#pharmacetuical

[cloudbasedsoftwareblog]

What is Sales Analytics?

Sales involve decisions based on limited information. Sales analytics helps in the discovery of insights and increasingly helps sales managers for taking the best decisions. Sales reports are a vital part of this process, and sales analytics have become a major portion of each sales report. Sales analytics allow firms to break down sales into manageable pieces and examine exactly what is working and what needs to improve.

Sales analytics helps sales managers understand where salespeople may improve by discovering, modelling, interpreting, and predicting sales trends and outcomes. As part of an analytic or planning activity, sales analytic systems provide a capability that enables discovery, diagnostic, and prediction exercises by allowing manipulation of parameters, measures, dimensions, or figures.

The use of sales analytics software is quickly increasing in the commercial world. We’ve outlined a few of the main reasons why the software should be a vital part of every sales director’s report below. So, in this sales analytics blog, we will talk about sales analytics software and the importance of analytics software.

To read more please click on below link.

Link: https://www.espine.in/blog/importance-of-sales-analytics-software/

[lackofhonor]

Rant begin. Just me venting.

...

Went to run with my running club this evening for a quick couple miles and got there mid conversation between two other members, both of whom are late 40s to early 60s. They are discussing adult children who continue living with their parents after 18 and how they can't believe how "kids" now just are content with "gaming and living in their parents' basement instead of moving out".

Me: "I didn't hear the situation you are discussing but it is actually quite expensive to rent a place. The going rate here (under 100k pop. city) is about $600 to $620 a month for a one bedroom. I currently rent at a slightly lower rate because I help my landlord around the property. For a lot of young adults working multiple jobs or fresh out of schooling it isn't always possible to afford a place on their own. Sometimes a roommate helps but you have to find someone reliable enough to rent with so you don't end up holding the bag.

Them: "But too many kids just don't want to try because they have it so good with their parents. "

Me: "That might be true. Everyone's experience is different. I am just saying it isn't always as easy as it seems. Prices vary with location and sometimes it is just as smart to stay put if you can and save money. Like I said I am currently renting and I know it can be hard."

Am I the asshole? Because these guys sure as shit have not been renting anytime in the last twenty years I guarantee you. One is a retired pharmacetuical salesman and not sure what the other guy does/did. I don't mean to insert myself but my tank for tolerating bullshit is low and I am about fucking tired of hearing this fucking bootstrap logic. Love my running club but it is very very middle to upper middle class/affluent and sometimes I wanna whack people for saying shit like this.

Maybe I am getting old too, but I feel like if you didn't have to be a young adult (18-25) or struggling adult (No age range thanks) from 2007 on your opinion on things like renting, wages, health insurance coverage etc is pretty well out of date.

I am having a hard time finding people I can connect with because while I was able to obtain my bachelors, I am just educated enough to be dangerous and want to discuss complex issues but also just poor and working class enough that I am always an outsider. Like I had a chat with someone who thought he grew up poor because his family farmed. His family had 1500+ head of cattle, owns over 2k acres and farms double that via rented ground. When I asked him why he thought he grew up poor he said his father didn't have a bachelor's degree and all the money went back into the farm. I asked if they ever had to go without or not seek medical care or put any of their assets for sale because the farm was in trouble. He said no. His father also paid for each of his children to obtain their college education. My face: 😐 You know just because your father didn't have a college degree and farms doesn't necessarily mean you were poor. It sounds like you were asset rich but cash poor, which is very different from living near or below poverty line. Him: 🤑Nah I was poor.

Same person after I expressed being a little overwhelmed lately with my full time job, back injury, side gig cleaning/house sitting and part time job as a crisis counselor: "Aw you need to slow down. Tell me what's on your mind. You'll feel better."

Me: "Thanks but I really don't feel like you can relate to my experience right now."

Yet he is offended? This is why I don't even bother trying with a lot of people. It's fine for them to dump on you but when they can't or won't do the same for you suddenly you're the problem for either not sharing or sharing and their inability to empathize makes you feel worse. 😱😱😱

Rant over...

