Literature DB >> 34693235

Corrigendum to: Influence of 25‑hydroxy-cholecalciferol levels on SARS-CoV-2 infection and COVID-19 severity: A systematic review and meta-analysis [EClinicalMedicine 37 (2021) 100,967].

Andrea Crafa1, Rossella Cannarella1, Rosita A Condorelli1, Laura M Mongioì1, Federica Barbagallo1, Antonio Aversa2, Sandro La Vignera1, Aldo E Calogero1.   

Abstract

[This corrects the article DOI: 10.1016/j.eclinm.2021.100967.].
© 2021 The Authors.

Entities:  

Year:  2021        PMID: 34693235      PMCID: PMC8527185          DOI: 10.1016/j.eclinm.2021.101168

Source DB:  PubMed          Journal:  EClinicalMedicine        ISSN: 2589-5370


We published a comprehensive systematic review and meta-analysis evaluating the current evidence on the impact of 25‑hydroxy-cholecalciferol [25(OH)D] and its deficiency, on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and the severity and mortality of the coronavirus 19 disease (COVID-19). Recently, we were informed that two studies included in our meta-analysis and published on pre-print platforms were withdrawn (original article references 39, 55). For this reason, in the attempt to understand whether the inclusion of these pre-prints could have affected the results of our meta-analysis, we decided to make an additional analysis after excluding not only the two withdrawn pre-prints but also a third one originally included in the analysis (45). Because of the exclusion of the 3 pre-prints (original article references 39, 45, 55), the flowchart of the included studies was modified (Fig. 1). Table 1, showing the characteristics of the included studies, and Table 2, concerning the quality analysis of the studies, were also updated after exclusion of the 3 pre-prints (original article references 39, 45, 55).
Fig. 1

Flowchart of the studies included in the meta-analysis.

Table 1

Main characteristics of the studies included in this meta-analysis.

