Complexity and clinical care
BMJ 2001; 323 doi: https://doi.org/10.1136/bmj.323.7314.685 (Published 22 September 2001) Cite this as: BMJ 2001;323:685
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Once every few years I read an article with a
combination of clarity of vision, insight and
common-sense which makes me cheer. Thank you for
crystallising my concern that the linearity which
characterises so much thinking in health leads policy
makers, local as well as national, to miss out, fatally,
on the reality of what being a human being means.
What makes us flawed machines is also what makes
us creative and empathic. We have to exploit our
strengths not stifle them in futile attempts to eliminate
our failings.
Judith Harvey
Competing interests: No competing interests
Dear sir,
The paper by Wilson & Holt (1) raises some fundamental issues on the
inherent mathematical properties of medical data and underlines the
rational basis for a truly revolutionary approach to their analysis and
interpretation.
In the past century we have witnessed a steady increase in the quantity
and quality of collected, analysed and published medical data. This trend,
which has been particularly evident in the last 40 years, has been driven
also by the spectacular development of digital document management systems
and electronic literature databases. If we consider the body of medical
literature as evidence of the amount of medical data processed all over
the world, it is clear that the growth has been exponential.
The number of currently published medical journals is estimated to be
around 20,000 and is still increasing due also to the advent of e-
publishing. This figure is at strong discrepancy with the scenario of the
first decades of 1900 when the number of medical journals was in the order
of a few dozens, mirroring the difficulties associated with systematic
data collection and the lack of knowledge of the basic rules of clinical
epidemiology, a discipline that was founded only in the '50s. At the time,
the application of statistics to the medical field was in its infancy and
this is not surprising since many techniques were originally developed for
different fields like agriculture and only subsequently applied to the
medical setting.
In fact the most powerful and well established statistical methods were
developed in the first half of the past century when the size as well as
the understanding of figures coming from clinical observations was rather
limited and certainly negligible in comparison with today. These methods
are still widely used today to analyse medical data and are indeed
considered as standard tests by the regulatory agencies.
It is noteworthy that all these methods rely on the basic assumption that
medical variables are normally distributed and, more importantly, that
they are linear in nature .
The reasons underlying this belief are quite easy to understand: on the
one hand linear models are undoubtedly more user friendly as compared to
non-linear ones which require stronger theoretical assumptions in the pre-
analysis phase; on the other hand the limited historical exposure of
physicians to medical data has led them to assume that biological
phenomena share the linear laws that govern physical systems and that have
their grounds in Newtonian mechanics .
The issue of non-linearity of medical data has very rarely been raised in
literature. Clearly epidemiologists and statisticians devoted to the
medical field are quite happy with linear techniques, since they have been
trained from the beginning with them; physicians and other health
professionals, due to their proverbial poor mathematical competence, are
also happy, provided that statisticians and regulatory agencies do not
think differently.
However, persisting in the linear approach is not without danger: if, for
instance, for two given variables a correlation coefficient of 0.018 is
calculated under the linear hypothesis and a P-value of 0.80 is added, a
relationship between the two is ruled out. Revisiting the relationship
between these two variables through the non-linear approach could change
the situation dramatically since fuzzy and smooth interactions may
determine significant effects through a complex multifactorial interplay.
There is now the reason to ask a fundamental question: is the mathematics
used in medicine what it should be?
It is perhaps useful to remind ourselves that nowadays research and
practice in medicine, diagnosis and therapy have become formidable due to
the contribution of physics with all its complex mathematics behind .
We should start to systematically address the analyses of our non-linear
and complex systems with a different kind of approach. In my view the use
of artificial neural networks, evolutionary algorithms and other systems
of "knowledge discovery in data bases" should be supported and encouraged.
The cooperation with "bio" mathematicians keen on complex adaptive systems
should be strongly advocated in the interest of the community and of the
quality of health care delivery.
Competing interests: No competing interests
Complexity theory goes a long way to explain the behaviour of
colleagues who spend as much time as they can in management (controlling)
roles. It is also encouraging to find some authoritative support in the
opposition to the headlong rush to the "practice of medicine by numbers"
(protocols and guidelines).
I hope that by pointing a fellow GP to this article at the weekend I
have been able to reduce his disillusionment with modern general practice.
I hope, too, it will help me to remain a little longer in a job I love but
which is increasingly made difficult by those who least understand it.
