dementia: 27 Diabetes mellitus: 154 Hypertension: 174 Cardiovascular disease: 78 Chronic lung disorders: 66 Obesity: 235

79 598 105 — — — 6/9

Panagiotou et al87 UK Retrospective cross sectional 134 (73/61) — — Hypertension: 56 Diabetes: 38 Obesity: 14 Malignancy: 15 Respiratory: 42 Cardiovascular disease: 20 Kidney and Liver diseases: 19

— — 44 132 1 1 6/10

Carpagnano et al88

Italy Retrospective cohort study 42 (30/12) — 65 (±13) *mean Hypertension: 26 Cardiovascular disease: 16 CKD: 16 Diabetes type II: 11 Cerebrovascular disease: 5 Psychosis, depression, anxiety: 10 Malignancy: 5 COPD: 5 Asthma: 2

8 11 23 — — — 8/9

Nicola et al89 Italy Retrospective cohort study 112 (52/60) — 47.2 (±16.4) — — — — — — — 6/9

Macaya et al90 Spain Retrospective cohort study 80 (35/45) — 67.65 (50- 84) Hypertension: 50 Diabetes mellitus: 32 Cardiac disease: 19

— — 45 — — — 7/9

(Continues)

     |  5 of 16GHASEMIAN Et Al.

TABLE ­1 Characteristics of studies entered into the systematic review

Study Country Study­design No.­of­patients­(cases)­ (male/female)

Controls­­­ (male/female)

Mean­(±SD) Median­(IQR)­age­of­­­ patients­(cases) Comorbidity­of­patients­(cases)

Vitamin­D­status­of­patients­(cases) Ethnicity­of­patients­(cases)

Quality­scoreb N I D CS AC O

Im et al81 South Korea Case- control study 50 150 57.5 (34.5- 68.0) — 13 — 37 — — — 7/9

Maghbooli et al82 Iran Retrospective cross sectional 235 — 58.72 (±15.2) *mean Diabetes: 86 Hypertension: 104 Respiratory disease: 72 Cancer: 2

77 — — — — — 7/10

Baktash et al83 UK Prospective cohort study 70 (42/28) — ≥65 Hypertension: 34 Diabetes mellitus: 26 Ischaemic heart disease: 15 Chronic respiratory disease: 13 Heart failure: 12 Stroke: 9 Dementia: 6 CKD: 16 Atrial fibrillation: 14 Cancer: 3 Endocrinological disease: 3

31 — 39 50 — 20 9/10

Meltzer et al84 US Retrospective cohort study 71 — — Hypertension:261 Diabetes:137 COPD:117 Pulmonary circulation disorders: 20 Depression: 119 CKD:116 Liver disease: 56 Comorbidities with immunosuppression: 105

39 — 32 — — — 9/10

Faul et al85 Ireland Retrospective cross sectional 33 (33/0) — ≥40 — 21 — 12 33 — — 5/10

Merzon et al86 Israel Case- control study 782 (385/397) 7025 (2849, 4176)

35.58 Depression/Anxiety: 73 Schizophrenia: 15 Dementia: 27 Diabetes mellitus: 154 Hypertension: 174 Cardiovascular disease: 78 Chronic lung disorders: 66 Obesity: 235

79 598 105 — — — 6/9

Panagiotou et al87 UK Retrospective cross sectional 134 (73/61) — — Hypertension: 56 Diabetes: 38 Obesity: 14 Malignancy: 15 Respiratory: 42 Cardiovascular disease: 20 Kidney and Liver diseases: 19

— — 44 132 1 1 6/10

Carpagnano et al88

Italy Retrospective cohort study 42 (30/12) — 65 (±13) *mean Hypertension: 26 Cardiovascular disease: 16 CKD: 16 Diabetes type II: 11 Cerebrovascular disease: 5 Psychosis, depression, anxiety: 10 Malignancy: 5 COPD: 5 Asthma: 2

8 11 23 — — — 8/9

Nicola et al89 Italy Retrospective cohort study 112 (52/60) — 47.2 (±16.4) — — — — — — — 6/9

Macaya et al90 Spain Retrospective cohort study 80 (35/45) — 67.65 (50- 84) Hypertension: 50 Diabetes mellitus: 32 Cardiac disease: 19

— — 45 — — — 7/9

(Continues)

6 of 16  |     GHASEMIAN Et Al.

