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Variability in Physician Estimates of Survival for Acute Respiratory Failure in Chronic Obstructive Pulmonary Disease
Variability in Physician Estimates of Survival for Acute Respiratory Failure in Chronic Obstructive Pulmonary Disease Robert A Pearlman, M.D., M.P.H. * Physician estimates of patient survival often influence clinical decisions. I studied physician estimates of survival for a patient with acute respiratory failure and underlying chronic obstructive pulmonary disease to identify the factors that may influence these estimates. Physicians (n 205) completed the same patient management problem and estimated the length of survival for the hypothetical patient. ,hysician estimates of survival were quite variable, ranging frOm one month to 6ve years.' Shorter estimates of survival associated ~th acquisition of select case mformation,
1)subjective information from family members and a profes-
of survival are particularly important E stimates treatment considerations in medical and surgical
chose to allow the patient to die (n = 86) expected the patient to live an average of six months, whereas those who opted for intubation (n = ~9) expected the patient to live an average of 15 months, In addition, approximately 16 percent of the physicians volunteered that the patient's expected survival prognosis (if treated) influenced their decision. For patients with chronic obstructive pulmonary disease (COPD), data in the medical literature describe prognosis. Hospital mortality associated with acute respiratory failure reportedly ranges from 6 percent to 37 percent, J.5.20 and the natural history of survival is influenced by pulmonary function (FEVb PaCO 2, N2 washout),":" cor pulmonale,18.21.22.28 and functional disability.15.I8.19 In addition, the literature addresses the poor prognosis associated with baseline radiographic evidence of chronic obstructive pulmonary disease, and required mechanical ventilation for respiratory failure. 19 ,25.30-33 However, uncertainty regarding prognosis in COPD remains and a paucity of data exists regarding the determinants of physician prognostications of survival for these patients. As such, I studied physician estimates of survival using' the aforementioned patient management problem depicting acute respiratory failure in an elderly, debilitated patient with underlying chronic obstructive pulmonary disease. The objectives of this study were to address four questions concerning survival prognostication in this case:
=
were
decisions, especially those near the end of life.l~ The effectiveness of proposed interventions often are evaluated in terms of their expected influence on surFor editorial comment, see page 475
vival. 6.7 In addition, clinical decisions frequently reflect trade-offs between morbidity and length of survival.t" As a result, accurate estimates of survival can be extremely useful in clinical decisions. Other considerations that may influence clinical decisions include the patient's age,lo-1.2 socioeconomic class.P" functional status.v" unique clinical characteristics {bedridden, diagnosis of cancel; receiving pain medications)," and "social salvageability. ''11 Physician characteristics and values also may effect medical management. Examples include the physicians practice setting.v'' level of training, 3 and perception of the patients quality of life. 14 It is unknown whether these factors influence physicians' estimates of survival. As discussed in an earlier paper, physician estimates of survival for a hypothetical patient with chronic obstructive pulmonary disease were related to a specific treatment decision (intubation vs allowing to die) in a patient management problem. 3 Physicians who
*Assistant Professor of Medicine and Health Services, University of
Washington Schools of Medicine and Public Health, and Veterans Administration Medical Center, Seattle. Former VA Fellow in the Robert Wood Johnson Clinical Scholars Program when data were collected. The opinions expressed herein reflect those of the author and are not necessarily those of the Robert WoodJohnson Foundation or the Veterans Administration. This project was supported in part by the Veterans Administration Northwest Health Services Research and Development Field Program and Geriatric Research Education and Clinical Center, and the Robert Wood Tohnson Foundation. Manuscript received August 20; revision accefted October 14. Reprint requests: Dr. Pearlman, VA Medica Center, 1660 South Columbian Way, Seattle 98108
sional colleague, and 2) physiologic and functional data previously demonstrated to be predictive of survival. The study suggests that estimates of survival for the same patient may vary among physicians because of different considerations of social and physiologic case information. Physician estimates of patient survival and treatment recommendations may become more uniform with additional education or decision aids regarding the propostication of survival.
1. Are there systematic differences in estimates of survival on the basis of physician experience, specialty, subspecialty, and site of practice? 2. What association exists between physiologic and social information about a patient and physicians' estimates of his survival? 3. Is consideration of predictors of prognosis (FEV 1.l evidence of COPD by chest radiograph, PaCO t , and functional level) associated with a narrower range of physician estimates of survival? 4. How well do physician estimates of survival correspond to those derived from the literature? CHEST I 91 I 4 I APRIL. 1987
515
METHODS
I presented a patient-management problem modeled after the ABIM certiflcation examination questions to a group of physicians. They were requested to select a limited amount of available case information, indicate a treatment preference (intubation vs allowing to die), estimate the patients survival time if treated, and explain the rationale for their treatment decision. Subjects were 205 internal medicine and family medicine physicians in King County (WA). They either were affiliated with the University of Washington (as residents or faculty) or practiced in the community. University physicians had appointments in either the Department of Internal Medicine or the Department of Family Medicine and were eligible for participation on the basis of recent inpatient care responsibilities. Community physicians were randomly selected from King County. The rates of participation were 84 percent (123 of 150) for University-afIlliated physicians and 69 percent (78 of 113) for community physicians. After obtaining ~nformed consent, physicians read the following case: An elderly, married, male nursing home resident is admitted to your service with worsening shortness of breath of three days' duration. The patient has a history of chronic obstructive pulmonary disease and mild pulmonary hypertension. Six months previously he was treated with 3 Umin of oxygen, which suppressed his respiratory drive. The patient was intubated and subsequently received a tracheostomy when it took two months to' wean him from the respirator. The patient has shortness of breath at rest with an increase and change in the color of his sputum (yellow to green). He has no fever and reports compliance with his prescribed aminophylline, prednisone, and metaproterenol inhaler. Initial evaluation shows a distressed, anxious, mildly blue' man taking 30 breaths/min with diminished breath sounds, ~se rales, and expiratory wheezes in both lung fields. Expectorated sputum shows many polymorphonuclear cells and a predominance of Cram-negative pleomorphic organisms. Arterial blood gas measurements show hypoxemia, hypercarbia, and respiratory acidosis. Chest roentgenogram shows no change since his baseline roentgenogram three months ago. On the basis of these data, treatment in the emergency room is begun for the pres~mptive diagnosis of acute bronchitis caused by H aeinophilw inftuenzae with appropriate dosages of aminophylline, ampicillin, prednisone, metaproterenol inhaler, and vigorous postural drainage and percussion. 1Wo liters per minute of low-flow oxygen is given, an amount slightly less than a previously determined retention threshold. After six hours of the currently prescribed therapy, he looks more fatigued and is struggling more wi~ his breathing. . Next, physicians considered the potential availability of 25 additional items of information. The physicians were then told to imagine (as might be the case in a' real clinical situation) that they had a limited time (two hours) to gather data before they would be forced to make a final treatment decision. In the context of this casemanagement problem, the physicians were allowed to select a limited amount of case inform~on. Physicians selected eight items to acquire more data about the case, and after all items were identified, they learned the details ~m their targeted inqufries. The infOrmation was classifiable into three generic categories: physiologic, social, and professional consultations. Within the physiologic data the fOllowipg infOrmation was potentially available: age, arterial blood gas levels obtained in the emergency room on this admission, bedside measures of pulmonary function taken now, careful review of the patient's previous hospital record describing his prolonged weaning from the respirator, optpatient pulmonary function tests obtained three weeb prior to this admission, repeat artertal blood gas determinadons over the two-hour period, repeat physical examination, review of fluid balance (input/output) since
