COVID-19
Conditions
Keywords
COVID-19, gut microbiome, antiphospholipid antibodies, rehabilitation, food products
Brief summary
The efficacy of natural foods such as freeze-dried mare's milk (Saumal) in post-COVID syndrome therapy has not been studied. The literature review has shown that researchers have focused more on evidence-based medications and less on natural products. Some raw foods, such as freeze-dried mare's milk, contribute to forming complete immune complexes and have antioxidant, membrane stabilizing, and antiviral effects. The use of Saumal proved its effectiveness in patients suffering from chronic hepatitis C. After 4 weeks of using freeze-dried mare's milk, the biodiversity of the intestinal microbiome was increased. The content of bacteria secreting short-chain fatty acids also increased. The study aims to confirm these effects at the gene level in patients who underwent COVID-19. This study will allow us to develop a highly evidence-based component of rehabilitation therapy in patients after COVID-19.
Detailed description
The study consists of three stages. Stage I. Randomized division of 75 patients under study into a main group of 38 patients receiving Saumal for 4 weeks and a control group of 37 patients not receiving Saumal. All respondents have suffered from COVID-19 in the last 6 months. At the moment of the research, all patients will be staying in rehabilitation centers in Almaty City. The study's biological material will be collected from the respondents (gut microbiome, antiphospholipid antibodies, biochemical blood analysis (glucose, ALT, AST, uric acid, TAGs, alkaline phosphatase)). Stage II. The main group will be given Saumal for four weeks, after which the gut microbiome, antiphospholipid antibodies, and biochemical blood analysis will be collected from both groups again. This will allow us to assess the impact of freeze-dried mare's milk on the condition of the gut microbiome, antiphospholipid antibodies, and biochemical blood analysis. Stage III. Data analysis. 1. Based on the results of gut microbiome sequencing, ELISA (antiphospholipid antibodies), and biochemical blood analysis in the main and control groups, we determine the dynamic changes of those parameters during COVID-19 rehabilitation. 2. According to the results, the effectiveness of Saumal itself regarding these 2 parameters will be evaluated. 3. Develop recommendations and an algorithm for patient management after COVID-19 to prevent complications.
Interventions
DIETARY_SUPPLEMENTFreeze-dried Mare Milk (Saumal)
Freeze-dried Mare Milk (Saumal) is frequently reported for having therapeutic and dietary properties associated with specific chemical composition and certain physical properties of the product. It contains a total of about 40 biologically active components, the most important of them vitamins A, C, B1, B2, B6, and B12, amino acids, enzymes, and trace elements (low molecular weight peptides, lactalbumins, and globulins). Saumal will be administered to patients at a dose of 25 grams of dry powder per 200 ml of water, 2 times a day, 30 minutes before the meal, for 4 weeks.
Sponsors
Asfendiyarov Kazakh National Medical University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
No
Inclusion criteria
1. Age 18 years and older; 2. Patients in rehabilitation after COVID-19; 3. Signed informed consent; 4. Presence of patient's history of COVID-19, reliably established by PCR+ /presence of IgG/ diagnosis of coronavirus pneumonia on Computer Tomography based on discharge from hospital or outpatient records.