[pharmacylabequipments]

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[peacewise08]

fukido training like old man

fukido training like old man

fukido is a place, a company, a small business, a pharmacetuical, an urban dictionary definition is the act of sport sex, and also it is not associated with aikido in any way shape or form that I am aware. decades of images One-TimeMonthlyYearly If you care to please make a one-time donationPlease choose to gift a monthly donationPlease choose to gift a yearly donation Please choose an amount…

[kathleenseiber]

How your brain decides to put in effort

Researchers have clear visual evidence that a region of the human brain known as the ventral striatum kicks in during decision-making to weigh the costs versus the benefits of making a physical effort.

The research gives the first detailed view of ventral striatum activity during three phases of effort-based decision-making—the anticipation of initiating an effort, the actual execution of the effort, and the reward, or outcome, of the effort.

“It’s important to understand the neural mechanisms underlying motivation,” says first author Shosuke Suzuki, a graduate student of psychology at Emory University.

“Our work has wide implications for treatment of disorders related to reduced motivation, such as depression, schizophrenia, and PTSD. It may also help enhance motivational programs for everything from education to athletics and public health.”

Decision mystery

“The willingness to expend effort is something crucial to our survival and something that we use every day,” adds senior author Michael Treadway, a research professor in the psychology department and psychiatry and behavioral science department.

“We’ve identified two closely overlapping, but nevertheless distinct, areas of the ventral striatum involved with different phases of effort-based decision-making,” Treadway says. “And with the sub-regions we’ve identified, we’ve provided a concrete neuroimaging tool to measure the sensitivity of signals associated with these phases that others can apply to their own data.”

For example, Treadway says, the new method could provide a window into how a drug is affecting the brains of patients suffering from motivational deficits, compared to controls.

The ventral striatum, located deep within the brain’s cerebral hemispheres, is an area associated with movement and mediating rewarding experiences and motivation.

Neuroimaging has consistently shown that the ventral striatum activates during decision-making to encode the potential value of rewards relative to costs, such as wait times and probability. The ventral striatum helps you decide whether to pay more for “next-day” delivery or choose “free, one-week” delivery to receive a package.

Neuroimaging studies had previously failed, however, to detect a strong value signal in the ventral striatum for decisions that require a physical effort. If you want more coffee, but the pot is empty, is it worth getting up and brewing some more?

“It was a mystery why this brain region encoded the value of a reward versus time and probability but did not appear to do so for physical effort,” Suzuki says. “It’s been a paradox in the neuroimaging literature.”

Imaging brains

Previous research on rodents showed that the ventral striatum is critical for motivating an animal to work for rewards like food. Animal research also shows evidence for two opposing signals in the ventral striatum. An activation signal prepares an animal to work and a discounting signal helps an animal select rewards that require the least effort. These signals help animals work for what they need, while also making sure they don’t work more than they have to.

The presence of these signals had never been tested in humans. The researchers theorized that as the physical cost to perform a task rises, the activation signal would drive an increase in activity in the ventral striatum, while the discounting signal would drive a decrease. They proposed that the simultaneous firing of these two signals—the cost of effort versus the activation of effort itself—is what made it harder to detect the value signal in previous studies.

An additional complication to detecting brain activation associated with physical effort is the fact that neuroimaging requires participants to lie still within a functional Magnetic Resonance Imaging (fMRI) machine while it scans their brains.

To get around these issues, the researchers designed fMRI experiments that would allow participants to remain in a supine position and would also separate the neural signals involving effort from the one associated with the cost of the effort.

For the first set of experiments, the researchers created a virtual maze. As their brains were scanned, study participants were presented with maze navigation tasks that required different levels of effort. In one condition, the participants watched themselves move through the virtual maze passively. In another condition, they simply pressed a button on a handheld device to move through the maze. A third condition required the higher effort of repeatedly and rapidly pressing the button to move through the maze. Each maze, when successfully completed, rewarded them with a nominal dollar amount.

During a second experiment, the neural activity of participants was measured as they made a series of choices between two options, with varying amounts of reward and effort required for each option. The effort and reward amounts were presented sequentially to try to isolate the effort-activation signal during the anticipation of various effort demands.

The results showed that two distinct regions of the ventral striatum fired in response to different phases of physical effort and effort-based decision making, with some overlap. Activity in an anterior region was mainly associated with reward and effort costs, while activity in a dorsal region was mainly associated with initiation of effortful movement. And this activity related to effortful movement was distinct from activity in another region, called the putamen, which was associated with initiation of simple movement.