First AuthorYearCountryStudy designSample sizeMean AgeGender Male/FemaleEthnicityOutcome evaluatedTime at 25(OH)D levels assessment
Abdollahi2020 [27]IranCase-control study402SARS-CoV-2 +48.0 ± 16.5SARS-CoV-2 +66/135NRDifference in mean 25(OH)D levels between COVID-19 positive and controlsNR
SARS-CoV-2 -46.34 ± 13.5SARS-CoV-2 -66/135
Abrishami2020IranRetrospective study73SARS-CoV-2 +55.2 ± 15.0SARS-CoV-2 +47/26NRDifference in 25(OH)D levels between dead and dischargedGenerally performed within 3 days of hospital admission
SARS-CoV-2 -/SARS-CoV-2 -/
Arvinte2020USAPilot study21SARS-CoV-2 +60.2 ± 17.4SARS-CoV-2 +15/6SARS-CoV-2 +Caucasian: 4 Hispanic: 17Difference in 25(OH)D levels between patients who died or were discharged from the hospitalAdmission to hospital
SARS-CoV-2 -/SARS-CoV-2 -/SARS-CoV-2 -/
Baktash2020UKProspective Cohort Study105SARS-CoV-2 +81 (SD NR)SARS-CoV-2 +42/28SARS-CoV-2 +Caucasian: 50 South Asian: 18 East Asian: 2 Afro-Caribbean: 1Difference in mean 25(OH)D levels between COVID-19 patients and controls. Assessment of the risk for COVID-19 related mortality in patients with VDDAdmission to hospital
SARS-CoV-2 -83.4 ± 8.1SARS-CoV-2 -15/20SARS-CoV-2 -Caucasian: 30 South Asian: 3 East Asian: 0 Afro-Caribbean: 3
Carpagnano2020ItalyRetrospective, observational single-center study42SARS-CoV-2 +65.0 ± 13.0SARS-CoV-2 +30/12NRAssessment of the risk for mortality by COVID-19 in patients with VDDPerformed within 12 h of admission to RICU
SARS-CoV-2 -/SARS-CoV-2 -/
Cereda2020ItalySingle-center cohort study129SARS-CoV-2 +73.6 ± 13.9SARS-CoV-2 +70/59SARS-CoV-2 +/Assessment of the risk for COVID-19 severity and related mortality in patients with VDDPerformed within 48 h of admission to hospital
SARS-CoV-2 -/SARS-CoV-2 -/SARS-CoV-2 -/
Chodick2020IsraelCross-sectional study14,520SARS-CoV-2 +40.6 (19.1)SARS-CoV-2 +788/529NRDifference in mean 25(OH)D levels between COVID-19 patients and controlsNR
SARS-CoV-2 -37.0 (19.1)SARS-CoV-2 -6092/7111
D'Avolio2020SwissRetrospective Cohort Study107SARS-CoV-2 +73.3 ± 12.5SARS-CoV-2 +19/8NRDifference in mean 25(OH)D levels between COVID-19 patients and controlsGenerally performed within 3 days of molecular testing for diagnosis of SARS-CoV-2 infection
SARS-CoV-2 -72.0 ± 15.9SARS-CoV-2 -39/41
De Smet2020BelgiumRetrospective observational study186SARS-CoV-2 +67.0 ± 20.9SARS-CoV-2 +109/77NRDifference in 25(OH)D levels between mild and severe cases and between dead or discharged patients. Assessment of the risk for COVID-19 severe forms in patients with VDDAdmission to hospital
SARS-CoV-2 -/SARS-CoV-2 -/
Faul2020 [41]IrelandObservational study33SARS-CoV-2 +NRSARS-CoV-2 +33/0SARS-CoV-2 +Caucasian: 33Difference in 25(OH)D levels between mild and severe COVID-19 patientsAdmission to hospital
SARS-CoV-2 -/SARS-CoV-2 -/SARS-CoV-2 -/
Hastie-Mackay2020UKRetrospective cohort study348,598SARS-CoV-2 +NRSARS-CoV-2 +265/184SARS-CoV-2 +White: 385 Black: 32 South Asian:19 Other: 13Difference in mean 25(OH)D levels between COVID-19 patients and controlsPre-hospedalization (at least 10 years old dosages)
SARS-CoV-2 -NRSARS-CoV-2 -168,391/179,758SARS-CoV-2 -White: 331,464 Black: 5022 South Asian:5917 Other: 5746
Hernandez2020SpainCase-control Study394SARS-CoV-2 +59.5 ± 16.8SARS-CoV-2 +123/74NRDifference in mean 25(OH)D levels between COVID-19 patients and controls. Assessment of the risk for COVID-19 severity and related mortality in patients with VDDAdmission to hospital
SARS-CoV-2 -61.0 ± 7.47SARS-CoV-2 -123/74
Im2020 [33]South KoreaCase-control study200SARS-CoV-2 +52.2 ± 20.7SARS-CoV-2 +21/29NRDifference in mean 25(OH)D levels between COVID-19 patients and controlsDosing performed on average within 2 days of hospital admission and no later than 7 days
SARS-CoV-2 -52.4 ± 20.2SARS-CoV-2 -NR