518
admission, review of repeat chest roentgenogram taken one hour ago with the radiologist, todays complete blood chemistry, differential, and serum electrolytes obtained in the emergency room, and todays morning theophylline blood level. Social information included religion; Insurance status; conversations regarding treatment options with the patient, wife, and son; conversation with wife about patients mental status; and the nursing home report. Consultative information was available from the head nurse of the intensive care unit, chiefmedical resident, "aggressive" and "nonaggressive" colleagues, pulmonary specialist, social worker, and textbook intubation guidelines. The details of the case information are presented in the Appendix. With additional knowledge, the physicians indicated a treatment preference between mechanical ventilation and allowing to die. They also responded to the following question: "What is the projected life expectancy of this patient, if intubated, in terms of months or years?" Nonparametric statistical analyses were used because of the skewed distribution of survival time (SPSS).34 Signfflcance values are reported in the text with the name of the test statistic. Stepwise linear regression was used to identify the independent pieces of information that best predicted survival prognoses. RESULTS
Two hundred five physicians participated in the study, including 72 resident physicians and 55 attending physicians at the University of Washington, and 78 private practitioners. Seventy-two physicians were from the family medicine discipline (18 resident physicians, 14 attending physicians, and 40 private practitioners). One hundred thirty three physicians were from the internal medicine discipline (54 resident physicians, 41 attending physicians, and 38 private practitioners). , The estimates for survival were discrepant with a skewed distribution, the tail of which extended to 60 months. In Figure 1, the distribution of survival estimates are compared between board certified pulmonologists (n = 9) and other physicians (n = 189). This shows that pulmonologists, who have the most expertise to prognosticate survival for patients with COPD and consequently represent a gold standard, provided a narrower range of survival estimates. Their median estimate of survival was five months and nearly 90 percent believed the patient would die within eight months. Comparisons of median survival estimates by physician role (resident, 6.1 months; attending, 6.2 months, private practitioner, 7.9 months), specialty (internal medicine, '6.4 months; family medicine, 6.2 months), subspecialty (pulmonologists, 5.0 months; other physicians, 6.4 months), and setting (with medical trainees, 6.2 months; without medical trainees, 8.0 months) showed no significant differences (p>.05, Kruskal Wallis ANOVA). The estimates of survival were associated with the case information that physicians-selected to help make their treatment decision. In general, physicians who selected a predominance of physiologic information estimated longer survival times for the patient (median Vart8bl1ity In Physician Estimates d Survival(Robert A. PHIIman)
50
Table I-Independent CON In.formstion Predictive cf Surviool1ime*
Percentage of Nonpulmonologists (n=189)
40
Point Biserial Median Survival Correlation Predictions (months) Coefficientt (p level) Not Selected Selected
30 20
Case Information
10 10
50
30
40
50
60
Percentage of Pulmonologists (n=9)
40
%
20
30
10 10
vival.
-.26 (.000) -.21 (.003) -.18 (.013) -.09 (.199)
11.7
.16 (.024) .19 (.009)
6.2
6.1
7.9
5.6
6.4
3.0
8.0
6.2
6.2
11.8
8.5
*Stepwise linear regression: RI = .14 t A negative correlation coefficient indicates thatselection of specific case information is associated with a shorter prediction of survival
20
FIG URE
Conversation with wife Conversation with son Conversation with patient Opinion of "nonaggressive" colleague Intubation guidelines Fluid balance status
20
30 Months
40
50
60
1. Pulmonologist and nonpulmonologist estimates of sur-
survival times: 6.5 months vs 6.0 months, p = .013, Mann-Whitney U test). In contrast, physicians who selected a predominance of social information predicted shorter survival times (median survival times: 5.9 months vs 6.4 months, p =.052, Mann-Whitney U test). Stepwise linear regression identified the independent predictors of the physicians' estimates of survival time (P< .1). Physicians who estimated shorter survival times were more likely to select information about the patient's, wife's, and son's wishes regarding treatment, and a "nonaggressive" colleague's consultative opinions. Physicians who estimated a longer survival were more likely to select information about the standard recommended guidelines for intubation, and a review of the fluid balance status since the patients admission. In aggregate, these variables accounted for 14 percent of the variance. Surprisingly, the amount of selected socialinformation was also an independent predictor of survival time, explaining 7 percent of the variance. Descriptive information about the independent predictors is presented in Table 1. The following selections of case information were significant zero order correlations (p<.05) that proved not to contribute independently to the survival prediction model: the ICU head nurse's report on the availability of a respirator and an leu bed (one respirator and one bed available), outpatient pulmonary function tests obtained three weeks prior to admission, the patient's religious preference (Protestant), pulmonary consultation, repeat arterial blood gas determinations over the two-hour period in the hospital, and a telephone conversation with the nurse from the nursing home to check on the patient's baseline level of function. Three pieces ofavailabledata were known predictors
time.
of shorter survival prognosis in COPD. These were pulmonary function test results (PaCOSh FEVJ, roentgenographic evidence of chronic obstructive pulmonary disease, and the level of functional disability.15.21-29 When more pieces of these "critical" data were chosen, physicians' estimates of survival time were shorter One hundred thirteen physicians selected only one piece of critical data. Their median estimate of survival was 6.3 months. Thirty six physicians selected any combination of two pieces of critical data. Their median estimate of survival was 5.9 months. Only four physicians selected all three pieces of critical data. Their median survival estimate was 3.0 months with a range from one to 12 months. Thirteen percent of the physicians estimated survival time to be equal to or greater than two years. These physicians were not uniquely identifiable by their role, specialty, or site of practice. Their only shared characteristic was that they selected the information about the wifes opinions regarding her husbands treatment less often than other physicians (chisquare, p<.03). DISCUSSION
Physician estimates of survival were investigated because they are inHuential factors in medical decisions that involve the elderly or individuals near the end of life, and are often based on limited empirical data. As such, this represents an area of uncertainty that may be affected by professional or social values rather than "scientific" considerations. A patient management problem describing an elderly, debilitated patient with chronic obstructive pulmonary disease and acute respiratory failure was presented to 205 physicians. Analyses were conducted to identify the factors associated with physicians' this hypothetical patient (if estimates of survival treated with mechanical ventilation). Specifically, physician characteristics (roles, specialty, practice setting)
ror
CHEST I 91 I 4 I APRIL, 1987