Motivational deficits

The researchers now hope to build upon this increased awareness for how the brain encodes signals related to motivation.

“Our current paper provides a paradigm for how to measure brain activity for effort-based decisions associated with assigned tasks,” Suzuki says. “Now we’re developing experiments to identify specific modes of signaling when people spontaneously initiate action. That may give us a better measure of how the brain operates when people do things because they want to do them, in real-life situations.

“Getting sensitive measurements for how people normally decide to expend effort may help us develop better treatments for people suffering motivational deficits related to depression or other illnesses.”

Funding for the work was funded by grants from the National Institute for Mental Health and the National Science Foundation Graduate Research Fellowship Program. For the past three years, Treadway served as a paid consultant for Blackthorn Therapeutics and Avanir Pharmacetuicals, but neither of these entities supported the current work, which is solely the views of the authors.

Source: Emory University

The post How your brain decides to put in effort appeared first on Futurity.

How your brain decides to put in effort published first on https://triviaqaweb.weebly.com/

[philsom-blog]

There are still questions about how precise exactly crispr is, what might the side effects be? THere is a chance of off-target-effects, you could think you are editting one thing, maybe the crispr component editted something else too. Or the gene we thought just does this ONE thing does something really important that we didn’t know. In America, if crispr editting leads to organisms that could not have been created the same by long-term breeding, they are viewed as new drugs and have to go through a huge testing phase.

As a new animal pharmacetuical drug Brazil and argentina have a very “relaxed” regulatory standpoint on gene editing Our immune systems may reject CAS9 if they dealt with a bacteria that also carries this protein, so in that case crispr wouldnt work at all.

[livingwellpage]

Health plans getting into the PBM game

Bloomberg reports that Anthem is creating is own pharmacy benefits manager (PBM).  Why?  It says it wasn’t getting a good deal from PBMs.

Health insurer Anthem Inc. plans to set up its own pharmacy benefits management unit, signaling a final break with Express Scripts Holding Co. after accusing it of overcharging by billions of dollars.

The move means Express Scripts will not only lose its biggest client but also face a new rival. Anthem’s new unit, called IngenioRx, will grow its own business with a “full suite” of services, the insurer said in a statement on Wednesday.

How much was the overcharging?  Anthem says the amount was $3 billion.

With drug prices on the rise, both pharma and PBM’s blame each other for high prices.  PBMs say that drug list prices are too high.  Pharmacetuical firms say they need to raise prices in order to offset large discounts and rebates that PBMs are demanding.

Anthem may not be the only firm entering the PBM market.  Amazon is also considering entering the PBM market.  UnitedHealth–Anthem’s top competitor–already has an in-house PBM known as OptumRx.

The one thing that is certain in the PBM world is that things are changing.

  Health plans getting into the PBM game published first on your-t1-blog-url

[marymillera6]

Causality: Bradford Hill criteria

If you observe two things occuring, how can you know whether event A causes event B. For instance, consider the case of patients who use a given treatment and finding that they have better health outcomes. While this relationship could be causal in nature, it may not be. For instance, if only people with higher socioeconomic status can afford the treatment and these same individuals are likely to have better health outcomes due to other factors (e.g., more flexible work schedules, more family support) than there may not be a causal relationship at all.

So how do we determine if some event A is causal of event B? In the medical literature, Bradford Hill criteria are often used. These are:

Strength (effect size): A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal. Consistency (reproducibility): Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Specificity: Causation is likely if there is a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship. Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). Biological gradient: Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.[1] Plausibility: A plausible mechanism between cause and effect is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge). Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. However, Hill noted that “… lack of such [laboratory] evidence cannot nullify the epidemiological effect on associations”. Experiment: “Occasionally it is possible to appeal to experimental evidence”. Analogy: The effect of similar factors may be considered.

These items are sensible. However, they do not derive from first principles. Instead, they look at logically, the likelihood that an observed phenomenon is causal, but do not put specific numeric limits. Let’s delve into each of these criteria in turn.

Strength: There is no reason why a causal effect need be strong. For instance, if we want to know what factors moved a toy boat forward, a small breath may move it slightly. The breath is clearly causal even though the effect is small. The reason for the strength criterion, however, likely is that in the real world, observations are made with a lot of noise (e.g., measurement error, selection bias, etc.). A strong relationship is more likely to be causal since it my not be overwhelmed by these other factors. Perhaps, the strength criterion should be used if we want to look at the principal causes of some effect.