Exclusion criteria
1. Chronic inflammatory bowel disease; 2. Gut microbiota transplantation; 3. Chronic pancreatic disease, period of exacerbation; 4. Liver cirrhosis, Metavir stage 3-4; 5. Any disease in the decompensation stage; 6. Neuralgic and psychological disorders that interfere with the study; 7. Cancer; 8. Non-transportable patients; 9. Patients who do not reside in Almaty; 10. Patients who have refused to participate in the study.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Gut Microbiome | 4 weeks | Intestinal microbiome studies will be performed using the Illumina MiSeq Metagenomics Kit. Creation of libraries for NGS sequencing. The commercial Illumina MiSeq The Metagenomics Kit includes two primer pools that can amplify the hypervariable regions of 16S rRNA in bacteria. The first pool produces V2-4-8, while the second pool allows for the production of V3-6 and 7-9 regions of 16S rRNA. Sequencing will be performed on an Ion S5 analyzer using an Illumina MiSeq Chip Kit. Once the PCR products have been run, it is important to follow standard procedures for fragment end recovery, adaptor ligation, nick gap repair, qualitative and quantitative assessment of non-amplified libraries, and pooling. |
| Antiphospholipid Antibodies | 4 weeks | IgG or IgM autoantibodies to cardiolipin, phosphatidyl serine, phosphatidyl-inositol, phosphatidyl acid, and β2-glycoprotein I are determined in human venous blood serum by enzyme immunoassay (ELISA) using the Anti-Phospholipid Screen IgG/IgM kit. |
| Biochemical Blood Analysis (Uric Acid) | 4 weeks | This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain) |
| Quality of Life Changes | 4 weeks | Constructs: Physical Functioning (PF), Role Limitations due to Physical Health (RP), Bodily Pain (BP), General Health (GH), Vitality (VT), Social Functioning (SF), Role Limitations due to Emotional Problems (RE), Mental Health (MH). All scale ranges (for any construct): 0 to 100. Higher scores indicate: PF - better physical functioning; RP - fewer role limitations due to physical health; BP - less bodily pain; GH - better perceived general health; VT - greater vitality and less fatigue; SF - better social functioning; RE - fewer role limitations due to emotional problems; MH - better mental health. The SF-36 does not have a single total score but can be summarized using two summary measures: 1. Physical Component Summary (PCS). Combines the following scales: PF, RP, BP, GH. 2. Mental Component Summary (MCS). Combines the following scales: VT, SF, RE, MH. Higher scores indicate better physical and mental health. Range: Typically standardized (mean = 50, SD = 10) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Biochemical Blood Analysis (ALT) | 4 weeks | This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain) |
| Biochemical Blood Analysis (Alkaline Phosphatase) | 4 weeks | This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain) |
| Biochemical Blood Analysis (AST) | 4 weeks | This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain) |
| Biochemical Blood Analysis (Glucose) | 4 weeks | This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain) |
| Biochemical Blood Analysis (Triacylglycerides) | 4 weeks | This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain) |
Countries
Kazakhstan
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| Main Group Patients who had suffered from COVID-19 in the six months before the start of the study. Patients will receive Saumal (freeze-dried mare milk) for four weeks.
Freeze-dried Mare Milk (Saumal): Freeze-dried Mare Milk (Saumal) is frequently reported for having therapeutic and dietary properties associated with specific chemical composition and certain physical properties of the product. It contains a total of about 40 biologically active components, the most important of them vitamins A, C, B1, B2, B6, and B12, amino acids, enzymes, and trace elements (low molecular weight peptides, lactalbumins, and globulins). Saumal will be administered to patients at a dose of 25 grams of dry powder per 200 ml of water, 2 times a day, 30 minutes before the meal, for 4 weeks. | 30 |
| Control Group Patients who had suffered from COVID-19 in the six months before the start of the study. There will be no intervention. | 30 |
| Total | 60 |
Withdrawals & dropouts
| Period | Reason | FG000 | FG001 |
|---|---|---|---|
| Overall Study | Lost to Follow-up | 4 | 3 |
| Overall Study | Physician Decision | 4 | 4 |
Baseline characteristics
| Characteristic | Main Group | Control Group | Total |
|---|---|---|---|
| Age, Categorical <=18 years | 0 Participants | 0 Participants | 0 Participants |
| Age, Categorical >=65 years | 10 Participants | 10 Participants | 20 Participants |
| Age, Categorical Between 18 and 65 years | 20 Participants | 20 Participants | 40 Participants |
| Count of Participants | 30 Participants | 30 Participants | 60 Participants |
| Race and Ethnicity Not Collected | — | — | 0 Participants |
| Sex: Female, Male Female | 20 Participants | 20 Participants | 40 Participants |
| Sex: Female, Male Male | 10 Participants | 10 Participants | 20 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk |
|---|---|---|
| deaths Total, all-cause mortality | 0 / 0 | 0 / 0 |
| other Total, other adverse events | 0 / 0 | 0 / 0 |
| serious Total, serious adverse events | 0 / 0 | 0 / 0 |
Outcome results
Primary
Antiphospholipid Antibodies
IgG or IgM autoantibodies to cardiolipin, phosphatidyl serine, phosphatidyl-inositol, phosphatidyl acid, and β2-glycoprotein I are determined in human venous blood serum by enzyme immunoassay (ELISA) using the Anti-Phospholipid Screen IgG/IgM kit.