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and management of case information were analyzed to assess their possible influence on physicians' prognostications. . The estimates of survival for the hypothetical patient ranged from one month to five years, with approximately half the physicians estimating survival to be less than six months. In general, the estimates of survival were similar for internists and family physicians; residents, attending physicians, and private practitioners; and physicians caring for patients with or without the presence of medical trainees. Although board certified pulmonologists generally estimated the patient's survival to be less than other physicians and demonstrated the narrowest range of survival estimates, their estimates were not appreciably different from those' of physicians without formal pulmonary training. Eighty-seven percent of all physicians estimated that the patient would live less than two years. The management of case information demonstrated intriguing associations with physicians' estimates. The preferential selection of social information was associated with shorter estimates of survival. The association between acquisition of social information and survival estimates (especially opinions by patients and family members regarding treatment) suggests that physicians may solicit subjective information from these individuals because they have learned to trust its predictive value. In addition, the change may reflect an appreciation fo~ published data that suggest that patients may predict their own mortality better than physicians.P'" As such, these findings may document for the first time the use of subjective information for "hard" predictions. Alternatively, physicians may have been seeking support from the family for their 'own subjective treatment preferences. Unfortunately, a cross-sectional design causality cannot be inferred from these associations. Just as the association between social case information and shorter estimates of survival were intriguing, so was the finding that selection of more physiologic case information was associated with longer estimates of survival. Based on the literature there were three pieces of case information (pulmonary function, radiographic evidence of COPD, and physical dysfunction resulting from the pulmonary disease) that were predictors of limited survival. When physicians selected more of these data, their estimates were shorter (sixmonth survival estimates with one piece of data to three-month survival estimates with three pieces of data). Yet, when physicians selected more physiologic information in general, their estimates for the patient's survival were longer. This suggests that physiologic inquiries yielding negative results or demonstrating the absence of complications may have led to longer estimates of survival. This is not completely surprising. Physicians often have difficulty interpreting nega518
tive test results and making predictions.F:" An alternate interpretation which demonstrates the importance of avoiding the inference of causality is that physicians who focus on physiologic information are optimistic regarding the efficacy oftreatment and their survival estimates, regardless of the data. In this scenario, selection of physiologic data would only be a marker for an optimistic personality. Stepwise multiple linear regression identified independent predictors of survival. Selection of subjective information regarding treatment preferences independently predicted shorter estimates of survival. Selection of information guidelines for intubation and the patients fluid status independently predicted longer estimates of survival. In aggregate, these variables only explained 14 percent of the variance, lending support to the unpredictability of physicians' estimates of survival for an individual case depicting COPD. The natural history of severe chronic obstructive pulmonary disease (FEV1 <.75L) suggests an approxiP1~e survival rate of 50 percent at two to three years. 21-2.'5 The expected survival for a severely dysfunctional patient with COPD and an episode of acute respiratory failure requiring mechanical ventilation, much like the hypothetical patient, is worse. In this situation, hospital mortality averages approximately 45 percentts·18·19.31.33 and the six-month expected mortality runs as high as 50 to 75 percent. J:S.17.~ Many of the physicians in this study estimated the patient's survival to be in this range, especially the pulmonologists and those who selected the known predictors of mortality for COPD. However, approximately 13 percent of the physicians estimated that 'the patient would live from two to five years, The only variable associated with this group of physicians was their preferential nonselection of information from the wife regarding her opinions about treatment. This study has several limitations. First, its design is cross-sectional and causal relationships cannot be inferred. Second, it involves physicians in one region of the country where practice patterns and values may be unique. As such, the generalizability ofthe results may be limited. Third, the management of case information and physician attributes only explain a small portion of the physicians' estimates of survival. Therefore, important unmeasured and unrecognized variables may not have been considered in this study. Finally, many of the statistically significant differences in survival estimates may not be clinically significant. However, in a previous paper the physicians' selection of categories of case information was documented to be an independent predictor of treatment intentions. 3 However; the study demonstrates several important findings that deserve attention, 'First, although estimates of survival may influence major treatment decisions, such as those' involving the use of life-sustaining
procedures, these estimates vary between physicians without being well understood. Prognosis regarding survival is a legitimate factor in medical decisions and one that physicians and patients should consider. If physicians' estimates are variable, then different patients with the same problem (prognosis) may be treated differently. If physicians' estimates are inaccurate, then major decisions may occur after deliberations based on false assessments. When prognosis regarding survival is particularly uncertain, or when attempting to apply statistical probabilities to an individual case, perhaps two caveats should be remembered: 1) prognostication information should be presented to patients with qualifications, and 2) the importance given to the survival estimates should be minimized somewhat by physicians in their own deliberations. Second, physician estimates may be influenced by social information to a greater degree than by physiologic uJbrmation. This finding suggests that under conditions of uncertainty, physicians may use data that represent the art of medicine more than the science of medicine. This behavior needs to be confirmed in other situations and analyzed to ascertain whether it leads to sensitive, compassionate care. Third, empirical and physiologic data influence physician estimates of survival, but only a limited number of physicians (n = 4) selected all the available data known to be predictive of mortality. This suggests that physicians might benefit from further education or decision aids (algorithms) regarding known predictors of mortality in COPD. Additional education could narrow the range of estimates and lead to a more consistent pattern of care for this condition based on the current state-of-the-art. Finally, there is a tremendous gap in our understanding of physicians' predictions regarding survival in this clinical context. As such, it represents fertile ground for further research. ACKNOWLEDGMENTS: The author wishes to thank Drs. Daniel Kent and Thomas Martin fur their careful review of the manuscript.
REFERENCES 1 Gaensler EA, Cugell DW: Lindgren I, Verstraeten JM, Smith SS, Streider JW The role of pulmonary insufficiency in mortality and Invalidism followiilg surgery for pulmonary tuberculosis. J . Thorac Surg 1955; 29: 163-87 2 Olsen ON, Block AJ Swenson EW, Castle JR, Wynne JW Pulmonary function evaluation of the lung resection candidate: a prospective study. Am Rev Respir Dis 1975; 111:379-87 3 Pearlman RA, Inui TS, Carter WB. Variability in physician bioethical decision-making. Ann Int Med 1982; 97:420-25 4 Perkins MSt lonsen AR, Epstein wv. Providers as predictors: using outcome predictions in intensive care. Crit Care Med 1986; 14:105-10 5 Linn BS, Linn MW Estimating survival for patients with latestage cancer. South Moo J 1980; 73:838-40 6 Pauker SG, McNeil BJ. Impact of patient preferences on the selection of therapy. J Chron Dis 1981; 34:77-86
7 Chang RWS, Jacobs S, Lee B. Use of Apache II severity of disease classification to identify intensive-care-unit patients who would not benefit from total parenteral nutrition. Lancet 1986; 2:1483-87 8 McNeil BJ, Weichselbaum R, Pauker SG. Fallacy of the five-year survival in lung cancer. N Eng} J Moo 1978; 299:1397-1401 9 McNeil BJ, Weichselbaum R, Pauker SG. Uadeoffs between quality and quantity of life in laryngeal cancer. N Eng} J Moo 1981; 305:982-87 10 Sudnow D. Passing on. Englewood Cliffs, New Jersey: PrenticeHall Inc, 1967 11 Crane D, The sanctity of social life: physicians' treatment of critically ill patients. New York: Russell Sage Foundation, 1975. 12 Legall JR, Bran-Buisson C, 1hJnet ~ et al..In8uence of age, previous health status, and severity of acute illness on outcome from intensive care. Critical Care Med 1982; 10:868 13 Brown NK, Thompson DJ. Nontreatment of fever in extendedcare facilities. N Eng) J Moo 1979; 300:1246-50 14 Pearlman RA, Speer JB Jr. Quality-of-life considerations in geriatric care. Am Geriatr Soc 1983; 31:113-20 15 Jessen O. Uacheostomy and artificial ventilation in chronic lung disease. Lancet 1967; 2:9-12 16 Burk RH, George RB. Acute respiratory failure in chronic obstructive pulmonary disease. Arch Intern Med 1973; 132:865-68 17 Moser KM, Shibel EM, Beamon AJ. Acute respiratory failure in obstructive lung disease. Long-term survival after treatment in an intensive care unit. JAMA 1973; 225:705-07 18 Gottlieb LS, Balchum oj Course of chronic obstructive pulmonary disease following first onset of respiratory failure. Chest