Consistency. If A causes B, and we observed B to occur after A in one case, it would be more convincing if every time A occurred, B occurred. For instance, if we want to show that snow causes ice, we could show that times when it snows, water turns to ice. However, if we can show that ice sometimes appear without snow, then clearly snow cannot cause ice. Thus, the consistency criterion is only valid so long as the reproducible tests or observations chosen are sufficiently diverse in order for the different observations to prove informative.

Specificity. This would be close to the causal pathway. If we see that treatment A improves health outcomes B, but don’t know why, it is less clear that this is causal. If we know that treatment A increases the production of protein P, we would expect to see patients with lower levels of protein P to see a bigger improvement in health outcomes. More specific proposed causal pathways can also be flawed, but it is helpful to understand the mechanism through which any causal effect could occur.

Temporality. Causes occur before effects. Makes sense.

Biological gradient. This causal pathway makes sense only for linear causal relationships. If I want to know whether ice makes people’s skin cold, I could test to see if more ice makes people’s skin more cold. However, if I am looking at a pharmacetuical and want to measure its effect on quality of life, increasing the dose from something minimal would likely improve health outcomes. Setting the dose too high, however, may lead to serious adverse events. Thus, the biological gradient criteria may fail in non-linear causal relationships.

Plausibility. This is a very subjective criterion. In practice, scientists often consider plausibility when making decisions on the likelihood of causality, but just because a relationship seems unlikely does not make it the case that it can’t be causal.

Coherence. I would similar evidence from lab and epidemiological studies helps to make the causal case. There may be cases, however, where the evidence differs, such as in cases where laboratory settings and real-world settings differ. In the case of clinical trials, patients receiving treatments outside of clinical trials often differ from those who enroll.

Experiment. If you could replicate the phenomenom to be studied in a lab setting and then test how including or removing a cause effects results, this would be strong evidence.

Analogy. Like plausibility, in practice, scientists are likely to see if there is evidence from analogous cases for causality. Failure to find an appropriate analogy, however, does not preclude a causal a relationship, particularly for novel phenomenon. Perhaps more importantly, finding an analogy does not mean that the phenomenon under investigation is causal.

In short, the Bradford Hill criteria provide some useful, practical guidelines for causality. Some of the criteria, however, are vague and they leave a lot of room for investigator judgment. One piece of advice from Potischman and Weed (1999) that I agree with is that Bradford Hill criteria should be used as a guide, but not as a list of criteria to definitively determine causality.

[venusremediespharma]

The Most Common Fever Types

Are you feeling under the weather? Well, fear not because we've got just the remedy for you! Check out our latest blog post on "The Most Common Fever Types" and arm yourself with all the information you need to tackle that pesky fever head-on. From low-grade fevers to high fevers, we cover it all in this comprehensive guide. Dive into the world of body temperatures and learn how to distinguish between different types of fevers so you can take control of your health like never before. So grab a cup of tea, get cozy, and let's unravel the mysteries of fevers together!

Learn more:

https://venusremedies.com/blog/common-fever

[maxihealth]

Causality: Bradford Hill criteria

If you observe two things occuring, how can you know whether event A causes event B. For instance, consider the case of patients who use a given treatment and finding that they have better health outcomes. While this relationship could be causal in nature, it may not be. For instance, if only people with higher socioeconomic status can afford the treatment and these same individuals are likely to have better health outcomes due to other factors (e.g., more flexible work schedules, more family support) than there may not be a causal relationship at all.

So how do we determine if some event A is causal of event B? In the medical literature, Bradford Hill criteria are often used. These are:

Strength (effect size): A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal. Consistency (reproducibility): Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Specificity: Causation is likely if there is a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship. Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). Biological gradient: Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.[1] Plausibility: A plausible mechanism between cause and effect is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge). Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. However, Hill noted that “… lack of such [laboratory] evidence cannot nullify the epidemiological effect on associations”. Experiment: “Occasionally it is possible to appeal to experimental evidence”. Analogy: The effect of similar factors may be considered.

These items are sensible. However, they do not derive from first principles. Instead, they look at logically, the likelihood that an observed phenomenon is causal, but do not put specific numeric limits. Let’s delve into each of these criteria in turn.

