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Evidence Based Prognostication Peoria 2010 (1)

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Updated version of Prognostication presentation. Not be used as sole basis for any medical decisions. Please talk with your doctor if you have questions about this information.

Updated version of Prognostication presentation. Not be used as sole basis for any medical decisions. Please talk with your doctor if you have questions about this information.

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  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield 11.     Prognosis (Evidence-based) A.      Disease specific i.      Cancer ii.     COPD iii.    CHF iv.     ALS v.      Stroke (Acute vs chronic) vi.     Dementia B.      Debility i.      Wt loss ii.     Decubiti Als Trauma Debility End stage heart
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Common responses to what is the prognosis?, obliged to perform many other unpleasant tasks, prognosis can seem mysterious powerful, final like death, routine versus serious prognosis (prognosis with moral overtones) PubMed results Jan 2007 Diagnosis 5.5mil Therapy 4.8 mil Prognosis 600k Ellipses of prognosis The Principles and Practices of Medicine 1892-1988
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Estimation of possible future outcomes of a treatment or a disease process Founded upon a combination of personal experience, statistics, and validated models
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Estimation of possible future outcomes of a treatment or a disease process Founded upon a combination of personal experience, statistics, and validated models
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Failure to prognosticate may lead to harm (unwanted therapies, flogging, etc.) threat versus reassurance
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Concept of natural course – problematic – impact of therapy interventions and the doctors role in responsibility in clinical course Prognostication as reassuring/comforting Prognosis as managing death – avoiding responsibility Predicting controls death but also associates you with death
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Clinical prediction vs. statistical modeling Accuracy Applicability to clinical situation Description of outcomes clinically irrelevant Inconsistent application
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield During the phase II intervention, patients experienced no improvement in patient-physician communication (eg, 37% of control patients and 40% of intervention patients discussed CPR preferences) or in the five targeted outcomes, i.e., incidence of timing of written DNR orders (adjusted ratio, 1.02; 95% confidence interval [CI], 0.90 to 1.15) physicians' knowledge of their patients' preferences not to be resuscitated (adjusted ratio, 1.22; 95% CI, 0.99 to 1.49), number of days spent in an ICU, receiving mechanical ventilation, or comatose before death (adjusted ratio, 0.97; 95% CI, 0.87 to 1.07), or level of reported pain (adjusted ratio, 1.15; 95% CI, 1.00 to 1.33). The intervention also did not reduce use of hospital resources (adjusted ratio, 1.05; 95% CI, 0.99 to 1.12).
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Black is cancer, gray in non-cancer
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Validated by Morita Complex, 6 week breakpoint Palliative performance scale (modified Karnofsky) 10–20 4 30–50 2.5 ‡ 60 0 Oral intake Severely reduced 2.5 Moderately reduced 1.0 Normal 0 Oedema Present 1.0 Absent 0.0 Dyspnoea at rest Present 3.5 Absent 0.0 Delirium Present 4.0 Absent 0.0 Interpretation of the PPI score Total score PPV for 6-week survival NPV for 6-week survival >4 0.83 0.71
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Adjuvant Online Breast Colon Lung
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Pubmed research Prognosis 660k Therapy 5.1m Diagnosis 5.9m
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield We must know the art and the science, be willing to make decisions in the face of error
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Mortality thoroughly studied Organ allocation for liver transplant Great effort to allocate organs according to “sickest first” instead of location and waiting times
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Reliably predicts death within 1 week, 3 months, and 1 year Kamath et al. Hepatology, 2001 Do we want to standardize the citations in the lower left corner?