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w
19 Sluiter JH, Blokzul EJ, Van Dul Van Haeringen JR, Hilvering C, Steenhuis EJ. Conservative and respirator treatment of acute respiratory insufficiency in patients with chronic obstructive lung disease. Am Rev Respir Dis 1972; 105:932-42 20 Martin TR, Lewis S~ Albert RK. The prognosis of patients with chronic obstructive pulmonary disease after hospitalization for acute respiratory failure. Chest 1982; 82:310-14 21 Traver GA, Cline MG, Burrows B. Predictors of mortality in chronic obstructive pulmonary disease. Am Rev Respir Dis 1979;
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22 Renzetti VD Jr, McClement JH t Litt BD. The Veterans Administration cooperative study of pulmonary function. III. Mortality in relation to respiratory function in chronic obstructive pulmonary disease. Am J Med 1966; 41:115-29 23 Burrows B, Earle RH. Course and prognosis of chronic obstructive lung disease. A prospective study of 200 patients. N Eng} J Med 1969; 280:397-404 24 Diener CF, Burrows B. Further observations on the course and prognosis of chronic obstructive lung disease. Am Rev Respir Dis
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25 Boushy SF, Thompson HK Jr, North LB, Beale AR, Snow TR. Prognosis in chronic obstructive pulmonary disease. Am Rev Respir Dis 1973; 108:1373-83 26 Beaty TH, Cohen BH, Newill CA, Menkes HA, Diamond EL, Chen CJ. Impaired pulmonary function as a risk factor for mortality. Am J Epidemioll982; 116:102-13 27 Beaty TH, Newill CA, Cohen BH, Tockman MS, Bryant SU, Spurgeon HA. Effects of pulmonary function on mortality. J Chron Dis 1985; 38:703-10 28 Sukumalchantra ~ Dinakara ~ Williams MH Jr. Prognosis ofpatients with chronic obstructive pulmonary disease after hospitalization for acute ventilatory failure: a three-year follow-up study. Chron Obstructive Pulm Dis 1965; 93:215-26 29 Knaus WAt Zimmerman JE, Wagner D~ Draper EA, Lawrence DE. APACHE-acute physiology and chronic health evaluation: a physiologically based classification system. Crit Care Med 1981;
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30 Teres 0, Brown RB, Lemeshow S. Predicting mortality of intensive care unit' patients. The importance of coma. Crit Care Med 1982; 10:86-95 31 Davis H, Lefrak SS, Miller 0, Malt S. Prolonged mechanically assisted ventilation. An analysis of outcome and charges. JAMA 1980; 243:43-45 32 Witek TJ, Schachter EN, Dean NL, Beck GJ. Mechanicallyassisted ventilation in a community hospital. Immediate outcome, hospital charges, and follow-up of patients. Arch Intern Med 1985; 145:235-39 33 McLean RF, McIntosh JD, Kung GY, Leung DMW, Byrick RJ. Outcome of respiratory intensive care for the elderly. Crit Care Med 1985;13:625-29 34 Nie NH, Hull CH, Jenkins JG, Steinbrenner K, Bent DB. Statistical package for the social sciences. New York: McGraw-Hill, Inc, 1975 35 Mossey JM, Shapiro E. Self-rated health: a predictor of mortality among the elderly. Am J Public Health 1982; 72:800-08 36 LaRue A, Bank L, Jarvik L, Hetland M. Health in old age: how do physicians' ratings and self-ratings compare? 1979; 34:687-91 37 Centor RM, Witherspoon JM, Dalton H~ Brody CE, Link K. The diagnosis of strep throat in adults in the emergency room. Med Decis Making 1981; 1:239-46 38 Christensen-Szalanski Jll, Bushyhead lB. Physicians" misunderstanding of normal findings. Med Decis Making 1983; 3:169-75 39 Politser E Decision analysis and clinical judgment. A re-evaluation. Med Decis Making 1981; 1:361-89 40 Asmundsson E Kilburn KH. Survival after acute respiratory failure. 145 patients observed 5 to 8~ years. Ann Intern Med 1974;
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APPENDIX
A. Age: 69 years old. B. Arterial blood gaslevels obtained in the emergency room on this admission: ABG (room air): Po l = 3 8 mm Hg; Pco, = 58 mm Hg; pH = 7.32, saturation percentage = 65 percent. C. Bedside measures of pulmonary function taken now: vital capacity-patient unable to cooperate, FEVl =300
O. E
Q.
ml.
D. Call to the ICU head nurse to check on the availability of a respirator and an ICU bed. There is one ICU bed and one respirator available. The nurse's response to learning who the potential patient might be was, "Not him again. Can't you treat him outside the Icur' E. Careful review of the patient's previous hospital record describing his prolonged weaning from the respirator: The weaning was not prolonged by any secondary complications. F: Case discussion with chief medical resident at the hospital: 01011' m not sure which is worse: bronchogenic lung cancer or severe chronic obstructive lung disease. Which way does the patient want to be treated?" G. Conversations With patient regarding treatment options: On admission the patient agreed to the proposed treatment plan. At the end of the first conversation he queried, UNo tube, right?" You responded with, "It doesn't seem necessary at this time." When the situation deteriorated, you returned to ask th~ patient about intubation again. However, he was somnolent and unable to answer questions meaningfully. H. Conversation with patients son about treatment: The son expressed the wish that no heroics be performed because 520
R.
of his father's suffering and current lifestyle. He also felt that his mother was suffering as a result of his father's condition. Conversation with the patient's wife about the patient's baseline mental status: OIcHe is slightly depressed and slightly forgetful. On rare occasions he can enjoy himself like the old days." Conversation with the patients wife about treatment options: CCI love him greatly and feel badly that I had to place him in a nursing home for appropriate care. I really hate seeing him suffer and hope that he'll get better:" Insurance status of patient and family: The patient and his wife qualify by virtue of their ages for Medicare. An application for acceptance to Medicaid is pending. Opinion about the case by a "non-aggressive" colleague: "The patient represents end-stage lung disease. What he really needs is a new set of lungs." Opinion about the case by an "aggressive" colleague: "The patient should maintain a tracheostomy button for possible future needs." Outpatient pulmonary function test results obtained three weeks prior to this admission: Vital capacity = 1.5 (40 percent); FEV tNC=O.22; FEF=0.17 (9 percent); residual volume = 5.4 (210 percent); TLC = 8.0 (150 percent); RVffLC =0.68; ABC (room air): P0 2 = 46 mm Hg, Pco, = 48 mm Hg, Pco, = 48 mm Hg, pH = 7.35, saturation percentage = 77 percent. Interpretation: severe COPD, chronic compensated respiratory acidosis with hypoxemia and hypercarbia. Patients religious preference: Protestant Pulmonary consultation: "The case reflects progressive respiratory acidosis in the face of maximal nonaggressive therapy. The patient will require acute mechanical assistance if he is to survive this insult. Kindly let me know if you decide to intubate and I'll follow the case with you." Recommended guidelines for intubation: Respiratory rate = 351minute; vital capacity < 15 mglkg body weight; FEVt
46 46 46 Po! 90-110 64 72 80 Peo235-45 pH 7.35-7.45 7.29 7.23 7.19 75 72 67 Saturation 97%* *Varies with age and sex S. Repeat physical examination: Two changes noted on the repeat examination: 1) respiratory rate now 40, and 2) mental status altered (somnolence). L Review of fluid balance (input/output) since admission: in balance. U. Review of repeat chest roentgenogram taken one hour ago with the radiologist: the chest roentgenogram shows chronic obstructive lung disease with no acute processes. There is no evidence of a pneumothorax. V. Social workers report on the patient and his family situation: The wife feels guilty about having placed her husband in a nursing home. Their financial savings are depleted because of the nursing home costs. The applicaYariabHity In Physician Estimates of Survival(Robert A Pearlman)
tion for welfare has been submitted. W Telephone conversation with the nurse from the patient's nursing home to check on his baseline level of function: "His activity level is restricted to walking halfway across the room, at which time his shortness of breath inhibits further activity. He uses a wheelchair part of the time. His wife visits once weekly since he was placed there three months ago."
x.
'Iodays complete blood chemistry, differential, and serum electrolytes obtained in the emergency room: normal except fur leukocyte count =12,I00/co mm with 12 percent bands, 78 percent polymorphonuclear cells, 8 percent lymphocytes, 1 percent monocytes, and 1 percent eosinophils. Y. 'Iodays morning theophylline blood level: 20 fJ.glml (therapeutic range: 10-20 fJ.glml).
20 Years of PrOgrammed Stimulation of the Heart Co-sponsored by the North American Society of Pacing and Electrophysiology, this congress,
to answer "Where to go from Here" will be held in Maastricht, The Netherlands, June 1-5. For
information, contact MECC, Congress Management B~ Posthus 630, 6200 AB Maastricht, The Netherlands.
