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Table of Contents
GUEST EDITORIAL
Year : 2022  |  Volume : 10  |  Issue : 4  |  Page : 219-220

Scientific predictors of disease outcomes: No crystal balls or parrots picking cards


Department of Internal Medicine and Pulmonology, Narayana Hrudayalaya, Bengaluru, Karnataka, India

Date of Submission19-Sep-2022
Date of Acceptance20-Sep-2022
Date of Web Publication25-Oct-2022

Correspondence Address:
Dr. B V Murali Mohan
Department of Internal Medicine and Pulmonology, Narayana Hrudayalaya, No. 258/a, Hosur Road, Bommasandra Industrial Area, Bengaluru - 560 099, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ajim.ajim_121_22

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How to cite this article:
Murali Mohan B V, Hibare KR. Scientific predictors of disease outcomes: No crystal balls or parrots picking cards. APIK J Int Med 2022;10:219-20

How to cite this URL:
Murali Mohan B V, Hibare KR. Scientific predictors of disease outcomes: No crystal balls or parrots picking cards. APIK J Int Med [serial online] 2022 [cited 2022 Dec 3];10:219-20. Available from: https://www.ajim.in/text.asp?2022/10/4/219/359445



Chronic obstructive pulmonary disease (COPD) is now recognized to be an important cause of morbidity and mortality, the world over. According to the Global Burden of Disease Study, COPD ranks 3rd in the world on the list of causes of deaths and Disability-Adjusted Life Years (DALYs).[1] A subanalysis of the same data for India shows that it is the second most important cause of deaths and DALYs in India, and we are also set to overtake China, the unfortunate current leader in these rankings.[2]

Periodic acute exacerbations that may punctuate the course of COPD are also periods when the disease thrusts its most heavy burden on the patient, his caregivers, and the health-care system. An acute exacerbation of COPD (AECOPD), may be defined briefly as “an acute worsening of respiratory symptoms that results in additional therapy.”[3] In-hospital mortality rates for acute exacerbations of COPD vary between 2.5% and 14%, and even higher.[4] Severe acute exacerbations are often associated with respiratory failure. An important subgroup of AECOPD is that of acute hypercapnic (or Type 2) respiratory failure, defined by hypoxia with hypercapnia. As impaired ventilation – ventilatory failure – underlies Type 2 respiratory failure, logically ventilatory support is needed. This used to be offered only by invasive mechanical ventilation (IMV), a modality that is expensive, extremely uncomfortable, associated with a high complication rate, prolonged intensive care unit (ICU), and hospital stay, and with difficulties in weaning the patient from the ventilator.

Over the past three decades, noninvasive ventilation (NIV) has established itself as an extremely useful modality to improve outcomes in acute hypercapnic respiratory failure, and avoid IMV, with corresponding reductions in costs, complications, and ICU stay.[5] While the benefits of NIV are undisputed, delays in switching from NIV to IMV are often associated with increased mortality. The indications and contraindications for NIV in AECOPD seem to be well established. What is less well established, and yet extremely important, is the ability to predict those who will respond to and those who will fail NIV.

Dr. Roopa Suresh et al. in this issue of the journal present their experience of NIV in 67 consecutive cases of acute hypercapnic respiratory failure in COPD. They have followed NIV guidelines and show good outcomes in clinical and oxygenation parameters within 24 h. However, seven patients failed the NIV trial within 24 h and of these, 5 (7.4%) died. Looked at slightly differently, five died of the seven who failed the NIV trial, i.e. a 71.4% mortality. This is not different from international standards as mentioned earlier. However, this has always been a worrying statistic and raises the question – Is it possible to predict those who will fail NIV before NIV is attempted and valuable time is lost?

There have been various predictive scores of outcomes of AECOPD – Dyspnea, Esinopenia, Consolidation, Acidemia, and Atrial Fibrillation (DECAF) score, BAP score, CAPS Score, and adaptations of the CURB-65 and Acute Physiology and Chronic Health Evaluation 2 scores – but these have not been specifically used to predict NIV failure or success. A recently published score that does attempt to predict NIV outcomes is the Noninvasive Ventilation Outcomes (NIVO) score from the team that derived the DECAF score. It appears to have a good predictive ability with an area under the receiver operating characteristic curve (AUROC) of 0.79. The NIVO score uses six variables (extended Medical Research Council Dyspnoea score 1–4/5a/5b, time from admission to acidemia >12 h, pH <7.25, presence of atrial fibrillation, Glasgow Coma Scale ≤14, and chest radiograph consolidation) all easily derived, and that will be available soon after arrival at an ER/casualty that can offer both NIV and IMV.[6] Another score is the (HACOR score consisted of Heart rate (beats/minute), acidosis (assessed by pH), consciousness (assessed by Glasgow coma score), oxygenation, and respiratory rate). score which also performed well with an AUROC of 0.71. However, the HACOR score uses a PaO2/FiO2 ratio as an index of oxygenation, something that is more difficult to assess accurately in the person receiving oxygen by mask or NIV.[7]