Time frame: 4 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Main Group | Antiphospholipid Antibodies | IgM | 2.73 U/ml | Standard Error 0.185 |
| Main Group | Antiphospholipid Antibodies | IgG | 1.43 U/ml | Standard Error 0.726 |
| Control Group | Antiphospholipid Antibodies | IgM | 4.45 U/ml | Standard Error 0.001 |
| Control Group | Antiphospholipid Antibodies | IgG | 4.50 U/ml | Standard Error 0.0001 |
Comparison: Null hypothesis: No statistically significant difference exists between antiphospholipid antibody levels before and after the mare's milk administration.~Alternate hypothesis: Statistically significant difference exists between antiphospholipid antibody levels before and after the mare's milk administration.p-value: >0.05Wilcoxon (Mann-Whitney)
Primary
Biochemical Blood Analysis (Uric Acid)
This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain)
Time frame: 4 weeks
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Main Group | Biochemical Blood Analysis (Uric Acid) | 5.56 mg/dL | Standard Error 0.01 |
| Control Group | Biochemical Blood Analysis (Uric Acid) | 7.87 mg/dL | Standard Error 0.34 |
Comparison: Null hypothesis: No statistically significant difference exists between uric acid blood levels before and after the mare's milk administration.~Alternate hypothesis: Statistically significant difference exists between uric acid blood levels before and after the mare's milk administration.p-value: 0.01Wilcoxon (Mann-Whitney)
Primary
Gut Microbiome
Intestinal microbiome studies will be performed using the Illumina MiSeq Metagenomics Kit. Creation of libraries for NGS sequencing. The commercial Illumina MiSeq The Metagenomics Kit includes two primer pools that can amplify the hypervariable regions of 16S rRNA in bacteria. The first pool produces V2-4-8, while the second pool allows for the production of V3-6 and 7-9 regions of 16S rRNA. Sequencing will be performed on an Ion S5 analyzer using an Illumina MiSeq Chip Kit. Once the PCR products have been run, it is important to follow standard procedures for fragment end recovery, adaptor ligation, nick gap repair, qualitative and quantitative assessment of non-amplified libraries, and pooling.
Time frame: 4 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Main Group | Gut Microbiome | Percentage of Firmicutes phylum at 4 weeks | 51.87 Mean percentages of gut microbiota units | Standard Error 0.001 |
| Main Group | Gut Microbiome | Percentage of Bacteroides phylum at 4 weeks | 29.43 Mean percentages of gut microbiota units | Standard Error 0.178 |
| Main Group | Gut Microbiome | Percentage of Proteobacteria phylum at 4 weeks | 6.52 Mean percentages of gut microbiota units | Standard Error 0.00001 |
| Main Group | Gut Microbiome | Percentage of Actinobacteria phylum at 4 weeks | 4.9 Mean percentages of gut microbiota units | Standard Error 0.951 |
| Main Group | Gut Microbiome | Percentage of Bacilli class at 4 weeks | 4.02 Mean percentages of gut microbiota units | Standard Error 0.043 |
| Main Group | Gut Microbiome | Percentage of Deltaproteobacteria class at 4 weeks | 0.94 Mean percentages of gut microbiota units | Standard Error 0.048 |
| Main Group | Gut Microbiome | Percentage of Erysipelotrichi class at 4 weeks | 1.58 Mean percentages of gut microbiota units | Standard Error 0.012 |
| Main Group | Gut Microbiome | Percentage of Caldilinea genus at 4 weeks | 0.06 Mean percentages of gut microbiota units | Standard Error 0.014 |
| Main Group | Gut Microbiome | Percentage of Clostridium genus at 4 weeks | 5.07 Mean percentages of gut microbiota units | Standard Error 0.008 |
| Main Group | Gut Microbiome | Percentage of Desulfovibrio genus at 4 weeks | 0.19 Mean percentages of gut microbiota units | Standard Error 0.039 |
| Main Group | Gut Microbiome | Percentage of Escherichia genus at 4 weeks | 0.75 Mean percentages of gut microbiota units | Standard Error 0.042 |
| Main Group | Gut Microbiome | Percentage of Lachnospira genus at 4 weeks | 1.77 Mean percentages of gut microbiota units | Standard Error 0.004 |
| Main Group | Gut Microbiome | Percentage of Prevotella genus at 4 weeks | 8.85 Mean percentages of gut microbiota units | Standard Error 0.003 |
| Main Group | Gut Microbiome | Percentage of Tindallia genus at 4 weeks | 0.20 Mean percentages of gut microbiota units | Standard Error 0.02 |