Coronary Angiography, 1987 The Department of Radiology, Brigham and Womens Hospital and Harvard MedicalSchool, co-sponsored by the Council on Cardiovascular Radiology of the American Heart Association, will present this annual postgraduate course JUlie 15-18, at the Marriott Copley Place, Boston. For information, contact Department of Continuing Education, Brigham and Women's Hospital, Department of Radiology, 75 Francis Street, Boston 02115.
CHEST I 91 I 4 I APRIL 1887
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1)subjective information from family members and a profes-
of survival are particularly important E stimates treatment considerations in medical and surgical
chose to allow the patient to die (n = 86) expected the patient to live an average of six months, whereas those who opted for intubation (n = ~9) expected the patient to live an average of 15 months, In addition, approximately 16 percent of the physicians volunteered that the patient's expected survival prognosis (if treated) influenced their decision. For patients with chronic obstructive pulmonary disease (COPD), data in the medical literature describe prognosis. Hospital mortality associated with acute respiratory failure reportedly ranges from 6 percent to 37 percent, J.5.20 and the natural history of survival is influenced by pulmonary function (FEVb PaCO 2, N2 washout),":" cor pulmonale,18.21.22.28 and functional disability.15.I8.19 In addition, the literature addresses the poor prognosis associated with baseline radiographic evidence of chronic obstructive pulmonary disease, and required mechanical ventilation for respiratory failure. 19 ,25.30-33 However, uncertainty regarding prognosis in COPD remains and a paucity of data exists regarding the determinants of physician prognostications of survival for these patients. As such, I studied physician estimates of survival using' the aforementioned patient management problem depicting acute respiratory failure in an elderly, debilitated patient with underlying chronic obstructive pulmonary disease. The objectives of this study were to address four questions concerning survival prognostication in this case:
=
were
decisions, especially those near the end of life.l~ The effectiveness of proposed interventions often are evaluated in terms of their expected influence on surFor editorial comment, see page 475
vival. 6.7 In addition, clinical decisions frequently reflect trade-offs between morbidity and length of survival.t" As a result, accurate estimates of survival can be extremely useful in clinical decisions. Other considerations that may influence clinical decisions include the patient's age,lo-1.2 socioeconomic class.P" functional status.v" unique clinical characteristics {bedridden, diagnosis of cancel; receiving pain medications)," and "social salvageability. ''11 Physician characteristics and values also may effect medical management. Examples include the physicians practice setting.v'' level of training, 3 and perception of the patients quality of life. 14 It is unknown whether these factors influence physicians' estimates of survival. As discussed in an earlier paper, physician estimates of survival for a hypothetical patient with chronic obstructive pulmonary disease were related to a specific treatment decision (intubation vs allowing to die) in a patient management problem. 3 Physicians who
*Assistant Professor of Medicine and Health Services, University of
Washington Schools of Medicine and Public Health, and Veterans Administration Medical Center, Seattle. Former VA Fellow in the Robert Wood Johnson Clinical Scholars Program when data were collected. The opinions expressed herein reflect those of the author and are not necessarily those of the Robert WoodJohnson Foundation or the Veterans Administration. This project was supported in part by the Veterans Administration Northwest Health Services Research and Development Field Program and Geriatric Research Education and Clinical Center, and the Robert Wood Tohnson Foundation. Manuscript received August 20; revision accefted October 14. Reprint requests: Dr. Pearlman, VA Medica Center, 1660 South Columbian Way, Seattle 98108
sional colleague, and 2) physiologic and functional data previously demonstrated to be predictive of survival. The study suggests that estimates of survival for the same patient may vary among physicians because of different considerations of social and physiologic case information. Physician estimates of patient survival and treatment recommendations may become more uniform with additional education or decision aids regarding the propostication of survival.
1. Are there systematic differences in estimates of survival on the basis of physician experience, specialty, subspecialty, and site of practice? 2. What association exists between physiologic and social information about a patient and physicians' estimates of his survival? 3. Is consideration of predictors of prognosis (FEV 1.l evidence of COPD by chest radiograph, PaCO t , and functional level) associated with a narrower range of physician estimates of survival? 4. How well do physician estimates of survival correspond to those derived from the literature? CHEST I 91 I 4 I APRIL. 1987
515
METHODS
I presented a patient-management problem modeled after the ABIM certiflcation examination questions to a group of physicians. They were requested to select a limited amount of available case information, indicate a treatment preference (intubation vs allowing to die), estimate the patients survival time if treated, and explain the rationale for their treatment decision. Subjects were 205 internal medicine and family medicine physicians in King County (WA). They either were affiliated with the University of Washington (as residents or faculty) or practiced in the community. University physicians had appointments in either the Department of Internal Medicine or the Department of Family Medicine and were eligible for participation on the basis of recent inpatient care responsibilities. Community physicians were randomly selected from King County. The rates of participation were 84 percent (123 of 150) for University-afIlliated physicians and 69 percent (78 of 113) for community physicians. After obtaining ~nformed consent, physicians read the following case: An elderly, married, male nursing home resident is admitted to your service with worsening shortness of breath of three days' duration. The patient has a history of chronic obstructive pulmonary disease and mild pulmonary hypertension. Six months previously he was treated with 3 Umin of oxygen, which suppressed his respiratory drive. The patient was intubated and subsequently received a tracheostomy when it took two months to' wean him from the respirator. The patient has shortness of breath at rest with an increase and change in the color of his sputum (yellow to green). He has no fever and reports compliance with his prescribed aminophylline, prednisone, and metaproterenol inhaler. Initial evaluation shows a distressed, anxious, mildly blue' man taking 30 breaths/min with diminished breath sounds, ~se rales, and expiratory wheezes in both lung fields. Expectorated sputum shows many polymorphonuclear cells and a predominance of Cram-negative pleomorphic organisms. Arterial blood gas measurements show hypoxemia, hypercarbia, and respiratory acidosis. Chest roentgenogram shows no change since his baseline roentgenogram three months ago. On the basis of these data, treatment in the emergency room is begun for the pres~mptive diagnosis of acute bronchitis caused by H aeinophilw inftuenzae with appropriate dosages of aminophylline, ampicillin, prednisone, metaproterenol inhaler, and vigorous postural drainage and percussion. 1Wo liters per minute of low-flow oxygen is given, an amount slightly less than a previously determined retention threshold. After six hours of the currently prescribed therapy, he looks more fatigued and is struggling more wi~ his breathing. . Next, physicians considered the potential availability of 25 additional items of information. The physicians were then told to imagine (as might be the case in a' real clinical situation) that they had a limited time (two hours) to gather data before they would be forced to make a final treatment decision. In the context of this casemanagement problem, the physicians were allowed to select a limited amount of case inform~on. Physicians selected eight items to acquire more data about the case, and after all items were identified, they learned the details ~m their targeted inqufries. The infOrmation was classifiable into three generic categories: physiologic, social, and professional consultations. Within the physiologic data the fOllowipg infOrmation was potentially available: age, arterial blood gas levels obtained in the emergency room on this admission, bedside measures of pulmonary function taken now, careful review of the patient's previous hospital record describing his prolonged weaning from the respirator, optpatient pulmonary function tests obtained three weeb prior to this admission, repeat artertal blood gas determinadons over the two-hour period, repeat physical examination, review of fluid balance (input/output) since
518
admission, review of repeat chest roentgenogram taken one hour ago with the radiologist, todays complete blood chemistry, differential, and serum electrolytes obtained in the emergency room, and todays morning theophylline blood level. Social information included religion; Insurance status; conversations regarding treatment options with the patient, wife, and son; conversation with wife about patients mental status; and the nursing home report. Consultative information was available from the head nurse of the intensive care unit, chiefmedical resident, "aggressive" and "nonaggressive" colleagues, pulmonary specialist, social worker, and textbook intubation guidelines. The details of the case information are presented in the Appendix. With additional knowledge, the physicians indicated a treatment preference between mechanical ventilation and allowing to die. They also responded to the following question: "What is the projected life expectancy of this patient, if intubated, in terms of months or years?" Nonparametric statistical analyses were used because of the skewed distribution of survival time (SPSS).34 Signfflcance values are reported in the text with the name of the test statistic. Stepwise linear regression was used to identify the independent pieces of information that best predicted survival prognoses. RESULTS
Two hundred five physicians participated in the study, including 72 resident physicians and 55 attending physicians at the University of Washington, and 78 private practitioners. Seventy-two physicians were from the family medicine discipline (18 resident physicians, 14 attending physicians, and 40 private practitioners). One hundred thirty three physicians were from the internal medicine discipline (54 resident physicians, 41 attending physicians, and 38 private practitioners). , The estimates for survival were discrepant with a skewed distribution, the tail of which extended to 60 months. In Figure 1, the distribution of survival estimates are compared between board certified pulmonologists (n = 9) and other physicians (n = 189). This shows that pulmonologists, who have the most expertise to prognosticate survival for patients with COPD and consequently represent a gold standard, provided a narrower range of survival estimates. Their median estimate of survival was five months and nearly 90 percent believed the patient would die within eight months. Comparisons of median survival estimates by physician role (resident, 6.1 months; attending, 6.2 months, private practitioner, 7.9 months), specialty (internal medicine, '6.4 months; family medicine, 6.2 months), subspecialty (pulmonologists, 5.0 months; other physicians, 6.4 months), and setting (with medical trainees, 6.2 months; without medical trainees, 8.0 months) showed no significant differences (p>.05, Kruskal Wallis ANOVA). The estimates of survival were associated with the case information that physicians-selected to help make their treatment decision. In general, physicians who selected a predominance of physiologic information estimated longer survival times for the patient (median Vart8bl1ity In Physician Estimates d Survival(Robert A. PHIIman)
50
Table I-Independent CON In.formstion Predictive cf Surviool1ime*
Percentage of Nonpulmonologists (n=189)
40
Point Biserial Median Survival Correlation Predictions (months) Coefficientt (p level) Not Selected Selected
30 20
Case Information
10 10
50
30
40
50
60
Percentage of Pulmonologists (n=9)
40
%
20
30
10 10
vival.