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Hepatology/Liver Transplantation Serum sodium, direct measure of severity of portal hypertension. Portal htn -> splanchnic arterial dilation -> decreased svr -> increased sympathetic, adh, renin-ang-ald system
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Involuntary weight loss of 5% or more
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Found in NCCN guidelines
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Taken from National Comprehensive Cancer Network guidelines 2006
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Limited stage = disease confined to ipsilateral hemithorax and one radiation field Only 33% of diagnoses are limited stage As reported on a mesothelioma website, I couldn’t find references on that website so maybe I shouldn’t use this data…it was the only place I found thorough numbers… I also found a website with article entitled “small cell lung cancer” by Jahan, T et al. www.cancersupportivecare.com that quoted the following numbers Limited stage 2 year survival 20% Extensive stage 2 year survival 5% Recurrence after remission 2-3 months
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Sahn in Seminars in Respiratory and Critical Care 2001
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield New 2008
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield New 2008
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield New for 2008
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield New for 2008
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield First comprehensive multivariate approach Good vs poor outcome Poor includes severe disability, vegetative state, and death Good is moderate disability, independent but unable to resume prior activity and good recovery 20 seconds no O2, 5 min no ATP no glucose Old text - “Predicting Outcome From Hypoxic-Ischemic Coma” Levy et al. JAMA 1985 Study developed newly constructed, empirically derived guidelines to predict outcome within the first few days after a cardiac arrest or similar global hypoxic-ischemic insult
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Signs related to recovery/lack of recovery 0/52 patients initially lacking pupillary reflex ever became independent, only 3 regained consciousness At three days absent or posturing motor responses were incompatible with future independence At initial exam, most favorable sign was incomprehensible speech
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Proposed that patients with absent pupil and motor response no better than flexion at 72 hr undergo ssep, if no response no chance of recovery and further care regarded as futile, palliative care given.
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield O2 and consciousness lost within 20 seconds, glucose and atp depleted by 5 minutes Citatations? Booth JAMA 2004
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Item 1 & 3 sound the same
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Severe = requiring mechanical ventilation
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Also lower body temp
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Citation Also Holloway
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Citation Also holloway
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Citation Holloway
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield 325 patients with dementia
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Activities of Daily Living Scale = 28∗ 1.9 ––––– Male Sex 1.9 ––––– Cancer 1.7 ––––– Oxygen Therapy Needed in Prior 14 Days 1.6 ––––– Congestive Heart Failure 1.6 ––––– Shortness of Breath 1.5 ––––– <25% of Food Eaten at Most Meals 1.5 ––––– Unstable Medical Condition 1.5 ––––– Bowel Incontinence 1.5 ––––– Bedfast 1.5 ––––– Age >83 y 1.4 ––––– Not Awake Most of the Day 1.4 –––––
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield If Total Risk Score is… 0 1 or 2 3, 4, or 5 6, 7, or 8 9, 10, or 11 Risk Estimate of Death Within 6 Months, % 8.9 10.8 23.2 40.4 57.0 ≥ 12 70.0
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Impact of delirium on the short term prognosis of advanced cancer patients. Italian Multicenter Study Group on Palliative Care. Caraceni A , Nanni O , Maltoni M , Piva L , Indelli M , Arnoldi E , Monti M , Montanari L , Amadori D , De Conno F . Unita' di Riabilitazione e Terapie Palliative, Department of Anesthesia and Critical Care, National Cancer Institute of Milan, Italy. BACKGROUND: The objective of this study was to evaluate the impact of delirium on the survival of advanced cancer patients also assessed with a validated prognostic score (the palliative prognostic [PaP] score). METHODS: The study population was a prospective multicenter consecutive case series of advanced cancer patients for whom chemotherapy was no longer considered viable and who were referred to palliative care programs. Clinical and biologic prognostic factors included in the PaP score were assessed at study entry. The Confusion Assessment Method criteria were applied to screen patients presenting with delirium. Survival times were measured from time of enrollment and death taken as an outcome. Survival curves were traced with the Kaplan-Meier method and comparison were based on log rank tests. RESULTS: Delirium was found in 109 cases among 393 consecutive patients (27.7%). The diagnosis of delirium was independently associated with male gender, central nervous system metastases, lower performance status, worse clinical prediction of survival, and progestational treatment. The survival curve of patients with delirium was significantly different from the nondelirious patients curve (log rank, 31.6, P < 0.0001). The median survival time was 21 days (95% confidence interval [CI], 16-27) for the delirious patients and 39 days (95% CI 33-49) for the others. Multivariate analysis showed that the diagnosis of delirium and PaP score were independently associated with prognosis. CONCLUSIONS: The diagnosis of delirium significantly worsens life expectancy prognosticated with the PaP score. By using the PaP score together with the assessment of cognitive status, physicians can correctly predict patients 30-day survival in greater than 70% of cases.