Study Country Study­design No.­of­patients­(cases)­ (male/female)

Controls­­­ (male/female)

Mean­(±SD) Median­(IQR)­age­of­­­ patients­(cases) Comorbidity­of­patients­(cases)

Vitamin­D­status­of­patients­(cases) Ethnicity­of­patients­(cases)

Quality­scoreb N I D CS AC O

Karahan et al91 Turkey Retrospective cohort study 149 (81/68) — 63.5 (±15.3) Coronary artery disease: 32 Hypertension: 85 Dyslipidaemia: 39 Diabetes mellitus: 61 Cerebrovascular accident: 9 COPD: 15 Malignancy: 23 CKD: 29 Chronic atrial fibrillation: 15 Congestive heart failure: 18 Acute kidney injury: 16

12 34 103 — — — 8/9

Abdollahi et al92 Iran Case- control study 201 (66/135) 201 (66/135) 48 (±16.95) Hypothyroidism: 15 Diabetes mellitus: 42 Splenectomy: 1 Heart failure and hypertension: 20 Respiratory infections: 14 Autoimmune diseases: 11 AIDS: 4

39 161 1 — — — 7/9

Arvinte et al93 US Prospective cohort study (pilot study)

21 (15/6) — 60.2 (±17.4) 61 (20- 94)

— — — — 4 — 17 6/9

Cereda et al94 Italy Prospective cohort study 129 (70/59) — 77 (65.0- 85.0) COPD: 16 Diabetes: 39 Hypertension: 89 Ischaemic heart disease: 52 Cancer: 27 CKD: 24

— 30a  99 — — — 7/9

Hamza et al95 Pakistan Randomised controlled trial study

168 (94/74) — 42.26 (±13.69) — 22 47 98 — — — 3/5

Hernandez et al96 Spain Case- control study 19 (7/12) 197 (123/74) 60.0 (59.0- 75.0) Hypertension: 12 Diabetes: 0 Cardiovascular disease: 3 COPD: 2 Active cancer: 0 Immunosuppression: 6

— — — — — — 7/9

Jain et al97 India Prospective cohort study 154 (95/69) — 46.05 (±8.8) — — — 90 — — — 8/9

Ling et al98 UK Retrospective cohort study 444 (245/199) — 74 (63- 83) Diabetes mellitus: 129 COPD: 100 Asthma: 52 IHD: 73 ACS: 48 Heart failure: 54 Hypertension: 197 TIA: 40 Dementia: 59 Obesity: 20 Malignancy of solid organ: 71 Malignancy of skin: 8 Haematological malignancy: 8 Solid organ transplant: 4 Inflammatory arthritis: 16 Inflammatory bowel disease: 5

63 80 87 386 5 53 8/9

Luo et al99 China Retrospective cross- sectional study

335 (148/187) 560 (257/303) 56.0 (43.0- 64.0) Comorbidity status: 147 — — 218 — — — 7/10

TABLE ­1  (Continued)

(Continues)

     |  7 of 16GHASEMIAN Et Al.

