Tag Archives: statistics

Rebuttal to “Opioids are Biggest Healthcare Problem”

Teater: Opioid problem biggest healthcare issue facing America [???]-  Nov 2018 – utter nonsense!

On the Inspire.com Opioid Information Thread, the member Seshet posted a brilliant rebuttal to the terribly mistaken article above:

The Cleveland Daily Banner has an article with Don Teater, MD, explaining how opioids should never be used for anything other than severe trauma or end-of-life care.

There are glaring errors in every paragraph.

Examples:   Continue reading

Automating clinical decisions with predictive analytics

Automating clinical decisions with predictive analytics – Twitter discussion from Terri A Lewis, PhD @tal7291

This is Dr. Lewis’ take on how Appriss is using the electronic health record (EHR) of pain patients to automatically calculate an “opioid risk score” and guide the doctor to prescribe less and/or add a naloxone prescription. (see EHR tool to assess patient risks for opioid abuse)

This kind of automated standardization flies in the face of the supposed intention to individualize treatments. Unfortunately, such personalized care is expensive, while standardization is cheap.

Allow me to point out the obvious. Med records are far too inconsistent, messy, wrong, incomplete for this to be a valid, reliable tool upon which to make clinical decisions that involve predictive analytics. JUST SAY NO.   Continue reading

The CDC Is Publishing Unreliable Data

The CDC Is Publishing Unreliable Data On Gun Injuries. People Are Using It Anyway. | FiveThirtyEight – Oct. 4, 2018 – By Sean Campbell, Daniel Nass and Mai Nguyen

For journalists, researchers and the general public, the Centers for Disease Control and Prevention serves as an authoritative source of information about Americans’ health, including estimates of how many people are killed or injured by guns.

This shows the CDC is using corrupted numbers to serve its own purposes and pushing a desired agenda, whether it be for gun control, flu shots, or opoids. See  my previous post, The CDC’s Math Doesn’t Add Up: Exaggerating Death Toll, for how the flu numbers were exaggerated.

I have now found two instances where the CDC has been caught inflating numbers to promote its desired conclusions (we must all get flu shots, we must have stricter gun control). So I believe we can assume the prescription opioid death numbers have been equally corrupted to promote the agenda that we must restrict prescription opioids because they are supposedly feeding the “opioid crisis”. Continue reading

CDC’s Math Doesn’t Add Up: Exaggerating Death Toll

The CDC’s Influenza Math Doesn’t Add Up: Exaggerating the Death Toll to Sell Flu Shots • Children’s Health Defense – October 09, 2018 – By the Children’s Health Defense team

Sometimes it’s interesting to get a look from a different viewpoint on a personal issue. This article was posted by people that are anti-vaccination, which I do not agree with; however, I see we share a healthy skepticism about the CDC’s data.

These folks see the same CDC shenanigans with flu death statistics as we pain patients do with opioid overdoses: both flu deaths and opioid overdose deaths are categorized and counted is such a way that the results show the desired “epidemic”.

Far from being impartial, this once venerable agency that was founded on pure and objective science is now tainted by personal “beliefs” and money, “massaging” their death certificate data to achieve ulterior objectives.   Continue reading

Poor statistical reporting persists

Poor statistical reporting persists despite editorial advice – Motor Impairment – September 27, 2018 by Joanna Diong

This ariticle piqued  my interest and started me on a search for more information about the corruption of “scientific evidence” that arises from biased studies.

Scientific discoveries must be reported accurately. If not, the general public will lose trust and question why their tax dollars are being wasted.

Unfortunately, the quality of research reports in the biomedical sciences is generally poor.

Basic statistical reporting is inadequate, and spin – the distorted, self-serving interpretation of results – is common Continue reading

3 Reasons To Be Wary Of Meta-Analyses

on 3 Reasons To Be Wary Of Meta-Analyses | American Council on Science and Health – By Stan Young — January 26, 2016

…relevant to the increasing use of statistics in science and health issues, statistician Stephen John Senn said that …data are often tortured until they confess to exactly what a scholar wants the numbers to say.

In a meta-analysis,

  1. the scientific literature is searched,
  2. a subset of papers is selected and then
  3. a combined estimate is made.

It is essentially “conducting research about previous research.”

Thus, we face an even greater problem of “garbage in, garbage out” because the biomedical field is rife with awful reserach with poor design and methodologies.  Continue reading

Truths, lies, and statistics

Truths, lies, and statistics – free full-text article /PMC5723807/ – Oct 2017

I’ve long noticed that research on pain and opioids has become ridiculously biased to support the “opioids are evil” narrative, measuring milligrams of opioid instead of patient outcomes. (See Opioids Blamed for Side-Effects of Chronic Pain)

While there is evidence of ongoing research misconduct in all it’s forms, it is challenging to identify the actual occurrence of research misconduct, which is especially true for misconduct in clinical trials.

Research misconduct is challenging to measure and there are few studies reporting the prevalence or underlying causes of research misconduct among biomedical researchers. Continue reading

Too Much Confidence In Meta-Analysis Claims

Media Should Have Far Less Confidence In Meta-Analysis Claims Than They Do | American Council on Science and HealthBy Hank Campbell — September 20, 2018

What meta-analysis is:

It is just what it sounds like, an analysis of analyses. The first meta-analysis was in 1976 and as Gene Glass described it then, the goal was to integrate the findings of collections of analysis results from individual studies.

In other words, he wanted a way to try and compare apples to apples from different studies. He was using systematic review.

I can already see a huge problem with this because the apples are the results/endpoints of the different studies being combined. (This is reminiscent of how the CDC combined prescription medication with heroin and illicit fentanyl to acheive their alarming “opioid crisis” and totally mislead those who are trying to ease it.)  Continue reading

I’ts an Overdose Epidemic not an Opioid Epidemic

Why there’s an overdose epidemic — in two graphs – STAT – By Hawre Jalal and Donald S. Burke – September 20, 2018

Here two of the authors write more about their recent study of the “Overdose Epidemic”:

The “overdose epidemic” that so many Americans are talking about isn’t really a single epidemic. It’s actually several of them, something we began exploring when we graphed the yearly counts of overdose deaths for the last 40 years.

It turns out that, when totaled, these sub-epidemics trace a nearly perfect exponential growth curve. For four decades, overdose deaths have been growing, doubling about every eight years.   Continue reading

Population Risk Does Not Equal Individual Risk

Risk In Perspective: Population Risk Does Not Equal Individual Risk – April 4, 2018 – This series is a collaboration between neuroscientist Alison Bernstein and biologist Iida Ruishalme.

Errors in risk perception are at the core of so many issues in science communication that we think this is a critical topic to explore in detail

Population risk is not the same as individual risk

We tend to think in very small sample sizes (after all, what happens to me and my family must be most important, right?) and not in terms of populations (which is how epidemiological statistics are calculated).

However, scientists measure population risks Continue reading