Jain2020IndiaProspective observational study154SARS-CoV-2 +NRSARS-CoV-2 +95/69NRDifference in 25(OH)D levels between mild and severe cases. Assessment of the risk for COVID-19 severe forms or mortality in patients with VDDAdmission to hospital
SARS-CoV-2 -/SARS-CoV-2 -/
Karonova2020RussiaObservational cohort study80SARS-CoV-2 +53.2 ± 15.7SARS-CoV-2 +43/37NRDifference in 25(OH)D levels between mild and severe COVID-19 forms and between dead or discharged patientsNE
SARS-CoV-2 -/SARS-CoV-2 -/
Kerget2020 [44]TurkeyCase-control Study88SARS-CoV-2 +49±21.1SARS-CoV-2 +41/47NRDifference in 25(OH)D levels between mild and severe COVID-19 forms and  between dead or discharged patientsAdmission to hospital
SARS-CoV-2 -35.2 ± 6.9SARS-CoV-2 -8/12
Luo2020ChinaRetrospective cross-sectional study895SARS-CoV-2 +54.3 ± 15.6SARS-CoV-2 +148/187NRDifference in 25(OH)D levels between COVID-19 patients and controls. Difference in 25(OH)D levels between mild and severe COVID-19 forms and between dead or discharged patients. Assessment of the risk for COVID-19 severity and related mortality in patients with VDDAdmission to hospital
SARS-CoV-2 -54.7 ± 8.2SARS-CoV-2 -257/303
SARS-CoV-2 -/SARS-CoV-2 -/
Mardani2020 [35]IranCase-control study123SARS-CoV-2 +43.3 ± 14.5SARS-CoV-2 +35/28NRDifference in mean 25(OH)D levels between COVID-19 patients and controls and between dead or discharged patientsAdmission to hospital
SARS-CoV-2 -40.8 ± 15.8SARS-CoV-2 -30/30
Merzon2020IsraelPopulation based study7807SARS-CoV-2 +35.6 ± 15.6SARS-CoV-2 +385/397NRDifference in mean 25(OH)D levels between COVID-19 patients and controlsPre-hospedalization (not specified when)
SARS-CoV-2 -47.4 ± 21.0SARS-CoV-2 -2849/4176
Panagiotou2020UKRetrospective study134SARS-CoV-2 +NRSARS-CoV-2 +73/61SARS-CoV-2 +Caucasian: 128 Asian: 4 Afro-Caribbean: 1 Other: 1Difference in 25(OH)D levels between mild and severe COVID-19 forms. Assessment of the risk for severe COVID-19 forms in patients with VDDAdmission to hospital
SARS-CoV-2 -/SARS-CoV-2 -/SARS-CoV-2 -/
Pizzini2020AustriaProspective Multicenter Observational Study109SARS-CoV-2 +58.0 ± 14.0SARS-CoV-2 +65/44NRDifference in 25(OH)D levels between mild and severe COVID-19 forms25(OH)D assays performed 8 weeks after disease onset
SARS-CoV-2 -/SARS-CoV-2 -/
Radujkovic2020GermanyProspective Observational Study185SARS-CoV-2 +50.7 ± 15.7SARS-CoV-2 +95/90NRDifference in 25(OH)D levels between mild and severe COVID-19 formsAdmission to hospital
SARS-CoV-2 -/SARS-CoV-2 -/
SARS-CoV-2 -/SARS-CoV-2 -/
Raisi-Estabragh2020UKProspective cohort study4510SARS-CoV-2 +68.1 ± 9.2SARS-CoV-2 +696/630SARS-CoV-2 +White: 1.141 Black: 76 Asian: 60 Chinese: 6 Mixed: 9 Other: 34Difference in mean 25(OH)D levels between COVID-19 patients and controlsPre-hospedalization (at least 10 years old dosages)
SARS-CoV-2 -68.91 ± 8.72SARS-CoV-2 -1505/1679SARS-CoV-2 -White: 2927 Black: 91 Asian: 78 Chinese: 3 Mixed: 24 Other: 61
Szeto2020USARetrospective cohort study93SARS-CoV-2 +NRSARS-CoV-2 +44/49SARS-CoV-2 +Black: 27Assessment of the risk for COVID-19 severity and related mortality in patients with VDDPrehospitalization (25(OH)D levels measured within the previous year and on average 136 days prior to hospital admission)
SARS-CoV-2 -/SARS-CoV-2 -/SARS-CoV-2 -/
Vassiliou2020GreekProspective observational cohort study30SARS-CoV-2 +65.0 ± 11.0SARS-CoV-2 +24/6NRDifference in 25(OH)D levels between dead and discharged COVID-19 patients and assessment of the risk for COVID-19 mortality in patients with VDDAdmission to ICU
SARS-CoV-2 -/SARS-CoV-2 -/
Ye2020 [38]ChinaCase-control study142SARS-CoV-2 +41.7 ± 15.9SARS-CoV-2 +32/48NRDifference in mean 25(OH)D levels between COVID-19 patients and controls, and between patients with severe or non-severe forms of COVID-19. Assessment of the risk for severe COVID-19 forms in patients with VDDAdmission to hospital
SARS-CoV-2 -44.7 ± 20.5SARS-CoV-2 -23/39