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Prognostic factors, clinical course, and hospital outcome of patients with chronic obstructive pulmonary disease admitted to an intensive care unit for acute respiratory failure. Afessa B , Morales IJ , Scanlon PD , Peters SG . Department of Internal Medicine, Division of Pulmonary and Critical Care, University of Florida Health Science Center, Jacksonville, FL, USA. afessa.bekele@mayo.edu OBJECTIVE: To describe prognostic factors, clinical course, and hospital outcome of patients with chronic obstructive pulmonary disease admitted to an intensive care unit for acute respiratory failure. DESIGN: Analysis of prospectively collected data. SETTING: A multidisciplinary intensive care unit of an inner-city university hospital. PATIENTS: Patients with chronic obstructive pulmonary disease admitted to an intensive care unit for acute respiratory failure from August 1995 through July 1998. MEASUREMENTS AND MAIN RESULTS: Data were obtained concerning demographics, arterial blood gas, Acute Physiology and Chronic Health Evaluation (APACHE) II score, sepsis, mechanical ventilation, organ failure, complications, and hospital mortality rate. Fifty-nine percent of patients were male, 63% white, and 36% African-American; the mean age was 63.1 +/- 8.9 yrs. Noninvasive mechanical ventilation was tried in 40% of patients and was successful in 54% of them. Invasive mechanical ventilation was required in 61% of the 250 admissions. Sepsis developed in 31% of patients, nonpulmonary organ failure in 20%, pneumothorax in 3%, and acute respiratory distress syndrome in 2%. Multiple organ failure developed in 31% of patients with sepsis compared with 3% without sepsis (p <.0001). Predicted and observed hospital mortality rates were 30% and 15%, respectively. Differences in age and arterial carbon dioxide and oxygen tensions between survivors and nonsurvivors were not significant. Arterial pH was lower in nonsurvivors than in survivors (7.21 vs. 7.25, p =.0408). The APACHE II-predicted mortality rate (p =.0001; odds ratio, 1.046; 95% confidence interval, 1.022-1.070) and number of organ failures (p <.0001; odds ratio, 5.524; 95% confidence interval, 3.041-10.031) were independent predictors of hospital outcome; invasive mechanical ventilation was not an independent predictor. CONCLUSIONS: Physiologic abnormalities at admission to an intensive care unit and development of nonrespiratory organ failure are important predictors of hospital outcome for critically ill patients with chronic obstructive pulmonary disease who have acute respiratory failure. Improved outcome would require prevention and appropriate treatment of sepsis and multiple organ failure.