| Main Group | Gut Microbiome | Percentage of Anaerobranca zavarzinii species at 4 weeks | 0.62 Mean percentages of gut microbiota units | Standard Error 0.006 |
| Main Group | Gut Microbiome | Percentage of Alkaliphilus crotonatoxidans species at 4 weeks | 1.40 Mean percentages of gut microbiota units | Standard Error 0.00001 |
| Main Group | Gut Microbiome | Percentage of Bacteroides xylanisolvens species at 4 weeks | 1.30 Mean percentages of gut microbiota units | Standard Error 0.00001 |
| Main Group | Gut Microbiome | Percentage of Bifidobacterium catenulatum species at 4 weeks | 0.96 Mean percentages of gut microbiota units | Standard Error 0.024 |
| Main Group | Gut Microbiome | Percentage of Bifidobacterium indicum species at 4 weeks | 0.10 Mean percentages of gut microbiota units | Standard Error 0.026 |
| Main Group | Gut Microbiome | Percentage of Roseburia faecis species at 4 weeks | 0.72 Mean percentages of gut microbiota units | Standard Error 0.006 |
| Control Group | Gut Microbiome | Percentage of Bifidobacterium catenulatum species at 4 weeks | 1.68 Mean percentages of gut microbiota units | Standard Error 0.434 |
| Control Group | Gut Microbiome | Percentage of Firmicutes phylum at 4 weeks | 46.1 Mean percentages of gut microbiota units | Standard Error 0.899 |
| Control Group | Gut Microbiome | Percentage of Escherichia genus at 4 weeks | 1.2 Mean percentages of gut microbiota units | Standard Error 0.71 |
| Control Group | Gut Microbiome | Percentage of Bacteroides phylum at 4 weeks | 29.77 Mean percentages of gut microbiota units | Standard Error 0.754 |
| Control Group | Gut Microbiome | Percentage of Alkaliphilus crotonatoxidans species at 4 weeks | 0.93 Mean percentages of gut microbiota units | Standard Error 0.028 |
| Control Group | Gut Microbiome | Percentage of Proteobacteria phylum at 4 weeks | 7.91 Mean percentages of gut microbiota units | Standard Error 0.823 |
| Control Group | Gut Microbiome | Percentage of Lachnospira genus at 4 weeks | 1.76 Mean percentages of gut microbiota units | Standard Error 0.049 |
| Control Group | Gut Microbiome | Percentage of Actinobacteria phylum at 4 weeks | 9.36 Mean percentages of gut microbiota units | Standard Error 0.003 |
| Control Group | Gut Microbiome | Percentage of Roseburia faecis species at 4 weeks | 0.36 Mean percentages of gut microbiota units | Standard Error 0.551 |
| Control Group | Gut Microbiome | Percentage of Bacilli class at 4 weeks | 4.46 Mean percentages of gut microbiota units | Standard Error 0.068 |
| Control Group | Gut Microbiome | Percentage of Prevotella genus at 4 weeks | 11.24 Mean percentages of gut microbiota units | Standard Error 0.698 |
| Control Group | Gut Microbiome | Percentage of Deltaproteobacteria class at 4 weeks | 0.92 Mean percentages of gut microbiota units | Standard Error 0.918 |
| Control Group | Gut Microbiome | Percentage of Bacteroides xylanisolvens species at 4 weeks | 1.63 Mean percentages of gut microbiota units | Standard Error 0.245 |
| Control Group | Gut Microbiome | Percentage of Erysipelotrichi class at 4 weeks | 1.46 Mean percentages of gut microbiota units | Standard Error 0.889 |
| Control Group | Gut Microbiome | Percentage of Caldilinea genus at 4 weeks | 0.17 Mean percentages of gut microbiota units | Standard Error 0.345 |
| Control Group | Gut Microbiome | Percentage of Tindallia genus at 4 weeks | 0.00 Mean percentages of gut microbiota units | Standard Error 1 |
| Control Group | Gut Microbiome | Percentage of Bifidobacterium indicum species at 4 weeks | 0.20 Mean percentages of gut microbiota units | Standard Error 0.052 |
| Control Group | Gut Microbiome | Percentage of Clostridium genus at 4 weeks | 2.59 Mean percentages of gut microbiota units | Standard Error 0.893 |
| Control Group | Gut Microbiome | Percentage of Anaerobranca zavarzinii species at 4 weeks | 0.18 Mean percentages of gut microbiota units | Standard Error 0.004 |
| Control Group | Gut Microbiome | Percentage of Desulfovibrio genus at 4 weeks | 0.76 Mean percentages of gut microbiota units | Standard Error 0.008 |
Comparison: Null hypothesis: there is no statistical significance between the mean percentages of microbiota units of the main and control groups after the mare's milk administration.~Alternate hypothesis: statistical significance exists between the mean percentages of microbiota units of the main and control groups after the mare's milk administration.p-value: <0.05t-test, 2 sided
