Yale University EliScholar – A Digital Platform for Scholarly Publishing at Yale Yale Medicine Thesis Digital Library School of Medicine January 2019 Searching For Phenotypes Of Sepsis: An Application Of Machine Learning To Electronic Health Records Michael Jarvis Boyle Follow this and additional works at: https://elischolar.edu/ymtdl Recommended Citation Boyle, Michael Jarvis, "Searching For Phenotypes Of Sepsis: An Application Of Machine Learning To Electronic Health Records" (2019). Yale Medicine Thesis Digital Library.edu/ymtdl/3477 This Open Access Thesis is brought to you for free and open access by the School of Medicine at EliScholar – A Digital Platform for Scholarly Publishing at Yale. It has been accepted for inclusion in Yale Medicine Thesis Digital Library by an authorized administrator of EliScholar – A Digital Platform for Scholarly Publishing at Yale. For more information, please contact elischolar@yale.
Searching for Phenotypes of Sepsis: An Application of Machine Learning to Electronic Health Records A Thesis Submitted to the Yale University School of Medicine In Partial Fulfillment of the Requirements for the Degree of Doctor of Medicine by Michael Jarvis Boyle 2019 SEARCHING FOR PHENOTYPES OF SEPSIS: AN APPLICATION OF MACHINE LEARNING TO ELECTRONIC HEALTH RECORDS. Boyle (Sponsored by R. Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT. Sepsis has historically been categorized into discrete subsets based on expert consensus-driven definitions, but there is evidence to suggest it would be better described as a continuum.
The goal of this study was to perform an exhaustive search for distinct phenotypes of sepsis using various unsupervised machine learning techniques applied to the electronic health record (EHR) data of 41,843 Yale New Haven Health System emergency department patients with infection between 2013 and 2016. Specifically, the aims were to develop an autoencoder to reduce the high-dimensional EHR data to a latent representation amenable to clustering, and then to search for and assess the quality of clusters within that representation using various clustering methods (partitional, hierarchical, and density-based) and standard evaluation metrics. Autoencoder training was performed by minimizing the mean squared error of the reconstruction. With this exhaustive search, no convincing consistent clusters were found.
Various clustering patterns were produced by the different methods but all had poor quality metrics, while evaluation metrics meant to find the ideal number of clusters did not agree on a consistent number but seemed to suggest fewer than two clusters. Inspection of one promising arrangement with eight clusters did not reveal a statistically significant difference in admission rate. While it is impossible to prove a negative, these results suggest there are not distinct phenotypic clusters of sepsis. 2 Acknowledgements I am indebted to my thesis advisor, Dr.
Andrew Taylor, for his constant support and insight, and to my friends and colleagues for their willingness to discuss these ideas and serve as valuable sounding boards. This work was made possible through the generous support of the Yale Summer Research Grant. None of this would be possible, however, without the love and support of my wife, Shirin Jamshidian. This work is dedicated to her.
3 INTRODUCTION 6 Sepsis Definitions 6 Machine Learning and Electronic Health Records 12 AIMS 15 METHODS 16 Study Design 16 Study Setting and Population 16 Study Protocol 17 Data Set Creation 19 Imputation 26 Autoencoder Training 26 Clustering 30 RESULTS AND DISCUSSION 31 Quality of dimensionality reduction and latent representation 31 Clustering 32 Assessing clustering propensity 32 Assessing ideal number of clusters 33 Partitional Methods 35 K-means 35 K-medoids 38 4 Hierarchical Methods 39 Agglomerative clustering with ward linkage 39 Agglomerative clustering with single and complete linkage 41 Density-Based Methods 41 DBSCAN 41 Making Sense of the Clustering 43 Limitations and Advantages 46 CONCLUSIONS 48 REFERENCES 51 APPENDIX 55 5 Introduction Sepsis, defined as “life-threatening organ dysfunction caused by a dysregulated host response to infection” (1), affects an estimated 30 million people worldwide every year, potentially resulting in 5.3 million deaths annually (2). In one 2017 study of 409 hospitals encompassing 10% (2,901,019) of all hospital admissions in the United States, the incidence of sepsis was 6.0% with a mortality rate of 15% (3). Another study of two large cohorts including nearly 7 million adult hospitalizations in the United States between 2010 and 2012 found that sepsis contributed to between 34.9% of all inpatient deaths (4). According the Agency for Healthcare Research and Quality, in 2013 sepsis was the most costly condition in the United States, responsible for 23.6 billion dollars of healthcare expenditure that year alone.
That expense amounts to 6.2% of national hospital costs resulting from nearly 1.3 million hospital stays (5). These staggering statistics are why in 2017 the WHA, the decision-making body of the WHO, adopted a resolution declaring the importance of improving diagnosis and management of sepsis (6), and why in 2018 there were more than 2,300 publications mentioning sepsis in the title when searched via PubMed. Sepsis Definitions Despite the interest in and impact of sepsis, it remains poorly understood. Its etiology is likely multifactorial, dependent upon both host and pathogenic factors, pro- and anti- inflammatory mediators, and the coagulation and neuroendocrine systems (7).
But lacking a precise understanding of its pathophysiological mechanism, the task of 6 defining the syndrome has been left to expert-led consensus groups which have reviewed and revised their recommendations three times since 1991 with no shortage of controversy (1, 8-11). While terms like “sepsis syndrome” were proposed earlier by researchers like Bone et al. in a 1989 trial of methylprednisolone for sepsis (12), the first consensus-based sepsis definitions were proposed at the 1991 American College of Chest Physicians/Society of Critical Care Medicine Sepsis Definitions Conference and published in 1992 (13, 14). Those definitions differentiated between infection, the invasion of host tissue by microorganisms, from sepsis, defined as the systemic host response to that infection as identified by having greater than one of the Systemic Inflammatory Response (SIRS) criteria (8).