Abbreviation: 25(OH)D, 25‑hydroxy-cholecalciferol; VDD, vitamin D deficiency; COVID-19, coronavirus disease 19; NR, Not Reported; SARS-CoV-2 +, patients positive for severe acute respiratory syndrome coronavirus 2 infection; SARS-CoV-2 -, patients negative for severe acute respiratory syndrome coronavirus 2 infection; SD, standard deviation; NE, Not evaluated; ICU, Intensive Care Unit; RICU, Respiratory Intermediate Care Unit.

Table 2

Quality assessment tool for observational cohort and cross-sectional studies.

Author1234567891011121314
Abrishami et al. (2020) [49]++++NR+++NA++
Arvinte et al. (2020) [50]+++NR++NA+
Baktash et al. (2020) [28]++++++NA+
Carpagnano et al. (2020) [54]+++NR+++NA++
Cereda et al. (2020)+++++++NA++
Chodick et al. (2020) [29]+++NR++NA++
D'Avolio et al. (2020) [30]++++++NA+
De Smet et al. (2020) [40]++++++NA+
Faul et al. (2020) [41]+++NRNRNRNR+NA+
Hastie-Mackay et al. (2020) [31]++++++++NR+NA++
Jain et al. (2020)+++++NR+++NA++
Karonova et al. (2020) [43]not assessable because in Russian language
Luo et al. (2020)+++++++NA++
Merzon et al. (2020) [36]+++++NA++NR+NA++
Panagiotou et al. (2020) [46]+++NR+++NA+
Pizzini et al. (2020) [47]++++++++NA+
Radujkovic et al. (2020) [48]+++++++NA++
Raisi-Estabragh et al. (2020) [37]++++++++NA++
Szeto et al. (2020) [53]++++NR++++NA++
Vassiliou et al. (2020) [51]++++++++NA+

1. Was the research question or objective in this paper clearly stated?

2. Was the study population clearly specified and defined?

3. Was the participation rate of eligible persons at least 50%?

4. Were all the subjects selected or recruited from the same or similar populations (including the same time period)? Were inclusion and exclusion criteria for being in the study pre-specified and applied uniformly to all participants?

5. Was a sample size justification, power description, or variance and effect estimates provided?

6. For the analyses in this paper, were the exposure(s) of interest measured prior to the outcome(s) being measured?

7. Was the timeframe sufficient so that one could reasonably expect to see an association between exposure and outcome if it existed?

8. For exposures that can vary in amount or level, did the study examine different levels of the exposure as related to the outcome (e.g., categories of exposure, or exposure measured as continuous variable)?

9. Were the exposure measures (independent variables) clearly defined, valid, reliable, and implemented consistently across all study participants?

10. Was the exposure(s) assessed more than once over time?

11. Were the outcome measures (dependent variables) clearly defined, valid, reliable, and implemented consistently across all study participants?

12. Were the outcome assessors blinded to the exposure status of participants?

13. Was loss to follow-up after baseline 20% or less?

14. Were key potential confounding variables measured and adjusted statistically for their impact on the relationship between exposure(s) and outcome(s)?

Flowchart of the studies included in the meta-analysis. Main characteristics of the studies included in this meta-analysis. Abbreviation: 25(OH)D, 25‑hydroxy-cholecalciferol; VDD, vitamin D deficiency; COVID-19, coronavirus disease 19; NR, Not Reported; SARS-CoV-2 +, patients positive for severe acute respiratory syndrome coronavirus 2 infection; SARS-CoV-2 -, patients negative for severe acute respiratory syndrome coronavirus 2 infection; SD, standard deviation; NE, Not evaluated; ICU, Intensive Care Unit; RICU, Respiratory Intermediate Care Unit. Quality assessment tool for observational cohort and cross-sectional studies. 1. Was the research question or objective in this paper clearly stated? 2. Was the study population clearly specified and defined? 3. Was the participation rate of eligible persons at least 50%? 4. Were all the subjects selected or recruited from the same or similar populations (including the same time period)? Were inclusion and exclusion criteria for being in the study pre-specified and applied uniformly to all participants? 5. Was a sample size justification, power description, or variance and effect estimates provided? 6. For the analyses in this paper, were the exposure(s) of interest measured prior to the outcome(s) being measured? 7. Was the timeframe sufficient so that one could reasonably expect to see an association between exposure and outcome if it existed? 8. For exposures that can vary in amount or level, did the study examine different levels of the exposure as related to the outcome (e.g., categories of exposure, or exposure measured as continuous variable)? 9. Were the exposure measures (independent variables) clearly defined, valid, reliable, and implemented consistently across all study participants? 10. Was the exposure(s) assessed more than once over time? 11. Were the outcome measures (dependent variables) clearly defined, valid, reliable, and implemented consistently across all study participants? 12. Were the outcome assessors blinded to the exposure status of participants? 13. Was loss to follow-up after baseline 20% or less? 14. Were key potential confounding variables measured and adjusted statistically for their impact on the relationship between exposure(s) and outcome(s)? Analysis of serum 25(OH)D levels in SARS-CoV2-positive versus negative patients, and also analysis of patients with infection discharged versus those who died from the disease, were not performed, since pre-prints (original article references 39, 45, 55) were not included for these outcomes in the original meta-analysis. Regarding analysis related to 25(OH)D levels in patients with severe or non-severe COVID-19 (original article Fig. 3), after exclusion of the pre-prints referenced originally as 39 and 45, 10 studies assessing this outcome remained. Specifically, the new analysis confirmed that 25(OH)D levels were clearly lower in the 492 patients with severe disease compared to the 817 patients with a non-severe course of the disease [MD −5.50 (−8.86, −2.14); p = 0.001] (Fig. 3A). After exclusion of the two pre-prints mentioned above, high inter-study heterogeneity was still found (Chi2 P < 0.00001, I2=93%) (Fig. 3B). After the removal of the studies by Luo and colleagues (original article reference 34), and Jain and colleagues (original article reference 42), identified as a source of heterogeneity at the Funnel Plot, the analysis showed homogeneity of the remaining studies (Chi2 P = 0.86, I2=0%) maintaining the statistical significance [MD −4.80 (−6.27, −3.32); p < 0.00001].
Fig. 3