-.26 (.000) -.21 (.003) -.18 (.013) -.09 (.199)
11.7
.16 (.024) .19 (.009)
6.2
6.1
7.9
5.6
6.4
3.0
8.0
6.2
6.2
11.8
8.5
*Stepwise linear regression: RI = .14 t A negative correlation coefficient indicates thatselection of specific case information is associated with a shorter prediction of survival
20
FIG URE
Conversation with wife Conversation with son Conversation with patient Opinion of "nonaggressive" colleague Intubation guidelines Fluid balance status
20
30 Months
40
50
60
1. Pulmonologist and nonpulmonologist estimates of sur-
survival times: 6.5 months vs 6.0 months, p = .013, Mann-Whitney U test). In contrast, physicians who selected a predominance of social information predicted shorter survival times (median survival times: 5.9 months vs 6.4 months, p =.052, Mann-Whitney U test). Stepwise linear regression identified the independent predictors of the physicians' estimates of survival time (P< .1). Physicians who estimated shorter survival times were more likely to select information about the patient's, wife's, and son's wishes regarding treatment, and a "nonaggressive" colleague's consultative opinions. Physicians who estimated a longer survival were more likely to select information about the standard recommended guidelines for intubation, and a review of the fluid balance status since the patients admission. In aggregate, these variables accounted for 14 percent of the variance. Surprisingly, the amount of selected socialinformation was also an independent predictor of survival time, explaining 7 percent of the variance. Descriptive information about the independent predictors is presented in Table 1. The following selections of case information were significant zero order correlations (p<.05) that proved not to contribute independently to the survival prediction model: the ICU head nurse's report on the availability of a respirator and an leu bed (one respirator and one bed available), outpatient pulmonary function tests obtained three weeks prior to admission, the patient's religious preference (Protestant), pulmonary consultation, repeat arterial blood gas determinations over the two-hour period in the hospital, and a telephone conversation with the nurse from the nursing home to check on the patient's baseline level of function. Three pieces ofavailabledata were known predictors
time.
of shorter survival prognosis in COPD. These were pulmonary function test results (PaCOSh FEVJ, roentgenographic evidence of chronic obstructive pulmonary disease, and the level of functional disability.15.21-29 When more pieces of these "critical" data were chosen, physicians' estimates of survival time were shorter One hundred thirteen physicians selected only one piece of critical data. Their median estimate of survival was 6.3 months. Thirty six physicians selected any combination of two pieces of critical data. Their median estimate of survival was 5.9 months. Only four physicians selected all three pieces of critical data. Their median survival estimate was 3.0 months with a range from one to 12 months. Thirteen percent of the physicians estimated survival time to be equal to or greater than two years. These physicians were not uniquely identifiable by their role, specialty, or site of practice. Their only shared characteristic was that they selected the information about the wifes opinions regarding her husbands treatment less often than other physicians (chisquare, p<.03). DISCUSSION
Physician estimates of survival were investigated because they are inHuential factors in medical decisions that involve the elderly or individuals near the end of life, and are often based on limited empirical data. As such, this represents an area of uncertainty that may be affected by professional or social values rather than "scientific" considerations. A patient management problem describing an elderly, debilitated patient with chronic obstructive pulmonary disease and acute respiratory failure was presented to 205 physicians. Analyses were conducted to identify the factors associated with physicians' this hypothetical patient (if estimates of survival treated with mechanical ventilation). Specifically, physician characteristics (roles, specialty, practice setting)
ror
CHEST I 91 I 4 I APRIL, 1987
117
and management of case information were analyzed to assess their possible influence on physicians' prognostications. . The estimates of survival for the hypothetical patient ranged from one month to five years, with approximately half the physicians estimating survival to be less than six months. In general, the estimates of survival were similar for internists and family physicians; residents, attending physicians, and private practitioners; and physicians caring for patients with or without the presence of medical trainees. Although board certified pulmonologists generally estimated the patient's survival to be less than other physicians and demonstrated the narrowest range of survival estimates, their estimates were not appreciably different from those' of physicians without formal pulmonary training. Eighty-seven percent of all physicians estimated that the patient would live less than two years. The management of case information demonstrated intriguing associations with physicians' estimates. The preferential selection of social information was associated with shorter estimates of survival. The association between acquisition of social information and survival estimates (especially opinions by patients and family members regarding treatment) suggests that physicians may solicit subjective information from these individuals because they have learned to trust its predictive value. In addition, the change may reflect an appreciation fo~ published data that suggest that patients may predict their own mortality better than physicians.P'" As such, these findings may document for the first time the use of subjective information for "hard" predictions. Alternatively, physicians may have been seeking support from the family for their 'own subjective treatment preferences. Unfortunately, a cross-sectional design causality cannot be inferred from these associations. Just as the association between social case information and shorter estimates of survival were intriguing, so was the finding that selection of more physiologic case information was associated with longer estimates of survival. Based on the literature there were three pieces of case information (pulmonary function, radiographic evidence of COPD, and physical dysfunction resulting from the pulmonary disease) that were predictors of limited survival. When physicians selected more of these data, their estimates were shorter (sixmonth survival estimates with one piece of data to three-month survival estimates with three pieces of data). Yet, when physicians selected more physiologic information in general, their estimates for the patient's survival were longer. This suggests that physiologic inquiries yielding negative results or demonstrating the absence of complications may have led to longer estimates of survival. This is not completely surprising. Physicians often have difficulty interpreting nega518
