Prevention represents the most cost-effective, long-term strategy for reducing the cancer burden and associated mortality. If provided with adequate information and support to adopt a healthy lifestyle, individuals can reduce their exposure to behavioural and dietary cancer risk factors by quitting smoking, maintaining a healthy BMI, cutting down on alcohol consumption, exercising more, and eating a healthy diet rich in fruit and vegetables.
Although smoking is currently the major cause of preventable cancer cases and accounts for 22% of cancer deaths, a 2018 report from Cancer Research UK estimated that high BMI (overweight and obesity) now causes more cases of four common cancers (bowel, kidney, ovarian, and liver) in the UK than does smoking, and could overtake smoking as the biggest cause of cancer in women in the UK by 2043. According to WHO, in 2016, 1·9 billion adults around the world were overweight, of whom 650 million had obesity—triple the number in 1975. State-level projections for the USA paint an even bleaker picture going forward: by 2030, 48·9% of adults will have obesity; 24·2% of adults will have severe obesity; and severe obesity will be the most common BMI category among women, non-Hispanic black adults, and low-income adults. With such shocking statistics, the knock-on effect of the obesity epidemic for cancer prevention and control cannot be underestimated.
From a The Lancet online article (January 18, 2020):
Smartphone app-based platforms for urine testing could improve adherence to albumin creatinine ratio (ACR) testing. One study showed screening of at-risk patients almost doubled with a home urine test kit that uses a smartphone camera to easily and accurately quantify ACR from a user-performed urine dipstick. If independently validated in a large, diverse population, this low-cost strategy could change the often dim trajectory for individuals with declining kidney function.
In the outpatient setting, a Japanese team used machine learning and natural language processing to predict disease progression and need for dialysis over 6 months in patients with diabetic nephropathy. And while the increased risk of contrast-induced acute kidney injury has been long appreciated, a machine learning algorithm trained and tested on 3 million adults effectively quantified the degree of kidney injury on the basis of the volume of contrast used and individual patient-level characteristics.
Effective physicians interrogate their patients’ choice of words as well as their body language; they attend to what they leave out of their stories as well as what they put in. More than 2000 years after Hippocrates, there remains as much poetry in medicine as there is science.
WHO’s definition of health is famously “a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity”. One of the oldest medical texts we know of, The Science of Medicine attributed to Hippocrates, sets out the goal of medicine in comparable terms: “the complete removal of the distress of the sick”.
In my working life as a physician, I’ve never found the distinction between arts and sciences a particularly useful one. In the earliest ancient Greek texts, medicine is described as a techne—a word better translated as “know-how”. It conveys elements of science, art, and skill, but also of artisanal craft. The precise functions of medicine may have subtly shifted over the ages, but our need as human beings for doctors remains the same; we go to them because we wish to invoke some change in our lives, either to cure or prevent an illness or influence some unwelcome mental or bodily process. The goal of medicine is, and always has been, the relief of human suffering—the word patient, from the Latin patientem, means sufferer. And the word physician is from the Greek phusis, or nature: to be engaged in clinical work is to engage oneself with the nature of illness, the nature of recovery, the nature of humanity.
…the researchers demonstrated that the biggest drop in cognitive ability occurs at the slightest level of hearing loss — a decline from zero to the “normal” level of 25 decibels, with smaller cognitive losses occurring when hearing deficits rise from 25 to 50 decibels.
As a consultant, I had profoundly failed to appreciate the experience of fatigue and apathy among patients. More than excessive tiredness, the fatigue was overwhelming, turning simple activities into insurmountable, exhausting challenges. It was frustrating and I fell into the trap of overexertion when I did have energy, thus exhausting myself and sabotaging the day’s recovery plan. Had staff not been so adept at encouraging me when I lacked energy and holding me back when I tried to overdo things, I would have squandered much valuable rehabilitation time.
I was a consultant in neurological rehabilitation for acquired brain injury when, at the age of 62 years, I had a stroke. Running for a train, I experienced pain in the right side of my head and mild weakness and sensory loss in my left limbs. I thought I’d had a stroke, but I was remarkably calm. It was late and my instinct was to get home, where I went to the study. In the morning, I found myself on the floor, half-blind, half-paralysed, and terrified.
Scans showed a large intracerebral haemorrhage in the area of the right basal ganglia. My symptoms could be explained by the damage to my brain—my medical world was in order, something to hold on to. I discussed my diagnosis and treatment with my colleagues during brief waking periods, grateful that they still saw the person I was before my stroke. Meanwhile, my wife was in the good hands of staff who treated her with sensitivity, giving her plain facts and support.
Our 3D deep-learning system performed well in both primary and external validations, suggesting that it could potentially be used for automated detection of glaucomatous optic neuropathy based on SDOCT volumes. Screening with the deep-learning system is much faster than conventional glaucoma screening methods (ie, by experienced specialists), can be done automatically, and does not require a large number of trained personnel on site. Further prospective studies are warranted to estimate the incremental cost-effectiveness of incorporating this artificial intelligence-based model for screening for glaucoma, both in the general population and among at-risk people.
Use of polypill was effective in preventing major cardiovascular events. Medication adherence was high and adverse event numbers were low. The polypill strategy could be considered as an additional effective component in controlling cardiovascular diseases, especially in LMICs.
When restricted to participants in the polypill group with high adherence, the reduction in the risk of major cardiovascular events was even greater compared with the minimal care group…
A fixed-dose combination therapy (polypill strategy) has been proposed as an approach to reduce the burden of cardiovascular disease, especially in low-income and middle-income countries (LMICs). The PolyIran study aimed to assess the effectiveness and safety of a four-component polypill including aspirin, atorvastatin, hydrochlorothiazide, and either enalapril or valsartan for primary and secondary prevention of cardiovascular disease.