Competing interests: No competing interests
Complexity, Nitric Oxide and Chronic Fatigue
While it is important to hear Prof. Ian Reid’s caution (BMJ Letters,
19th January 2002) about misusing the language of complexity as metaphor
without mathematical modelling, I hope the rather dismissive style of his
letter will not hinder the way we develop theories of disease, nor of ‘un-
learning’ as a form of therapy. Chronic Fatigue Syndrome (CFS) provides a
useful illustration. The Chief Medical Officer’s Report of January 2002
recognised CFS to be a genuine condition. But what sort of genuine
condition could it be? This case example from primary care illustrates an
interesting new disease paradigm.
A 42 year old family man, social class 1employed, had experienced
this syndrome for two years. His condition had started following a viral
chest infection that put him off work three months after his father had
died. He continued to experience tiredness, muscle aches and episodes of
profound weakness that suddenly and unexpectedly forced him to lie down.
When he became anxious about the unpredictable amount of time he needed
off work, I offered a trial of a beta-blocker because he was also getting
episodes of tachycardia. Nebivolol had recently come onto the market, and
he agreed to try this. It unfortunately made his symptoms acutely and
profoundly worse. He recovered over a week or two sufficiently to return
to work, but sadly the condition deteriorated with a fluctuating course
again.
Nebivolol is marketed as a highly cardio-selective beta-blocker that
also produces vaso-dilatation via nitric oxide modulation. The role of
nitric oxide as an intra-endothelial mediator of rapid vasodilatation has
been extensively researched. Massive release is associated with
cardiogenic shock. Its mode of action on small vessels, including those of
muscles and the brain, takes effect over about two seconds. This is about
the time it takes for an episode of profound weakness to affect a sufferer
of CFS. Pall and Satterlee have recently presented evidence suggesting
elevated nitric oxide as a possible mechanism for the fatigue of CFS. The
CSM has on record twelve adverse reaction reports of fatigue on nebivolol,
by far the largest single side-effect to be reported, and proportionally
much higher than is reported for labetolol, another cardio-selective beta-
blocker.
But this is not a simple issue reducible to biochemistry. The new
disease paradigm in question is a complex adaptive systems that includes
whole people experiencing loss emotions within networks of relationships.
The science of psychoneuroimmunology (PNI) is detailing how emotional
states affect the immune system through the hypothalamic-pituitary-adrenal
system. The theory proposed by Hyland , for example, is that co-incidental
timing of events within such a system can generate maladaptive emergent
properties, an ‘extended network learning error’. It has been known since
1977 that lymphocyte function is depressed after bereavement, and fatigue
is a common ‘psychological’ feature of bereavement. Reduced killer cell
activation detectable in CFS is also mediated by increased nitric oxide.
Sufferers of CFS vigorously reject the suggestion that ‘depression’
(identified by questionnaires designed to diagnose it) is a predisposing
factor. Perhaps bereavement, or even ‘unrecognised grieving’ may be the
confounding, timely, dynamically significant, and much less stigmatising,
psycho-social feature of the physical, and therefore (sic) genuine,
condition of CFS.
Hyland’s ‘extended network learning error’ model for CFS is one
possibility that allows the complex interplay of social attachments,
emotional states, and hypothalamic hormonal or mediator chemistry to
produce a pattern of emergent conditions. His model predicts just the
response my patient had - deterioration, improvement and then slow
deterioration again - to the challenge of an iatrogenic chemical
interference. But, in response to Prof. Reid, at the ‘whole human’ level
word ‘interference’ is important to making, and un-learning, errors.
Therefore metaphors must have their place alongside statistics in this new
paradigm of genuine illness.
1. Pall ML, Satterlee JD. Elevated nitric oxide/peroxynitrite
mechanism for the common aetiology of multiple chemical sensitivity,
chronic fatigue syndrome and post-traumatic stress disorder. Annals of the
New York Academy of Sciences 2001; 933: 323-329.
2. Hyland M. Extended Network Learning Error: A new way of
conceptualising chronic fatigue syndrome. Psychology and Health 2001; 16:
273-287.
3. Bartrop RW, Lazarus L, et al. Depressed lymphocyte function after
bereavement. Lancet 1977; 1: 834-836.
4. Ogawa M, Nishiura T, et al. Decreased nitric oxide-mediated
natural killer cell activation in chronic fatigue syndrome. European
Journal of Clinical Investigation 1998; 28(11): 937-943.
5. Griffiths TN. Lost and Then Found: Turniong life’s disappointments
into hidden treasures. Carlisle: Paternoster, 1999.
Editorial note
The patient whose case is described has given his signed informed consent to publication.
Competing interests: No competing interests