Strength: There is no reason why a causal effect need be strong. For instance, if we want to know what factors moved a toy boat forward, a small breath may move it slightly. The breath is clearly causal even though the effect is small. The reason for the strength criterion, however, likely is that in the real world, observations are made with a lot of noise (e.g., measurement error, selection bias, etc.). A strong relationship is more likely to be causal since it my not be overwhelmed by these other factors. Perhaps, the strength criterion should be used if we want to look at the principal causes of some effect.

Consistency. If A causes B, and we observed B to occur after A in one case, it would be more convincing if every time A occurred, B occurred. For instance, if we want to show that snow causes ice, we could show that times when it snows, water turns to ice. However, if we can show that ice sometimes appear without snow, then clearly snow cannot cause ice. Thus, the consistency criterion is only valid so long as the reproducible tests or observations chosen are sufficiently diverse in order for the different observations to prove informative.

Specificity. This would be close to the causal pathway. If we see that treatment A improves health outcomes B, but don’t know why, it is less clear that this is causal. If we know that treatment A increases the production of protein P, we would expect to see patients with lower levels of protein P to see a bigger improvement in health outcomes. More specific proposed causal pathways can also be flawed, but it is helpful to understand the mechanism through which any causal effect could occur.

Temporality. Causes occur before effects. Makes sense.

Biological gradient. This causal pathway makes sense only for linear causal relationships. If I want to know whether ice makes people’s skin cold, I could test to see if more ice makes people’s skin more cold. However, if I am looking at a pharmacetuical and want to measure its effect on quality of life, increasing the dose from something minimal would likely improve health outcomes. Setting the dose too high, however, may lead to serious adverse events. Thus, the biological gradient criteria may fail in non-linear causal relationships.

Plausibility. This is a very subjective criterion. In practice, scientists often consider plausibility when making decisions on the likelihood of causality, but just because a relationship seems unlikely does not make it the case that it can’t be causal.

Coherence. I would similar evidence from lab and epidemiological studies helps to make the causal case. There may be cases, however, where the evidence differs, such as in cases where laboratory settings and real-world settings differ. In the case of clinical trials, patients receiving treatments outside of clinical trials often differ from those who enroll.

Experiment. If you could replicate the phenomenom to be studied in a lab setting and then test how including or removing a cause effects results, this would be strong evidence.

Analogy. Like plausibility, in practice, scientists are likely to see if there is evidence from analogous cases for causality. Failure to find an appropriate analogy, however, does not preclude a causal a relationship, particularly for novel phenomenon. Perhaps more importantly, finding an analogy does not mean that the phenomenon under investigation is causal.

In short, the Bradford Hill criteria provide some useful, practical guidelines for causality. Some of the criteria, however, are vague and they leave a lot of room for investigator judgment. One piece of advice from Potischman and Weed (1999) that I agree with is that Bradford Hill criteria should be used as a guide, but not as a list of criteria to definitively determine causality.

Causality: Bradford Hill criteria posted first on https://carilloncitydental.blogspot.com

[cloudbasedsoftwareblog]

Spine software systems is a group that deals in cloud-based solutions for pharmaceutical wholesalers, retailers, and manufacturers.

Spine makes the work easy by offering billing, accounting, inventory, and ERP software.

The beauty of Spine’s software is user-friendliness and cloud technology which can be used by mobile or desktop anywhere at any time, just need the internet.

So if you belong to the pharmaceutical sector and are willing to have the solution to make your work automatic through the software, then visit Spine’s official website.  

[realselfblog]

Causality: Bradford Hill criteria

If you observe two things occuring, how can you know whether event A causes event B. For instance, consider the case of patients who use a given treatment and finding that they have better health outcomes. While this relationship could be causal in nature, it may not be. For instance, if only people with higher socioeconomic status can afford the treatment and these same individuals are likely to have better health outcomes due to other factors (e.g., more flexible work schedules, more family support) than there may not be a causal relationship at all.

So how do we determine if some event A is causal of event B? In the medical literature, Bradford Hill criteria are often used. These are:

Strength (effect size): A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal. Consistency (reproducibility): Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Specificity: Causation is likely if there is a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship. Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). Biological gradient: Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.[1] Plausibility: A plausible mechanism between cause and effect is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge). Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. However, Hill noted that “… lack of such [laboratory] evidence cannot nullify the epidemiological effect on associations”. Experiment: “Occasionally it is possible to appeal to experimental evidence”. Analogy: The effect of similar factors may be considered.