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Impact of delirium on the short term prognosis of advanced cancer patients. Italian Multicenter Study Group on Palliative Care. Caraceni A , Nanni O , Maltoni M , Piva L , Indelli M , Arnoldi E , Monti M , Montanari L , Amadori D , De Conno F . Unita' di Riabilitazione e Terapie Palliative, Department of Anesthesia and Critical Care, National Cancer Institute of Milan, Italy. BACKGROUND: The objective of this study was to evaluate the impact of delirium on the survival of advanced cancer patients also assessed with a validated prognostic score (the palliative prognostic [PaP] score). METHODS: The study population was a prospective multicenter consecutive case series of advanced cancer patients for whom chemotherapy was no longer considered viable and who were referred to palliative care programs. Clinical and biologic prognostic factors included in the PaP score were assessed at study entry. The Confusion Assessment Method criteria were applied to screen patients presenting with delirium. Survival times were measured from time of enrollment and death taken as an outcome. Survival curves were traced with the Kaplan-Meier method and comparison were based on log rank tests. RESULTS: Delirium was found in 109 cases among 393 consecutive patients (27.7%). The diagnosis of delirium was independently associated with male gender, central nervous system metastases, lower performance status, worse clinical prediction of survival, and progestational treatment. The survival curve of patients with delirium was significantly different from the nondelirious patients curve (log rank, 31.6, P < 0.0001). The median survival time was 21 days (95% confidence interval [CI], 16-27) for the delirious patients and 39 days (95% CI 33-49) for the others. Multivariate analysis showed that the diagnosis of delirium and PaP score were independently associated with prognosis. CONCLUSIONS: The diagnosis of delirium significantly worsens life expectancy prognosticated with the PaP score. By using the PaP score together with the assessment of cognitive status, physicians can correctly predict patients 30-day survival in greater than 70% of cases.
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Narcotic and benzodiazepine use after withdrawal of life support: association with time to death? Chan JD , Treece PD , Engelberg RA , Crowley L , Rubenfeld GD , Steinberg KP , Curtis JR . Department of Epidemiology, School of Public Health and Community Medicine, University of Washington, Seattle, USA. jdchan@u.washington.edu OBJECTIVE: To determine whether the dose of narcotics and benzodiazepines is associated with length of time from mechanical ventilation withdrawal to death in the setting of withdrawal of life-sustaining treatment in the ICU. DESIGN: Retrospective chart review. SETTING: University-affiliated, level I trauma center. PATIENTS: Consecutive critically ill patients who had mechanical ventilation withdrawn and subsequently died in the ICU during two study time periods. RESULTS: There were 75 eligible patients with a mean age of 59 years. The primary ICU admission diagnoses included intracranial hemorrhage (37%), trauma (27%), acute respiratory failure (27%), and acute renal failure (20%). Patients died during a median of 35 min (range, 1 to 890 min) after ventilator withdrawal. On average, 16.2 mg/h opiates in morphine equivalents and 7.5 mg/h benzodiazepine in lorazepam equivalents were administered during the time period starting 1 h before ventilator withdrawal and ending at death. There was no statistically significant relationship between the average hourly narcotic and benzodiazepine use during the 1-h period prior to ventilator withdrawal until death, and the time from ventilator withdrawal to death. The restriction of medication assessment in the last 2 h of life showed an inverse association between the use of benzodiazepines and time to death. For every 1 mg/h increase in benzodiazepine use, time to death was increased by 13 min (p = 0.015). There was no relationship between narcotic dose and time to death during the last 2 h of life (p = 0.11). CONCLUSIONS: We found no evidence that the use of narcotics or benzodiazepines to treat discomfort after the withdrawal of life support hastens death in critically ill patients at our center. Clinicians should strive to control patient symptoms in this setting and should document the rationale for escalating drug doses. PMID: 15249473 [PubMed - indexed for MEDLINE]