The SIRS criteria, which had been previously defined and which even then were acknowledged as not specific to sepsis, were composed of: 1) a temperature greater than 38°C or less than 36°C; 2) tachycardia greater than 90 beats per minute; 3) tachypnea greater than 20 breaths per minute or a PaCO2 of less than 32 mm Hg; and 4) a white blood cell count greater than 12,000/mm3 or less than 4,000/mm3, or the presence of more than 10 percent immature neutrophils. The experts proposed the term “severe sepsis” to define the pathological condition where the adaptive response known as sepsis became maladaptive by causing organ dysfunction, hypoperfusion (lactic acidosis, oliguria, or acutely altered mental status), or sepsis-induced hypotension. They further defined “septic shock” as a more extreme subset of “severe sepsis” where the maladaptive response produced fluid-unresponsive hypotension or tissue hypoperfusion. Although the consensus group explicitly acknowledged that 7 “sepsis and its sequelae represent a continuum of clinical and pathophysiologic severity”, they also defined transition points between these states which were subsequently used for nearly two decades to guide patient care and recruitment into clinical trials.
Infection was differentiated from sepsis by two or more SIRS criteria; the adaptive host response (sepsis) became maladaptive (severe sepsis) with the presence of organ dysfunction, hypoperfusion, or hypotension; and fluid unresponsive hypotension marked the transition point between severe sepsis and septic shock. The 1992 definitions were criticized almost immediately. The use of the SIRS criteria was criticized for its rigid cutoffs that narrowly excluded potentially septic patients from clinical trials, its lack of specificity for sepsis and the consequent heterogeneity of the patients it captured (68% of one study group including ICU and general wards patients met SIRS criteria), its uselessness for guiding clinical care, and its superficial relationship with underlying pathophysiology (10, 15). In response to these criticisms, in 2001 a second sepsis definitions conference was held.
However, citing a lack of new evidence, the expert consensus group merely reaffirmed the 1991 definitions with the additional acknowledgement that more clinical and laboratory variables could be used to identify systemic illness than just the four SIRS criteria. They did not provide specific guidance about how to use these additional variables to make the diagnosis (9). Over the subsequent decade, the same criticisms of the definitions persisted and new studies clarified existing shortcomings. More researchers pointed out the need for 8 objective principles and biomarkers (16), while others suggested that organ dysfunction become part of the criteria for sepsis to prevent confusion between the terms sepsis and severe sepsis (17).
Significantly, in 2015 Kaukonen et al. showed that among more than 100,000 ICU patients with infection and organ failure, one in eight did not meet SIRS criteria and mortality increased in a linear stepwise fashion with each additional SIRS criterion. There was no transitional increase in mortality at the threshold of two SIRS criteria, challenging “the sensitivity, face validity, and construct validity of the rule regarding two or more SIRS criteria in diagnosing or defining severe sepsis in patients in the ICU” (18). Finally, in 2016 a group of critical care specialists met once more to develop the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).
The task force determined that limitations of previous definitions included “excessive focus on inflammation, the misleading model that sepsis follows a continuum through severe sepsis to shock, and inadequate specificity and sensitivity of the systemic inflammatory response syndrome (SIRS) criteria” (1). They created the current definition for sepsis, “life-threatening organ dysfunction caused by a dysregulated host response to infection,” and operationalized this definition as the increase of two or more points in the ICU-centric Sequential Organ Failure Assessment (SOFA) score. Severe sepsis was discarded as a redundant term, and septic shock was defined as a higher-mortality subset of sepsis in requiring vasopressors to maintain a mean arterial pressure of 65 mm Hg or greater and a serum lactate level greater than 2 mmol/L (>18 mg/dL) in the absence of hypovolemia. The consensus article and two accompanying analyses 9 determined the in-hospital mortality rates of these new definitions to be greater than 10% for sepsis and greater than 40% for septic shock (19, 20).
The group also published a new scoring system, the quick Sequential Organ Failure Assessment (qSOFA) score, meant to be used to identify patients with a mortality equivalent to that of sepsis outside the ICU setting. While the most recent criteria were analyzed with data in the papers that accompanied their release, they were still expert consensus-based and not derived a priori from an understanding of the pathophysiology (21). The group did not delineate distinct phenotypes of patients within the heterogeneous group captured by the non-specific organ dysfunction criteria. Moreover, they retained a categorical distinction between normal physiology, sepsis, and septic shock with discrete laboratory and clinical cutoffs.
This categorical approach has been criticized as far back as the early literature prior to the release of the first sepsis definitions. In their 1992 critique of Bone et al.’s proposed “sepsis syndrome” definition, Knaus and colleagues wrote of their own analysis: “these findings led us to our major conclusion that while categoric definitions of sepsis may be useful in selecting patients for entry into clinical trials, they may not be useful in characterizing individual, or perhaps even group, risks. What our results suggest rather is that the current clinical condition of sepsis, at least as it is applied to a subset of critically ill patients admitted to ICUs, is a continuous state with the prognosis determined, in large part, by the degree of physiologic imbalance at the time of admission” (22). 10 This debate over definitions has significant real-world implications for patients because definitions can drive management.
One of the major turning points in the management of sepsis was the 2001 trial of early goal-directed therapy (EGDT) for severe sepsis and septic shock, frequently referred to as the Rivers trial after its first author (23). The trial showed that when severe sepsis or septic shock were managed with specific goals for central venous oxygen saturation and pressure, hematocrit, and mean arterial pressure, mortality dropped from 46% to 30% compared to standard of care.