These items are sensible. However, they do not derive from first principles. Instead, they look at logically, the likelihood that an observed phenomenon is causal, but do not put specific numeric limits. Let’s delve into each of these criteria in turn.

Strength: There is no reason why a causal effect need be strong. For instance, if we want to know what factors moved a toy boat forward, a small breath may move it slightly. The breath is clearly causal even though the effect is small. The reason for the strength criterion, however, likely is that in the real world, observations are made with a lot of noise (e.g., measurement error, selection bias, etc.). A strong relationship is more likely to be causal since it my not be overwhelmed by these other factors. Perhaps, the strength criterion should be used if we want to look at the principal causes of some effect.

Consistency. If A causes B, and we observed B to occur after A in one case, it would be more convincing if every time A occurred, B occurred. For instance, if we want to show that snow causes ice, we could show that times when it snows, water turns to ice. However, if we can show that ice sometimes appear without snow, then clearly snow cannot cause ice. Thus, the consistency criterion is only valid so long as the reproducible tests or observations chosen are sufficiently diverse in order for the different observations to prove informative.

Specificity. This would be close to the causal pathway. If we see that treatment A improves health outcomes B, but don’t know why, it is less clear that this is causal. If we know that treatment A increases the production of protein P, we would expect to see patients with lower levels of protein P to see a bigger improvement in health outcomes. More specific proposed causal pathways can also be flawed, but it is helpful to understand the mechanism through which any causal effect could occur.

Temporality. Causes occur before effects. Makes sense.

Biological gradient. This causal pathway makes sense only for linear causal relationships. If I want to know whether ice makes people’s skin cold, I could test to see if more ice makes people’s skin more cold. However, if I am looking at a pharmacetuical and want to measure its effect on quality of life, increasing the dose from something minimal would likely improve health outcomes. Setting the dose too high, however, may lead to serious adverse events. Thus, the biological gradient criteria may fail in non-linear causal relationships.

Plausibility. This is a very subjective criterion. In practice, scientists often consider plausibility when making decisions on the likelihood of causality, but just because a relationship seems unlikely does not make it the case that it can’t be causal.

Coherence. I would similar evidence from lab and epidemiological studies helps to make the causal case. There may be cases, however, where the evidence differs, such as in cases where laboratory settings and real-world settings differ. In the case of clinical trials, patients receiving treatments outside of clinical trials often differ from those who enroll.

Experiment. If you could replicate the phenomenom to be studied in a lab setting and then test how including or removing a cause effects results, this would be strong evidence.

Analogy. Like plausibility, in practice, scientists are likely to see if there is evidence from analogous cases for causality. Failure to find an appropriate analogy, however, does not preclude a causal a relationship, particularly for novel phenomenon. Perhaps more importantly, finding an analogy does not mean that the phenomenon under investigation is causal.

In short, the Bradford Hill criteria provide some useful, practical guidelines for causality. Some of the criteria, however, are vague and they leave a lot of room for investigator judgment. One piece of advice from Potischman and Weed (1999) that I agree with is that Bradford Hill criteria should be used as a guide, but not as a list of criteria to definitively determine causality.

Causality: Bradford Hill criteria posted first on http://dentistfortworth.blogspot.com

[quintinefowler-blog]

Emphysema: The Smoker’s Disease

Emphysema is a respiratory disease that continues to get worse over time. It makes it hard to breathe and causes an individual to feel as if they are constantly short of breath.

The tiny air sacs and airways in the lungs lose their elastic qualities and this in turn makes it hard to completely exhale the air from the body.

Normal lungs work like a balloon and bring in vast amounts of fresh air and then release equal amounts of Co2. When emphysema is present some of this carbon dioxide is left in the lungs and each breath becomes more difficult. As this terrible medical condition becomes worse breathing starts to come at great effort and physical activities take a great amount of energy.

Emphysema usually develops over years and there are treatments that can slow it's progress. Some symptoms that you should be on the lookout for include: consistent shortness of breath, headaches, constant coughing, fatigue, wheezing, difficulty concentrating, tightness in the chest, irritability and a distended chest.