Study Country Study­design No.­of­patients­(cases)­ (male/female)

Controls­­­ (male/female)

Mean­(±SD) Median­(IQR)­age­of­­­ patients­(cases) Comorbidity­of­patients­(cases)

Vitamin­D­status­of­patients­(cases) Ethnicity­of­patients­(cases)

Quality­scoreb N I D CS AC O

Karahan et al91 Turkey Retrospective cohort study 149 (81/68) — 63.5 (±15.3) Coronary artery disease: 32 Hypertension: 85 Dyslipidaemia: 39 Diabetes mellitus: 61 Cerebrovascular accident: 9 COPD: 15 Malignancy: 23 CKD: 29 Chronic atrial fibrillation: 15 Congestive heart failure: 18 Acute kidney injury: 16

12 34 103 — — — 8/9

Abdollahi et al92 Iran Case- control study 201 (66/135) 201 (66/135) 48 (±16.95) Hypothyroidism: 15 Diabetes mellitus: 42 Splenectomy: 1 Heart failure and hypertension: 20 Respiratory infections: 14 Autoimmune diseases: 11 AIDS: 4

39 161 1 — — — 7/9

Arvinte et al93 US Prospective cohort study (pilot study)

21 (15/6) — 60.2 (±17.4) 61 (20- 94)

— — — — 4 — 17 6/9

Cereda et al94 Italy Prospective cohort study 129 (70/59) — 77 (65.0- 85.0) COPD: 16 Diabetes: 39 Hypertension: 89 Ischaemic heart disease: 52 Cancer: 27 CKD: 24

— 30a  99 — — — 7/9

Hamza et al95 Pakistan Randomised controlled trial study

168 (94/74) — 42.26 (±13.69) — 22 47 98 — — — 3/5

Hernandez et al96 Spain Case- control study 19 (7/12) 197 (123/74) 60.0 (59.0- 75.0) Hypertension: 12 Diabetes: 0 Cardiovascular disease: 3 COPD: 2 Active cancer: 0 Immunosuppression: 6

— — — — — — 7/9

Jain et al97 India Prospective cohort study 154 (95/69) — 46.05 (±8.8) — — — 90 — — — 8/9

Ling et al98 UK Retrospective cohort study 444 (245/199) — 74 (63- 83) Diabetes mellitus: 129 COPD: 100 Asthma: 52 IHD: 73 ACS: 48 Heart failure: 54 Hypertension: 197 TIA: 40 Dementia: 59 Obesity: 20 Malignancy of solid organ: 71 Malignancy of skin: 8 Haematological malignancy: 8 Solid organ transplant: 4 Inflammatory arthritis: 16 Inflammatory bowel disease: 5

63 80 87 386 5 53 8/9

Luo et al99 China Retrospective cross- sectional study

335 (148/187) 560 (257/303) 56.0 (43.0- 64.0) Comorbidity status: 147 — — 218 — — — 7/10

TABLE ­1  (Continued)

(Continues)

8 of 16  |     GHASEMIAN Et Al.

2.6 | Heterogeneity­assessment

I- square (I2) statistic was used for heterogeneity evaluation. Following Cochrane Handbook for Systematic Reviews of Interventions,12 the I2 was interpreted as follows: “0% to 40%: might not be important; 30% to 60%: may represent moderate het- erogeneity; 50% to 90%: may represent substantial heterogeneity; 75% to 100%: considerable heterogeneity. The importance of the ob- served value of I2 depends on (i) magnitude and direction of effects and (ii) strength of evidence for heterogeneity (eg, P- value from the chi- squared test, or a confidence interval for I2).” Thus, the random- effects model was used for pooling the outcomes in case of het- erogeneity; otherwise, the inverse variance fixed- effect model was used. Forest plots were presented to visualise the degree of variation between studies.

2.7 | Data­analysis

Meta- analysis was performed using Comprehensive Meta- Analysis (CMA) v. 2.2.064 software. The pooling of effect sizes was done with 95% Confident Interval (CI). The fixed/random- effects model was used according to heterogeneities. In the case of zero frequency, the correction value of 0.1 was used.

2.8 | Publication­bias

Begg's and Egger's tests were used for publication bias evaluation. A P- value of less than .05 was considered as statistically significant.

3  | RESULTS

3.1 | Study­selection­process

The first search through databases resulted in 1382 papers. After removing duplicated papers and first- step screening based on title and abstract, 121 papers were assessed for eligibility. Finally, 23 ar

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