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How might we further detail the identity of frailty?

The current future direction, and indeed past, of “frailty”, for both service provision and research at least, are both intimately linked with the angle of perspective you decide to choose.

“Anekāntavāda” (Sanskrit: अनेकान्तवाद, “many-sidedness”) refers to the Jain doctrine about metaphysical truths that emerged in ancient India; it states that the ‘ultimate truth and reality’ is complex, has multiple aspects (

The Jain texts explain the anekāntvāda concept using the parable of blind men and elephant, in a manner similar to those found in both Buddhist and Hindu texts about limits of perception and the importance of complete context.

A famous parable has several Indian variations, but broadly goes as follows:

A group of blind men heard that a strange animal, called an elephant, had been brought to the town, but none of them were aware of its shape and form. They then tried to deduce its form from some preliminary investigations. In the case of the first person, whose hand landed on the trunk, said “This being is like a thick snake”. For another one whose hand reached its ear, it seemed like a kind of fan. As for another person, whose hand was upon its leg, said, the elephant is a pillar like a tree-trunk. The blind man who placed his hand upon its side said, “elephant is a wall”….”

The ‘ultimate truth and reality’ in frailty are sometimes difficult to see, when processes, procedures and policies appear to be so dominant in the discourse.

Part of the drive to wanting to ‘do something’ about frailty, as for dementia, is that there appears to be so much to stake in terms of exposure to risk of increased morbidity and mortality. As for dementia, the rationale has been to hope to intervene in a more timely way, with more accurate timely diagnoses. Frailty could learn lessons here from other fields such as dementia.

Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity, and knowledge storage. AI techniques have been applied, for example, in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enable cost-effectiveness, and reduce readmission and mortality rates.

Precision medicine is a new paradigm that combines diagnostic, imaging, and analytical tools to produce accurate diagnoses and therapeutic interventions tailored to the individual patient. This approach stands in contrast to the traditional “one size fits all” concept, according to which researchers develop disease treatments and preventions for an “average” patient without considering individual differences.

If frailty is viewed as a number of different symptom clusters, involving heterogeneity, a ‘swiss army knife’ approach to managing frailty might, in fact, reap dividends.  The “one size fits all” concept has led to many ineffective or inappropriate approaches across health and social care, especially for disease such as dementia and cancer, where comorbidity is the norm rather than the exception.

Psychiatric diseases are very heterogeneous both in clinical manifestation and aetiology, and many care of the elderly conditions are heterogeneous likewise. With the growing interest in personalised medicine, it becomes even more important not only to classify or diagnose someone as a patient with a certain disorder, its treatment needs a more precise definition of the underlying biology, since different biological origins of the same disease may require (very) different treatments.

There are different lines of thinking about what frailty is, and a broad consensus has indeed emerged. Frailty might, nonetheless, benefit from a more sophisticated approach to its identification, which takes on board how the person who is frail is just part of a wider ecosystem which brings with it its own factors encouraging vulnerability or resilience. The recent alternative interpretation (a “network approach”) is gaining some support. It suggests that a stressor causes symptoms that activate other symptoms, in a circular, self-reinforcing way.

This theory moves away from disorders being traditionally conceptualised as categorical or dimensional models. For example, while the clinical specialism of psychiatry has shifted its focus to a more biological approach, social factors still have an important role in crosscultural diagnosis, psychiatric disorders relating to social deprivation, rehabilitation and enabling social inclusion. The degree to which society is willing to accept people with various issues and problems has an obvious impact on their quality of life. An alternative representation of the long-term course of Crohn’s disease complications has introduced the notion of the “rolling phenotype”.

As is commonly observed in clinical practice, this definition allows progression to a more severe phenotype (stricturing, penetrating) but also, regression to a less severe behaviour (inflammatory, or remission) over time.  This might be especially fruitful in models of frailty, where a unilateral accumulation of deficits is often left unchallenged, despite various research and service improvement iniatives to provide effective ‘interventions’ for frailty.

Schizophrenia and dementia as complex syndromes are well recognised. Taking schizophrenia, similar to positive and negative symptoms, the three ’syndromes’ or clusters of symptoms appear to represent independent or semi-independent dimensions of psychopathology that frequently coexist in individuals with schizophrenia. Mental health is not the only place where clusters of symptoms occur. Physical symptoms are likely to occur in clusters that may be associated with adverse outcome in patients with heart failure (HF).

Despite the importance of early recognition of worsening symptoms in HF management, the impact of physical symptoms on adverse outcome has been relatively under-explored in the context of symptom clusters. For example, the “weary and the dyspneic” symptom clusters predicted cardiac rehospitalisation and cardiac mortality, respectively. Patient education for self-monitoring of symptoms should focus on symptom clusters rather than single symptom. Targeting management to the right people, the idea behind realistic medicine, is not a new idea. It has been called various things elsewhere, such as “Choosing Wisely” in the United States and “Slow Medicine” in Italy. They all grow from the same root—reduce unnecessary treatment, address unacceptable variation, and deliver more appropriate, personalised care.


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