If you have one or more of these symptoms then you should see a doctor for testing. You will receive a physical and the doctor will look closely at your medical history. If you are a smoker the doctor will be very interested in this. You might receive tests to check the functioning of your lungs, blood tests, X-rays or a CT-scan.

Smoking is the leading cause of emphysema. The chemicals in cigarettes irritate the airways and alveoli in the lungs and end up causing extensive damage. As the smoke, or other particles, reach the lungs macrophages are released to destroy them. This is good, but the bad part is they also kill off essential proteins that are responsible for keeping the lungs elastic in quality.

Another condition that can cause emphysema is a deficiency of the protein alpha-1-antitrypsin. This proteins main job is to make sure the lungs keep their elasticity. This condition runs in families and is often the cause of emphysema in people who have never smoked.

Herbal medicine can help to support your lungs and often work well with a conventional treatment plan. Matricaria recutita and astralagus can help to lessen the spasms and inflammation. Mag Phos and Nat Sulph can also help to lessen the constriction on your throat and chest. Phlegm is a major problem with emphysema and these can help to reduce it.

Effective Treatment for Bronchitis and Asthma

BronchoSoothe is a proven, safe and effective natural remedy that contains a combination of biochemic tissue salts which promotes easy, comfortable and normal breathing for bronchitis and asthma sufferers.

Regular use ensures systemic balance of biochemic tissue salts in the body, optimizes health at the cellular level, relieves symptoms of disease, restores health and vitality, optimizes the therapeutic effects of other remedies by improving systemic functioning and metabolism.

Formulated by our team of experts in natural medicine, BronchoSoothei s pharmacetuically manufactured to the highest standards.

Learn more about BronchoSoothe now. Why do we promote this?

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Emphysema: The Smoker’s Disease

Emphysema is a respiratory disease that continues to get worse over time. It makes it hard to breathe and causes an individual to feel as if they are constantly short of breath.

The tiny air sacs and airways in the lungs lose their elastic qualities and this in turn makes it hard to completely exhale the air from the body.

Normal lungs work like a balloon and bring in vast amounts of fresh air and then release equal amounts of Co2. When emphysema is present some of this carbon dioxide is left in the lungs and each breath becomes more difficult. As this terrible medical condition becomes worse breathing starts to come at great effort and physical activities take a great amount of energy.

Emphysema usually develops over years and there are treatments that can slow it’s progress. Some symptoms that you should be on the lookout for include: consistent shortness of breath, headaches, constant coughing, fatigue, wheezing, difficulty concentrating, tightness in the chest, irritability and a distended chest.

If you have one or more of these symptoms then you should see a doctor for testing. You will receive a physical and the doctor will look closely at your medical history. If you are a smoker the doctor will be very interested in this. You might receive tests to check the functioning of your lungs, blood tests, X-rays or a CT-scan.

Smoking is the leading cause of emphysema. The chemicals in cigarettes irritate the airways and alveoli in the lungs and end up causing extensive damage. As the smoke, or other particles, reach the lungs macrophages are released to destroy them. This is good, but the bad part is they also kill off essential proteins that are responsible for keeping the lungs elastic in quality.

Another condition that can cause emphysema is a deficiency of the protein alpha-1-antitrypsin. This proteins main job is to make sure the lungs keep their elasticity. This condition runs in families and is often the cause of emphysema in people who have never smoked.

Herbal medicine can help to support your lungs and often work well with a conventional treatment plan. Matricaria recutita and astralagus can help to lessen the spasms and inflammation. Mag Phos and Nat Sulph can also help to lessen the constriction on your throat and chest. Phlegm is a major problem with emphysema and these can help to reduce it.

Effective Treatment for Bronchitis and Asthma

BronchoSoothe is a proven, safe and effective natural remedy that contains a combination of biochemic tissue salts which promotes easy, comfortable and normal breathing for bronchitis and asthma sufferers.

Regular use ensures systemic balance of biochemic tissue salts in the body, optimizes health at the cellular level, relieves symptoms of disease, restores health and vitality, optimizes the therapeutic effects of other remedies by improving systemic functioning and metabolism.

Formulated by our team of experts in natural medicine, BronchoSoothei s pharmacetuically manufactured to the highest standards.

Learn more about BronchoSoothe now. Why do we promote this?

[Read More ...] http://www.natural-holistic-health.com/emphysema-smokers-disease/