Details about Haemophilus parainfluenzae: NCBI 729, gram-negative or unknown

  1. Normal Microbiota:

    • Haemophilus parainfluenzae is a commensal bacterium that is commonly found in the human respiratory tract, oral cavity, and other mucosal surfaces. It is a part of the normal microbiota in these regions.
  2. Commensalism:

    • In most cases, Haemophilus parainfluenzae is considered a commensal, meaning it typically coexists with the host without causing harm. Commensal bacteria are important for maintaining the balance of the microbial communities in various body sites.
  3. Opportunistic Pathogen:

    • While Haemophilus parainfluenzae is usually commensal, it has been reported as an opportunistic pathogen in certain circumstances. It may cause infections, particularly in individuals with compromised immune systems or underlying health conditions.
  4. Infections:

    • Haemophilus parainfluenzae has been associated with various infections, including respiratory tract infections, otitis media (ear infections), sinusitis, and occasionally, more severe conditions like endocarditis and meningitis. However, it's important to note that infections caused by Haemophilus parainfluenzae are generally opportunistic rather than primary pathogens.
  5. Antibiotic Sensitivity:

    • Haemophilus parainfluenzae is usually sensitive to a range of antibiotics, and treatment is typically guided by antibiotic susceptibility testing.
  6. Clinical Significance:

    • The clinical significance of Haemophilus parainfluenzae infections may vary depending on the specific clinical context, the health status of the individual, and the site of infection. Infections are generally more common in individuals with weakened immune systems.

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More Information
Statistics 4658 Interactions with Other Bacteria NCBI Data Punk End Products Produced

Lab Reporting

Different labs use different software to read the sample. See this post for more details.
One lab may say you have none, another may say you have a lot! - This may be solely due to the software they are using to estimate.
We deem lab specific values using values from the KM method for each specific lab to be the most reliable.

Desired Levels Suggestions for Haemophilus parainfluenzae

Using Kaltoft-Moldrup Heuristic Using uploaded data for Haemophilus parainfluenzae

Lab Low and High are calculated using the formula that most labs use: Mean - 2 Standard Deviation to Mean + 2 Standard Deviation

These are values that are computed from lab specific samples (Patent Pending)
LabKM LowKM Percentile LowKM HighKM Percentile HighLab LowLab HighMeanStandard Deviation
All 0.003 9.3 %ile 2.208 98.3 %ile 0 1.66 0.196 0.747
BiomeSight 0.001 0 %ile 0.992 97 %ile 0 1.164 0.161 0.512
Ombre/Thryve 0.002 7.7 %ile 0.713 96.5 %ile 0 1.098 0.147 0.485
uBiome 0.002 0 %ile 4.534 98.5 %ile 0 3.206 0.405 1.429
Lab Suggestions for Haemophilus parainfluenzae
Haemophilus parainfluenzae (NCBI 729) per million
Low Boundary High Boundary Low Boundary %age High Boundary %age Lab Samples
0 100 0 0.01 XenoGene
Statistic by Lab Source for Haemophilus parainfluenzae
These desired values are reported from the lab reports
Lab Frequency Seen Average Standard Deviation Sample Count Lab Samples
Microba 26.667 %   0.099 %  0.155 % 8.0 30
CosmosId 39.474 %   0.1 %  0.341 % 15.0 38
es-xenogene 22.857 %   0.106 %  0.101 % 8.0 35
SequentiaBiotech 44.444 %   0.163 %  0.239 % 16.0 36
Thorne 100 %   0.091 %  0.163 % 55.0 55
uBiome 65.952 %   0.404 %  1.428 % 523.0 793
CerbaLab 100 %   0.011 %  0.01 % 3.0 3
Thryve 68.046 %   0.147 %  0.477 % 1069.0 1571
BiomeSight 74.418 %   0.164 %  0.517 % 1981.0 2662
custom 19.403 %   0.089 %  0.178 % 13.0 67

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Data Contradictions β€” Limits of Certainity

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General Substance Specific Substance Effect
Antibiotics, Antivirals etc ampicillin (antibiotic)s[CFS] 2 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc benzylpenicillin sodium (antibiotic) 1 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc beta lactam (antibiotic)s 1 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc cefotaxime sodium salt (antibiotic) 1 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc ceftriaxone (antibiotic)s 2 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc ciprofloxacin (antibiotic)s[CFS] 3 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc clindamycin (antibiotic)s[CFS] 1 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc doxycycline (antibiotic)s[CFS] 1 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc erythromycin (antibiotic)s[CFS] 1 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc fluoroquinolone (antibiotic)s 1 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc gentamicin (antibiotic)s 2 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc imipenem (antibiotic)s 2 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc meropenem (antibiotic)s 2 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc minocycline (antibiotic)s[CFS] 2 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc piperacillin-tazobactam (antibiotic)s 3 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc tetracycline (antibiotic)s 1 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc tobramycin (antibiotic)s 2 Studies recorded. The consensus is Decreases📓, Click for details.
Antibiotics, Antivirals etc vancomycin (antibiotic)[CFS] 2 Studies recorded. The consensus is Decreases📓, Click for details.
Common Supplements Exercise 1 Studies recorded. The consensus is Decreases📓, Click for details.
Diet Style low protein diet 1 Studies recorded. The consensus is Decreases📓, Click for details.
Food (excluding seasonings) ku ding cha tea 1 Studies recorded. The consensus is Increases📓, Click for details.
Herb or Spice cinnamon (oil. spice) 1 Studies recorded. The consensus is Decreases👶, Click for details.
Herb or Spice coriander oil 1 Studies recorded. The consensus is Decreases👶, Click for details.
Herb or Spice lavender 1 Studies recorded. The consensus is Decreases👶, Click for details.
Herb or Spice lemongrass oil 1 Studies recorded. The consensus is Decreases👶, Click for details.
Herb or Spice peppermint (spice, oil) 1 Studies recorded. The consensus is Decreases👶, Click for details.
Herb or Spice Perilla frutescens(shiso) 1 Studies recorded. The consensus is Decreases👶, Click for details.
Herb or Spice thyme (thymol, thyme oil) 1 Studies recorded. The consensus is Decreases👶, Click for details.
Herb or Spice wormwood(artemisia) 1 Studies recorded. The consensus is Decreases📓, Click for details.
Prescription - Other proton-pump inhibitors (prescription) 2 Studies recorded. The consensus is Increases👶📓, Click for details.
Probiotics bacillus subtilis natto (probiotics) 1 Studies recorded. The consensus is Increases📓, Click for details.
Probiotics bifidobacterium longum bb536 (probiotics) 1 Studies recorded. The consensus is Increases📓, Click for details.
Probiotics lactobacillus kefiri (NOT KEFIR) 1 Studies recorded. The consensus is Decreases📓, Click for details.
Probiotics lactobacillus rhamnosus (probiotics) 1 Studies recorded. The consensus is Increases📓, Click for details.
Vitamins, Minerals and similar vitamin d 1 Studies recorded. The consensus is Decreases📓, Click for details.

All suggestions are computed solely on their predicted microbiome impact. Safety, side-effects etc must be evaluated by your medical professionals before starting. Some items suggests have significant risk of adverse consequences for some people.

Special thanks to David F Morrison and Geert Van Houcke for doing Quality Assurance. Special thanks to Oliver Luk, B.Sc. (Biology) from BiomeSight for spot checking the coding of data from the US National Library of Medicine

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