Comparison: Null Hypothesis: The freeze-dried mare's milk does not significantly influence the mean percentages of gut microbiota units.~Alternate Hypothesis: The freeze-dried mare's milk significantly influences the mean percentages of gut microbiota units.p-value: <0.05ANOVA
Primary
Quality of Life Changes
Constructs: Physical Functioning (PF), Role Limitations due to Physical Health (RP), Bodily Pain (BP), General Health (GH), Vitality (VT), Social Functioning (SF), Role Limitations due to Emotional Problems (RE), Mental Health (MH). All scale ranges (for any construct): 0 to 100. Higher scores indicate: PF - better physical functioning; RP - fewer role limitations due to physical health; BP - less bodily pain; GH - better perceived general health; VT - greater vitality and less fatigue; SF - better social functioning; RE - fewer role limitations due to emotional problems; MH - better mental health. The SF-36 does not have a single total score but can be summarized using two summary measures: 1. Physical Component Summary (PCS). Combines the following scales: PF, RP, BP, GH. 2. Mental Component Summary (MCS). Combines the following scales: VT, SF, RE, MH. Higher scores indicate better physical and mental health. Range: Typically standardized (mean = 50, SD = 10)
Time frame: 4 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Main Group | Quality of Life Changes | PCS | 47.965 T-score | Standard Error 0.004 |
| Main Group | Quality of Life Changes | MCS | 49.524 T-score | Standard Error 0.001 |
| Control Group | Quality of Life Changes | PCS | 50.797 T-score | Standard Error 0.647 |
| Control Group | Quality of Life Changes | MCS | 49.393 T-score | Standard Error 0.091 |
Comparison: Null hypothesis: No statistically significant difference exists between the scores on a scale (PCS, MCS) after the mare's milk administration.~Alternate hypothesis: Statistically significant difference exists between the scores on a scale (PCS, MCS) after the mare's milk administration.p-value: <0.01t-test, 2 sided
Comparison: Null hypothesis: No statistically significant difference exists between the scores on a scale (PCS, MCS) after 2 measurements in the control group.~Alternate hypothesis: Statistically significant difference exists between the scores on a scale (PCS, MCS) after 2 measurements in the control group.p-value: >0.05t-test, 2 sided
Comparison: Null Hypothesis: The freeze-dried mare's milk does not significantly influence the scores on the scales (PCS, MCS).~Alternate Hypothesis: The freeze-dried mare's milk significantly influences the scores on the scales (PCS, MCS).p-value: <0.01ANOVA
Secondary
Biochemical Blood Analysis (Alkaline Phosphatase)
This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain)
Time frame: 4 weeks
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Main Group | Biochemical Blood Analysis (Alkaline Phosphatase) | 85 IU/L |
| Control Group | Biochemical Blood Analysis (Alkaline Phosphatase) | 92 IU/L |
Secondary
Biochemical Blood Analysis (ALT)
This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain)
Time frame: 4 weeks
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Main Group | Biochemical Blood Analysis (ALT) | 31 units per liter (IU/L) |
| Control Group | Biochemical Blood Analysis (ALT) | 35 units per liter (IU/L) |
Secondary
Biochemical Blood Analysis (AST)
This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain)
Time frame: 4 weeks
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Main Group | Biochemical Blood Analysis (AST) | 34 units per liter (IU/L) |
| Control Group | Biochemical Blood Analysis (AST) | 33 units per liter (IU/L) |
Secondary
Biochemical Blood Analysis (Glucose)
This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain)
Time frame: 4 weeks
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Main Group | Biochemical Blood Analysis (Glucose) | 5.4 mmol/L |
| Control Group | Biochemical Blood Analysis (Glucose) | 5.7 mmol/L |
Secondary
Biochemical Blood Analysis (Triacylglycerides)
This biochemical indicator will be determined from patient serum on a BA400 analyzer (BioSystems S.A., Spain)
Time frame: 4 weeks
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Main Group | Biochemical Blood Analysis (Triacylglycerides) | 1.5 mmol/L |
| Control Group | Biochemical Blood Analysis (Triacylglycerides) | 1.4 mmol/L |