The well-conducted study of Roopa Suresh et al. shows that NIV used correctly as per guidelines, as they have done, carries good outcomes in the majority of patients with AECOPD. Failure to improve arterial blood gases at 4 h is a strong indication to switch from NIV to IMV. Most importantly, it should be emphasized that NIV should not be used in a “fit-and-forget” mode but monitoring of clinical, oxygenation, and hemodynamic parameters should be as careful and initially frequent as during IMV. Improved prediction of outcomes of NIV may help to identify those who need more frequent monitoring.

We would strongly recommend the routine use of predictive scores such as NIVO or HACOR. At the same time, we would strongly recommend further research into this important area, both in trying to validate these scores in our settings and/or developing our own scores.

In the same issue, Prof. B S Nagaraja and Dr. Anindita Menon et al. have studied the predictive value of the DECAF and BAP scores referred to above, in predicting outcomes of AECOPD. This well-conducted study suggests that the DECAF score is a good tool to use with a high predictive value for the prognosis of outcomes of acute exacerbations, including morbidity and mortality. The BAP score performed significantly less well but has the significant advantage of being based on just four parameters, and a single-laboratory parameter blood urea nitrogen. The others, based on altered mental status, pulse rate, and age are easy to calculate even in theEmergency Room (ER). By comparison, the DECAF is slightly more complicated, needing as it does in addition to dyspnea, eosinophil counts, a chest X-ray for evidence of consolidation, arterial blood gas values, and an electrocardiogram (past or present) for evidence of atrial fibrillation. Often, in the ER, there is a trade-off between simpler scores and a decrease in predictive values and accuracy, on the one hand, compared to a more complicated score which relies on multiple parameters, is more difficult to obtain and delays decision-making. This study supports the DECAF score and is perhaps only limited by the small numbers. It also looks at the overall prognosis and unlike the NIVO and HACOR scores does not address the likelihood of NIV success or failure. It would also have been helpful if the authors had clearly stated how many patients were transferred from NIV to IMV and after what period of NIV trial, or whether they were intubated and ventilated from the beginning.

It is heartening to see two studies that try to bring scientific rigor to the often difficult area of predicting outcomes of an unstable condition like AECOPD. We look forward to more and larger studies in the same area.



 
  References Top

1.
GBD 2015 LRI Collaborators. Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory tract infections in 195 countries: A systematic analysis for the global burden of disease study 2015. Lancet Infect Dis 2017;17:1133-61.  Back to cited text no. 1
    
2.
India State-Level Disease Burden Initiative CRD Collaborators. The burden of chronic respiratory diseases and their heterogeneity across the states of India: The global burden of disease study 1990-2016. Lancet Glob Health 2018;6:e1363-74.  Back to cited text no. 2
    
3.
Global Initiative for Chronic Obstructive Lung Disease. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease. 2022. Available From: https://goldcopd.org/2022-gold-reports-2/. [Last accessed on 2022 Sep 16].  Back to cited text no. 3
    
4.
Hoogendoorn M, Hoogenveen RT, Rutten-van Mölken MP, Vestbo J, Feenstra TL. Case fatality of COPD exacerbations: A meta-analysis and statistical modelling approach. Eur Respir J 2011;37:508-15.  Back to cited text no. 4
    
5.
Brochard L, Mancebo J, Wysocki M, Lofaso F, Conti G, Rauss A, et al. Noninvasive ventilation for acute exacerbations of chronic obstructive pulmonary disease. N Engl J Med 1995;333:817-22.  Back to cited text no. 5
    
6.
Hartley T, Lane ND, Steer J, Elliott MW, Sovani MP, Curtis HJ, et al. The noninvasive ventilation outcomes (NIVO) score: Prediction of in-hospital mortality in exacerbations of COPD requiring assisted ventilation. Eur Respir J 2021;58:1-10.  Back to cited text no. 6
    
7.
Duan J, Wang S, Liu P, Han X, Tian Y, Gao F, et al. Early prediction of noninvasive ventilation failure in COPD patients: Derivation, internal validation, and external validation of a simple risk score. Ann Intensive Care 2019;9:108.  Back to cited text no. 7
    




 

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