Alright, where was I? Yes, after a long hiatus from this page due to my varying and burdensome commitments, I am finally back to the arms of popular medicine. I am back and am here to stay- if anyone is interested in what I have been up to, just keep on reading- this post has the potential to end up as a regurgitating ramble of all of my values and my personality.
Medicine is a commitment - it is not always easy to claim that medicine is merely a subject where you merely need to know where to search for stuff, albeit there is some truth in it. Apart from the hardware, in which I am duly referring to the knowledge that comes with medical education (the endless pages of Guyton & Hall, and Davidson's that all medical students have to recite by heart...of course, as I mentioned previously, I much prefer online resources since textbooks run the risk of being outdated), one also needs to develop one's software- of which I am referring to one's communication skills, and ability to relate to patients (the notorious 'empathy' which is reiterated at least thousands of times in those medical ethics seminars we are all forced to attend if we want to pass the year). Medicine is also a song- every patient's story is a melody on its own. The variation of notes, the undulating flow of musical rhythm, as well as the richness of lyrics, all contribute to the uniqueness of individual patient accounts. I am extremely glad that the medical community has finally taken its first step to step away from the shadows of its past, henceforth recognising the importance of personalised medicine, i.e. treating patients according to their individual needs instead of resorting to rigid and stiff algorithms which represent the majority, not the whole. Of course, given the constraints of healthcare, where a general practitioner (GP) is only given 8 minutes to deal with an individual patient, it is fanatical to claim that every patient to be subjected to the assumed rigour pertinent to the popular definition of personalised medicine- tailoring the needs of every single patient to the most alarmingly minute detail. But then, as with all else medicine, it is a blend of conventional medicine and personalised medicine - for simpler cases, we can reduce the personalised component so that while the major needs of the patient are duly met, efficiency can be preserved. For instance, if a patient comes in with regular frontal headaches, facial pain, and a runny nose, where such symptoms have lasted for five days, then it is only reasonable to assume the patient has acute sinusitis and should be given supportive therapy (assumed viral pathology). However, if, at the same time, the patient shows signs of depression, or deeper family issues, we should not negate or dismiss their suffering by putting these issues down lightly. They are equally important. Talk to the patient, understand their needs and manage their expectations. If required, we can write a psychiatric referral- in this case, we are meeting the patient's needs holistically. This is, to me, how we should maximise patient satisfaction without compromising the efficiency of care provision.
In this period, I have published quite a number of scientific papers- if anyone is interested, you're welcome to throw a glance. I am going to put them on the page anyway (in full references). This brings me to the next point: research. After launching a diatribe against the ills of conventional medicine, I must concede that in medical research, a field which talks in numbers rather than words (in most cases; I can bet that most doctors jump straight to the figures, tables, and charts, when reading scientific papers), conventional medicine, as opposed to personalised medicine, plays a fundamental role. Research focuses on the reproducibility of a treatment. This may seem contrary to what I have said, but we can dissect this argument to make it easier to understand. What if I say that we need to establish the safety and efficacy of a treatment modality (e.g. a particular drug, or a combination of different drugs) in the general population, before exploring its efficacy in special populations? What if I say that this is not merely because of scientific convention, but also because of a multitude of reasons? The use of collective statistics enhances the reproducibility and replicability of data. It means that if a drug works in 80% of the population, let's say, then it is worth manufacturing and distributing in the wider market. For the remaining 20%, although the drug is not very effective or even dangerous, they can be given other drugs. This does not only incentivise large pharmaceutical companies to synthesise different drugs (after all, Big Pharma is only motivated to produce drugs if they are needed in large quantities), but also allows us to help the maximum number of patients. If we test drugs on individual patients without knowing its safety profile and somatic effects, even if the drug works on that single patient, there is no telling if the drug can help other patients. There is no telling whether the patient's condition may worsen at a later stage - in other words, we are uncertain as to how the course of illness is modified by the drug. If I may add an additional argument, by getting the 'gist' of a drug by testing it on a statistically representative sample, we can be 'more' certain (not completely certain; remember that drugs can also behave in ways we have never predicted. An analogy can be drawn with the AstraZeneca COVID-19 vaccine and reported incidents of immune thrombocytopenic purpura) of the characteristics, both chemical and clinical, of the drug. Therefore, we can select the most appropriate drugs for patients, bearing in mind their personal characteristics and how they interact with those of the drug(s).
Seeing how important holistic care is, I guess this is also the high time to make a public health point regarding vaccination: we need to carry out more studies on whether booster doses are required for immunocompromised patients, including those afflicted by cancer and autoimmune disorders.
After all, vaccines are for the many, not the few.
Comments