The Blindspots in Modern Medicine
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Modern medicine, despite its many strengths, has serious blindspots.
It is exceptional at acute care—treating crises, saving lives, relieving suffering.
But it performs poorly in prevention and root-cause repair.
Too often, it mistakes symptoms for diseases and treats numbers instead of restoring biology.
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1) The Flawed Dogmas Medicine Won’t Let Go Of
Medicine has a long history of clinging to flawed dogmas long after they’ve failed— from the miasma theory to today’s lipid-centric model of atherosclerosis.
We mistake correlation for cause and then build entire industries around it.
The calories-in/calories-out model of obesity, the salt-centric explanation of hypertension, and the glucocentric approach to diabetes all treat numbers, not biology.
And when dogma replaces inquiry, patients pay the price
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​2) Epistemic Capture: The Corrupted Operating System of Modern Medicine
When the operating system of science degrades, everything built on it follows. Epistemic capture means funding priorities, publication bias, guideline politics, and media amplification decide what “counts” as knowledge—and what is suppressed. Breakthroughs from rigorous thinkers get buried; weaker ideas with louder megaphones harden into doctrine.
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​3) Cargo-cult science — Ritual without understanding
We keep the outward forms—p-values, forest plots, guideline citations—while neglecting falsification, replication, mechanism, and curiosity. The childlike “why/why not?” disappears, and with it, correction.
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4)Top-down culture
Scientific research shifts from testing to learn to proving to defend the beliefs by top brass : DASH trials to lower BP revolved around salt; Lipid centric model demonized saturated fat.
Contradictions are labeled “paradoxes” instead of falsifications.
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​​5) Lack of Reasoning & Critical Thinking
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To evaluate evidence rigorously, the science needs Bayesian updating—weigh new results by how well they fit established biology—and prior plausibility—could this be true before the study? Keep humility about external validity (will it hold outside the trial?) and phenotype heterogeneity (same label, different mechanisms, different responses). To prove causation from correlation, Bradford Hill's criteria need to be met—temporality, strength/consistency, dose–response, plausibility/coherence, experiment/reversibility.
Critical thinking is critical to understand inherent uncertainty in medical science, and must design studies/experiments that could falsify the theory. When findings don’t cohere—or a black swan appears—revise or discard the model, instead of calling it an “unexplained paradox” and pressing on.
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6) Compartmentalized Medicine
Medicine is divided into compartments that rarely communicate.
Basic research, clinical research, patient care, and policy each operate in their own silos, with separate languages, incentives, and priorities.
Superspecialists deepen this fragmentation—treating organ-slices rather than the person as an integrated whole. The result is disconnected knowledge and incoherent models: data without synthesis, science without translation, and clinical care that manages symptoms instead of restoring physiology.
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7) The drug-centric architecture
Pharmacology has become the center of the enterprise. We identify a mechanism, immediately convert it into a target, design a drug, and build a market.
Discovery → development → publication → promotion → guideline.
Mechanism depth, phenotype fit, and long-term outcomes are often afterthoughts. We reverse-engineer disease around available drugs: bisphosphonates around the T-score, statins around “cholesterol,” and now an expanding machinery around Lp(a).
This profit-maximizing architecture starves anything that can’t be patented. Large, long-horizon trials of lifestyle and physiology repair are rarely funded; even public grants target drug therapy.
Most of drug trial are funded and managed by drug companies with limited oversight. Taxpayers subsidize the pipeline, then paying for the same drug—paying twice, and often priced out because of astronomical cost.
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8) Surrogate Outcomes and Statistical Illusions
Modern medicine often confuses improving a metric with improving health.
Surrogate endpoints—such as revascularization rates, hospital readmissions, “time to progression” in oncology, and composite outcomes that mix soft and hard endpoints—are treated as evidence of benefit. Yet these measures are often operator-dependent or statistically engineered, and do not reliably reflect meaningful outcomes patients actually experience.
Meanwhile, RRR (Relative Risk Reduction) makes small effects look large, while the real clinical decision tools—ARR (Absolute Risk Reduction), NNT, and NNH—rarely appear in the discussion.
We end up celebrating statist
Once a measure becomes the target (Goodhart’s law), the system optimizes the number, not reality.
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​9) Biomarker fixation
We’ve become obsessed with biomarkers and treat them as diseases instead of signals. We chase glucose, LDL, and blood pressure as if they were the problem, when they’re downstream consequences of disturbed homeostasis. The chart looks better but the patient is worse and the biology stays broken.
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10) Manufactured diseases & diagnosis
​Before a drug even reaches the market, the machinery of medicine often reshapes disease—or invents new ones—to fit the treatment. Diagnostic thresholds shift, “risk factors” are reclassified as diseases, and normal physiology is rebranded as pathology.
Post-menopausal osteoporosis is defined by an arbitrary T-score, converting normal aging into a lifelong medication commitment. Hyperlipidemia is treated as the disease itself, rather than as a biomarker—and a poor, unreliable one at that—fueling a trillion-dollar market around managing a number instead of addressing the underlying process.