tive test results and making predictions.F:" An alternate interpretation which demonstrates the importance of avoiding the inference of causality is that physicians who focus on physiologic information are optimistic regarding the efficacy oftreatment and their survival estimates, regardless of the data. In this scenario, selection of physiologic data would only be a marker for an optimistic personality. Stepwise multiple linear regression identified independent predictors of survival. Selection of subjective information regarding treatment preferences independently predicted shorter estimates of survival. Selection of information guidelines for intubation and the patients fluid status independently predicted longer estimates of survival. In aggregate, these variables only explained 14 percent of the variance, lending support to the unpredictability of physicians' estimates of survival for an individual case depicting COPD. The natural history of severe chronic obstructive pulmonary disease (FEV1 <.75L) suggests an approxiP1~e survival rate of 50 percent at two to three years. 21-2.'5 The expected survival for a severely dysfunctional patient with COPD and an episode of acute respiratory failure requiring mechanical ventilation, much like the hypothetical patient, is worse. In this situation, hospital mortality averages approximately 45 percentts·18·19.31.33 and the six-month expected mortality runs as high as 50 to 75 percent. J:S.17.~ Many of the physicians in this study estimated the patient's survival to be in this range, especially the pulmonologists and those who selected the known predictors of mortality for COPD. However, approximately 13 percent of the physicians estimated that 'the patient would live from two to five years, The only variable associated with this group of physicians was their preferential nonselection of information from the wife regarding her opinions about treatment. This study has several limitations. First, its design is cross-sectional and causal relationships cannot be inferred. Second, it involves physicians in one region of the country where practice patterns and values may be unique. As such, the generalizability ofthe results may be limited. Third, the management of case information and physician attributes only explain a small portion of the physicians' estimates of survival. Therefore, important unmeasured and unrecognized variables may not have been considered in this study. Finally, many of the statistically significant differences in survival estimates may not be clinically significant. However, in a previous paper the physicians' selection of categories of case information was documented to be an independent predictor of treatment intentions. 3 However; the study demonstrates several important findings that deserve attention, 'First, although estimates of survival may influence major treatment decisions, such as those' involving the use of life-sustaining
procedures, these estimates vary between physicians without being well understood. Prognosis regarding survival is a legitimate factor in medical decisions and one that physicians and patients should consider. If physicians' estimates are variable, then different patients with the same problem (prognosis) may be treated differently. If physicians' estimates are inaccurate, then major decisions may occur after deliberations based on false assessments. When prognosis regarding survival is particularly uncertain, or when attempting to apply statistical probabilities to an individual case, perhaps two caveats should be remembered: 1) prognostication information should be presented to patients with qualifications, and 2) the importance given to the survival estimates should be minimized somewhat by physicians in their own deliberations. Second, physician estimates may be influenced by social information to a greater degree than by physiologic uJbrmation. This finding suggests that under conditions of uncertainty, physicians may use data that represent the art of medicine more than the science of medicine. This behavior needs to be confirmed in other situations and analyzed to ascertain whether it leads to sensitive, compassionate care. Third, empirical and physiologic data influence physician estimates of survival, but only a limited number of physicians (n = 4) selected all the available data known to be predictive of mortality. This suggests that physicians might benefit from further education or decision aids (algorithms) regarding known predictors of mortality in COPD. Additional education could narrow the range of estimates and lead to a more consistent pattern of care for this condition based on the current state-of-the-art. Finally, there is a tremendous gap in our understanding of physicians' predictions regarding survival in this clinical context. As such, it represents fertile ground for further research. ACKNOWLEDGMENTS: The author wishes to thank Drs. Daniel Kent and Thomas Martin fur their careful review of the manuscript.
REFERENCES 1 Gaensler EA, Cugell DW: Lindgren I, Verstraeten JM, Smith SS, Streider JW The role of pulmonary insufficiency in mortality and Invalidism followiilg surgery for pulmonary tuberculosis. J . Thorac Surg 1955; 29: 163-87 2 Olsen ON, Block AJ Swenson EW, Castle JR, Wynne JW Pulmonary function evaluation of the lung resection candidate: a prospective study. Am Rev Respir Dis 1975; 111:379-87 3 Pearlman RA, Inui TS, Carter WB. Variability in physician bioethical decision-making. Ann Int Med 1982; 97:420-25 4 Perkins MSt lonsen AR, Epstein wv. Providers as predictors: using outcome predictions in intensive care. Crit Care Med 1986; 14:105-10 5 Linn BS, Linn MW Estimating survival for patients with latestage cancer. South Moo J 1980; 73:838-40 6 Pauker SG, McNeil BJ. Impact of patient preferences on the selection of therapy. J Chron Dis 1981; 34:77-86
7 Chang RWS, Jacobs S, Lee B. Use of Apache II severity of disease classification to identify intensive-care-unit patients who would not benefit from total parenteral nutrition. Lancet 1986; 2:1483-87 8 McNeil BJ, Weichselbaum R, Pauker SG. Fallacy of the five-year survival in lung cancer. N Eng} J Moo 1978; 299:1397-1401 9 McNeil BJ, Weichselbaum R, Pauker SG. Uadeoffs between quality and quantity of life in laryngeal cancer. N Eng} J Moo 1981; 305:982-87 10 Sudnow D. Passing on. Englewood Cliffs, New Jersey: PrenticeHall Inc, 1967 11 Crane D, The sanctity of social life: physicians' treatment of critically ill patients. New York: Russell Sage Foundation, 1975. 12 Legall JR, Bran-Buisson C, 1hJnet ~ et al..In8uence of age, previous health status, and severity of acute illness on outcome from intensive care. Critical Care Med 1982; 10:868 13 Brown NK, Thompson DJ. Nontreatment of fever in extendedcare facilities. N Eng) J Moo 1979; 300:1246-50 14 Pearlman RA, Speer JB Jr. Quality-of-life considerations in geriatric care. Am Geriatr Soc 1983; 31:113-20 15 Jessen O. Uacheostomy and artificial ventilation in chronic lung disease. Lancet 1967; 2:9-12 16 Burk RH, George RB. Acute respiratory failure in chronic obstructive pulmonary disease. Arch Intern Med 1973; 132:865-68 17 Moser KM, Shibel EM, Beamon AJ. Acute respiratory failure in obstructive lung disease. Long-term survival after treatment in an intensive care unit. JAMA 1973; 225:705-07 18 Gottlieb LS, Balchum oj Course of chronic obstructive pulmonary disease following first onset of respiratory failure. Chest
1973; 63:5-8
w
19 Sluiter JH, Blokzul EJ, Van Dul Van Haeringen JR, Hilvering C, Steenhuis EJ. Conservative and respirator treatment of acute respiratory insufficiency in patients with chronic obstructive lung disease. Am Rev Respir Dis 1972; 105:932-42 20 Martin TR, Lewis S~ Albert RK. The prognosis of patients with chronic obstructive pulmonary disease after hospitalization for acute respiratory failure. Chest 1982; 82:310-14 21 Traver GA, Cline MG, Burrows B. Predictors of mortality in chronic obstructive pulmonary disease. Am Rev Respir Dis 1979;
119:895-902
22 Renzetti VD Jr, McClement JH t Litt BD. The Veterans Administration cooperative study of pulmonary function. III. Mortality in relation to respiratory function in chronic obstructive pulmonary disease. Am J Med 1966; 41:115-29 23 Burrows B, Earle RH. Course and prognosis of chronic obstructive lung disease. A prospective study of 200 patients. N Eng} J Med 1969; 280:397-404 24 Diener CF, Burrows B. Further observations on the course and prognosis of chronic obstructive lung disease. Am Rev Respir Dis
1975; 111:719-24