Panel A. Forest plot of studies that assessed 25(OH)D levels as a continuous variable in patients with severe course of COVID-19 than those with mild course. Panel B. Funnel plot showing the source of heterogeneity of studies that evaluated 25(OH)D levels as a continuous variable in patients with severe course of COVID-19 than those with mild course. Serum 25(OH)D levels are expressed in ng/ml.

Panel A. Forest plot of studies that assessed 25(OH)D levels as a continuous variable in patients with severe course of COVID-19 than those with mild course. Panel B. Funnel plot showing the source of heterogeneity of studies that evaluated 25(OH)D levels as a continuous variable in patients with severe course of COVID-19 than those with mild course. Serum 25(OH)D levels are expressed in ng/ml. Also, the analysis of the risk of severe COVID-19 in patients with VDD (original article Fig. 5) did not change after the exclusion of pre-print reference 39. This outcome was assessed on data extracted from 10 studies. The study by Cereda and colleagues (original article reference 52) was considered twice since it evaluated both the percentage of patients with severe pneumonia and patients admitted to the intensive care units as an outcome of severity. The study by Jain and colleagues (original article reference 42) was also considered twice since they assessed the risk of infection severity both in patients with 25(OH)D<20 ng/ml and then in patients with levels below 10 ng/ml. The new statistical analysis confirmed that patients with VDD had a higher risk of a severe disease course than patients without deficiency [OR 3.78 (1.77, 8.06); p = 0.0006], regardless of the cut-off values considered to establish the efficiency (Fig. 5A). The Funnel plot showed that the heterogeneity found (Chi2 P < 0.00001, I2=85%) was attributable to the studies Jain and colleagues’ (original article reference 42) and Hernandez and coworkers’ (original article reference 32) (Fig. 5B). Once the data from these studies were excluded, heterogeneity was no longer observed (Chi2 P = 0.53, I2=0%) and the risk of developing a severe course of the disease in VDD patients remained significant [OR 2.47 (1.80, 3.37); p < 0.00001].
Fig. 5

Panel A. Forest plot of studies that assessed the risk of a severe course of disease in subjects with 25(OH)D values below or above a specified cut-off. The different cut-offs used by the studies allowed for subgroup analysis. Studies using cut-off values higher than those established by the Endocrine Society for the diagnosis of Vitamin D Deficiency (<20 ng/ml) were not included. Panel B. Funnel plot showing the source of heterogeneity of studies that evaluated the risk of a severe course of disease in subjects with 25(OH)D below or above a specified cut-off.

Panel A. Forest plot of studies that assessed the risk of a severe course of disease in subjects with 25(OH)D values below or above a specified cut-off. The different cut-offs used by the studies allowed for subgroup analysis. Studies using cut-off values higher than those established by the Endocrine Society for the diagnosis of Vitamin D Deficiency (<20 ng/ml) were not included. Panel B. Funnel plot showing the source of heterogeneity of studies that evaluated the risk of a severe course of disease in subjects with 25(OH)D below or above a specified cut-off. Finally, the analysis of the risk of mortality in patients with VDD (original article supplementary Fig. 2) also remained unchanged after the exclusion of the pre-print reference 55. Indeed, the analysis of the remaining 8 studies confirmed the absence of a significant increase in mortality risk in patients with VDD compared to patients with adequate 25(OH)D levels [OR 1.74 [0.84, 3.59]; p = 0.14] regardless of the cut-off values considered for deficiency (supplementary Fig. 2A). Heterogeneity between studies was found (Chi2 P < 0.03, I2=55%), and its origin was due to the study by Jain and colleagues (42) (Supplementary Fig. 2B). When this was excluded from the analysis, the Funnel Plot showed homogeneity among the remaining studies (Chi2 P = 0.15, I2=36%), and the increased risk of COVID-19 mortality in the presence of VDD was confirmed to be non-significant [OR 1.30 (0.83, 2.03); p = 0.25]. In conclusion, the results of this new analysis showed no difference compared to the original one. Therefore, the inclusion of pre-prints did not affect the results of our meta-analysis. After the exclusion of pre-prints, we may still hypothesize a role for low 25(OH)D levels in the risk of SARS-CoV-2 infection and the development of more severe forms of COVID-19.
  20 in total