25 Boushy SF, Thompson HK Jr, North LB, Beale AR, Snow TR. Prognosis in chronic obstructive pulmonary disease. Am Rev Respir Dis 1973; 108:1373-83 26 Beaty TH, Cohen BH, Newill CA, Menkes HA, Diamond EL, Chen CJ. Impaired pulmonary function as a risk factor for mortality. Am J Epidemioll982; 116:102-13 27 Beaty TH, Newill CA, Cohen BH, Tockman MS, Bryant SU, Spurgeon HA. Effects of pulmonary function on mortality. J Chron Dis 1985; 38:703-10 28 Sukumalchantra ~ Dinakara ~ Williams MH Jr. Prognosis ofpatients with chronic obstructive pulmonary disease after hospitalization for acute ventilatory failure: a three-year follow-up study. Chron Obstructive Pulm Dis 1965; 93:215-26 29 Knaus WAt Zimmerman JE, Wagner D~ Draper EA, Lawrence DE. APACHE-acute physiology and chronic health evaluation: a physiologically based classification system. Crit Care Med 1981;
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30 Teres 0, Brown RB, Lemeshow S. Predicting mortality of intensive care unit' patients. The importance of coma. Crit Care Med 1982; 10:86-95 31 Davis H, Lefrak SS, Miller 0, Malt S. Prolonged mechanically assisted ventilation. An analysis of outcome and charges. JAMA 1980; 243:43-45 32 Witek TJ, Schachter EN, Dean NL, Beck GJ. Mechanicallyassisted ventilation in a community hospital. Immediate outcome, hospital charges, and follow-up of patients. Arch Intern Med 1985; 145:235-39 33 McLean RF, McIntosh JD, Kung GY, Leung DMW, Byrick RJ. Outcome of respiratory intensive care for the elderly. Crit Care Med 1985;13:625-29 34 Nie NH, Hull CH, Jenkins JG, Steinbrenner K, Bent DB. Statistical package for the social sciences. New York: McGraw-Hill, Inc, 1975 35 Mossey JM, Shapiro E. Self-rated health: a predictor of mortality among the elderly. Am J Public Health 1982; 72:800-08 36 LaRue A, Bank L, Jarvik L, Hetland M. Health in old age: how do physicians' ratings and self-ratings compare? 1979; 34:687-91 37 Centor RM, Witherspoon JM, Dalton H~ Brody CE, Link K. The diagnosis of strep throat in adults in the emergency room. Med Decis Making 1981; 1:239-46 38 Christensen-Szalanski Jll, Bushyhead lB. Physicians" misunderstanding of normal findings. Med Decis Making 1983; 3:169-75 39 Politser E Decision analysis and clinical judgment. A re-evaluation. Med Decis Making 1981; 1:361-89 40 Asmundsson E Kilburn KH. Survival after acute respiratory failure. 145 patients observed 5 to 8~ years. Ann Intern Med 1974;
I.
J.
K.
L. M. N.
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APPENDIX
A. Age: 69 years old. B. Arterial blood gaslevels obtained in the emergency room on this admission: ABG (room air): Po l = 3 8 mm Hg; Pco, = 58 mm Hg; pH = 7.32, saturation percentage = 65 percent. C. Bedside measures of pulmonary function taken now: vital capacity-patient unable to cooperate, FEVl =300
O. E
Q.
ml.
D. Call to the ICU head nurse to check on the availability of a respirator and an ICU bed. There is one ICU bed and one respirator available. The nurse's response to learning who the potential patient might be was, "Not him again. Can't you treat him outside the Icur' E. Careful review of the patient's previous hospital record describing his prolonged weaning from the respirator: The weaning was not prolonged by any secondary complications. F: Case discussion with chief medical resident at the hospital: 01011' m not sure which is worse: bronchogenic lung cancer or severe chronic obstructive lung disease. Which way does the patient want to be treated?" G. Conversations With patient regarding treatment options: On admission the patient agreed to the proposed treatment plan. At the end of the first conversation he queried, UNo tube, right?" You responded with, "It doesn't seem necessary at this time." When the situation deteriorated, you returned to ask th~ patient about intubation again. However, he was somnolent and unable to answer questions meaningfully. H. Conversation with patients son about treatment: The son expressed the wish that no heroics be performed because 520
R.
of his father's suffering and current lifestyle. He also felt that his mother was suffering as a result of his father's condition. Conversation with the patient's wife about the patient's baseline mental status: OIcHe is slightly depressed and slightly forgetful. On rare occasions he can enjoy himself like the old days." Conversation with the patients wife about treatment options: CCI love him greatly and feel badly that I had to place him in a nursing home for appropriate care. I really hate seeing him suffer and hope that he'll get better:" Insurance status of patient and family: The patient and his wife qualify by virtue of their ages for Medicare. An application for acceptance to Medicaid is pending. Opinion about the case by a "non-aggressive" colleague: "The patient represents end-stage lung disease. What he really needs is a new set of lungs." Opinion about the case by an "aggressive" colleague: "The patient should maintain a tracheostomy button for possible future needs." Outpatient pulmonary function test results obtained three weeks prior to this admission: Vital capacity = 1.5 (40 percent); FEV tNC=O.22; FEF=0.17 (9 percent); residual volume = 5.4 (210 percent); TLC = 8.0 (150 percent); RVffLC =0.68; ABC (room air): P0 2 = 46 mm Hg, Pco, = 48 mm Hg, Pco, = 48 mm Hg, pH = 7.35, saturation percentage = 77 percent. Interpretation: severe COPD, chronic compensated respiratory acidosis with hypoxemia and hypercarbia. Patients religious preference: Protestant Pulmonary consultation: "The case reflects progressive respiratory acidosis in the face of maximal nonaggressive therapy. The patient will require acute mechanical assistance if he is to survive this insult. Kindly let me know if you decide to intubate and I'll follow the case with you." Recommended guidelines for intubation: Respiratory rate = 351minute; vital capacity < 15 mglkg body weight; FEVt
46 46 46 Po! 90-110 64 72 80 Peo235-45 pH 7.35-7.45 7.29 7.23 7.19 75 72 67 Saturation 97%* *Varies with age and sex S. Repeat physical examination: Two changes noted on the repeat examination: 1) respiratory rate now 40, and 2) mental status altered (somnolence). L Review of fluid balance (input/output) since admission: in balance. U. Review of repeat chest roentgenogram taken one hour ago with the radiologist: the chest roentgenogram shows chronic obstructive lung disease with no acute processes. There is no evidence of a pneumothorax. V. Social workers report on the patient and his family situation: The wife feels guilty about having placed her husband in a nursing home. Their financial savings are depleted because of the nursing home costs. The applicaYariabHity In Physician Estimates of Survival(Robert A Pearlman)
tion for welfare has been submitted. W Telephone conversation with the nurse from the patient's nursing home to check on his baseline level of function: "His activity level is restricted to walking halfway across the room, at which time his shortness of breath inhibits further activity. He uses a wheelchair part of the time. His wife visits once weekly since he was placed there three months ago."
x.
'Iodays complete blood chemistry, differential, and serum electrolytes obtained in the emergency room: normal except fur leukocyte count =12,I00/co mm with 12 percent bands, 78 percent polymorphonuclear cells, 8 percent lymphocytes, 1 percent monocytes, and 1 percent eosinophils. Y. 'Iodays morning theophylline blood level: 20 fJ.glml (therapeutic range: 10-20 fJ.glml).
20 Years of PrOgrammed Stimulation of the Heart Co-sponsored by the North American Society of Pacing and Electrophysiology, this congress,
to answer "Where to go from Here" will be held in Maastricht, The Netherlands, June 1-5. For
information, contact MECC, Congress Management B~ Posthus 630, 6200 AB Maastricht, The Netherlands.
Coronary Angiography, 1987 The Department of Radiology, Brigham and Womens Hospital and Harvard MedicalSchool, co-sponsored by the Council on Cardiovascular Radiology of the American Heart Association, will present this annual postgraduate course JUlie 15-18, at the Marriott Copley Place, Boston. For information, contact Department of Continuing Education, Brigham and Women's Hospital, Department of Radiology, 75 Francis Street, Boston 02115.
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