1.  Evaluation of the relationship of serum vitamin D levels in COVID-19 patients with clinical course and prognosis.

Authors:  Buğra Kerget; Ferhan Kerget; Ahmet Kızıltunç; Abdullah Osman Koçak; Ömer Araz; Elif Yılmazel Uçar; Metin Akgün
Journal:  Tuberk Toraks       Date:  2020-09

2.  Angiotensin-converting enzyme inhibitors and angiotensin-receptor blockers are not associated with increased risk of SARS-CoV-2 infection.

Authors:  Gabriel Chodick; Amir Nutman; Naama Yiekutiel; Varda Shalev
Journal:  J Travel Med       Date:  2020-08-20       Impact factor: 8.490

3.  Low 25-Hydroxyvitamin D Levels on Admission to the Intensive Care Unit May Predispose COVID-19 Pneumonia Patients to a Higher 28-Day Mortality Risk: A Pilot Study on a Greek ICU Cohort.

Authors:  Alice G Vassiliou; Edison Jahaj; Maria Pratikaki; Stylianos E Orfanos; Ioanna Dimopoulou; Anastasia Kotanidou
Journal:  Nutrients       Date:  2020-12-09       Impact factor: 5.717

4.  Serum 25(OH)D Level on Hospital Admission Associated With COVID-19 Stage and Mortality.

Authors:  Dieter De Smet; Kristof De Smet; Pauline Herroelen; Stefaan Gryspeerdt; Geert A Martens
Journal:  Am J Clin Pathol       Date:  2021-02-11       Impact factor: 2.493

5.  Does Serum Vitamin D Level Affect COVID-19 Infection and Its Severity?-A Case-Control Study.

Authors:  Kun Ye; Fen Tang; Xin Liao; Benjamin A Shaw; Meiqiu Deng; Guangyi Huang; Zhiqiang Qin; Xiaomei Peng; Hewei Xiao; Chunxia Chen; Xiaochun Liu; Leping Ning; Bangqin Wang; Ningning Tang; Min Li; Fan Xu; Shao Lin; Jianrong Yang
Journal:  J Am Coll Nutr       Date:  2020-10-13       Impact factor: 3.169

6.  Vitamin D concentrations and COVID-19 infection in UK Biobank.

Authors:  Claire E Hastie; Daniel F Mackay; Frederick Ho; Carlos A Celis-Morales; Srinivasa Vittal Katikireddi; Claire L Niedzwiedz; Bhautesh D Jani; Paul Welsh; Frances S Mair; Stuart R Gray; Catherine A O'Donnell; Jason Mr Gill; Naveed Sattar; Jill P Pell
Journal:  Diabetes Metab Syndr       Date:  2020-05-07

7.  25-Hydroxyvitamin D Concentrations Are Lower in Patients with Positive PCR for SARS-CoV-2.

Authors:  Antonio D'Avolio; Valeria Avataneo; Alessandra Manca; Jessica Cusato; Amedeo De Nicolò; Renzo Lucchini; Franco Keller; Marco Cantù
Journal:  Nutrients       Date:  2020-05-09       Impact factor: 5.717

8.  Vitamin D Deficiency and Outcome of COVID-19 Patients.

Authors:  Aleksandar Radujkovic; Theresa Hippchen; Shilpa Tiwari-Heckler; Saida Dreher; Monica Boxberger; Uta Merle
Journal:  Nutrients       Date:  2020-09-10       Impact factor: 5.717

9.  Possible association of vitamin D status with lung involvement and outcome in patients with COVID-19: a retrospective study.

Authors:  Alireza Abrishami; Nooshin Dalili; Peyman Mohammadi Torbati; Reyhaneh Asgari; Mehran Arab-Ahmadi; Behdad Behnam; Morteza Sanei-Taheri
Journal:  Eur J Nutr       Date:  2020-10-30       Impact factor: 5.614

10.  Vitamin D status and outcomes for hospitalised older patients with COVID-19.

Authors:  Vadir Baktash; Tom Hosack; Nishil Patel; Shital Shah; Pirabakaran Kandiah; Koenraad Van den Abbeele; Amit K J Mandal; Constantinos G Missouris
Journal:  Postgrad Med J       Date:  2020-08-27       Impact factor: 2.401

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