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Clinical predictors and outcomes for patients requiring tracheostomy in the intensive care unit. Kollef MH , Ahrens TS , Shannon W . Department of Medicine, Washington University School of Medicine, St.Louis, MO, USA. OBJECTIVE: To identify clinical predictors for tracheostomy among patients requiring mechanical ventilation in the intensive care unit (ICU) setting and to describe the outcomes of patients receiving a tracheostomy. DESIGN: Prospective cohort study. SETTING: Intensive care units of Barnes-Jewish Hospital, an urban teaching hospital. PATIENTS: 521 patients requiring mechanical ventilation in an ICU for >12 hours. INTERVENTIONS: Prospective patient surveillance and data collection. MEASUREMENTS AND MAIN RESULTS: The main variables studied were hospital mortality, duration of mechanical ventilation, length of stay in the ICU and the hospital, and acquired organ-system derangements. Fifty-one (9.8%) patients received a tracheostomy. The hospital mortality of patients with a tracheostomy was statistically less than the hospital mortality of patients not receiving a tracheostomy (13.7% vs. 26.4%; p = .048), despite having a similar severity of illness at the time of admission to the ICU (Acute Physiology and Chronic Health Evaluation [APACHE] II scores, 19.2 +/- 6.1 vs. 17.8 +/- 7.2; p = .173). Patients receiving a tracheostomy had significantly longer durations of mechanical ventilation (19.5 +/- 15.7 days vs. 4.1 +/- 5.3 days; p < .001) and hospitalization (30.9 +/- 18.1 days vs. 12.8 +/- 10.1 days; p < .001) compared with patients not receiving a tracheostomy. Similarly, the average duration of intensive care was significantly longer among the hospital nonsurvivors receiving a tracheostomy (n = 7) compared with the hospital nonsurvivors without a tracheostomy (n = 124; 30.9 +/- 16.3 days vs. 7.9 +/- 7.3 days; p < .001). Multiple logistic regression analysis demonstrated that the development of nosocomial pneumonia (adjusted odds ratio [AOR], 4.72; 95% confidence interval [CI], 3.24-6.87; p < .001), the administration of aerosol treatments (AOR, 3.00; 95% CI, 2.184.13; p < .001), having a witnessed aspiration event (AOR, 3.79; 95% CI, 2.30-6.24; p = .008), and requiring reintubation (AOR, 2.21; 95% CI, 1.54-3.18; p = .028) were variables independently associated with patients undergoing tracheostomy and receiving prolonged ventilatory support. Among the 44 survivors receiving a tracheostomy in the ICU, 38 (86.4%) were alive 30 days after hospital discharge and 31 (70.5%) were living at home. CONCLUSIONS: Despite having longer lengths of stay in the ICU and hospital, patients with respiratory failure who received a tracheostomy had favorable outcomes compared with patients who did not receive a tracheostomy. These data suggest that physicians are capable of selecting critically ill patients who most likely will benefit from placement of a tracheostomy. Additionally, specific clinical variables were identified as risk factors for prolonged ventilatory assistance and the need for tracheostomy.
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield 5 year 65% with cancer For example, a serum albumin of less than 3.0 g/dL versus greater than 4.0 g/dL confers a 4.4 times greater risk of death; a serum albumin level of less than 3.5 g/dL is associated with a 1–year mortality of approximately 50%. For stage 5 CKD patients, poor functional status is also highly predictive of early death. Fifteen studies examining the relationship between functional status and mortality found a significant association with early death. Measures used to assess functional status have included the Karnofsky or Modified Karnofsky Scale, the Gutman functional status, activities of daily living, and Medical Outcomes Study 36-item Short Form (SF-36).2 In 2000, Beddhu
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield JPMrenal pall care article
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Added for 2008 Zoccolella, S et al. for the SLAP Registry. Analysis of survival and prognostic factors in amyotrophic lateral sclerosis: a population based study. J Neurol Neurosurg Psychiatry . Volume 79(1), January 2008, pp 33-7. MRC CRASH Trial Collaborators. Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. BMJ . 2008 February 23; 336(7641): 425–429. Kinzbrunner BM, Weinreb NJ, Merriman MP. Debility, unspecified: a terminal diagnosis. Am J Hosp Palliat Care. 1996 Nov-Dec;13(6):38-44.
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield Added for 2008 Zoccolella, S et al. for the SLAP Registry. Analysis of survival and prognostic factors in amyotrophic lateral sclerosis: a population based study. J Neurol Neurosurg Psychiatry . Volume 79(1), January 2008, pp 33-7. MRC CRASH Trial Collaborators. Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. BMJ . 2008 February 23; 336(7641): 425–429. Kinzbrunner BM, Weinreb NJ, Merriman MP. Debility, unspecified: a terminal diagnosis. Am J Hosp Palliat Care. 1996 Nov-Dec;13(6):38-44.
  • Evidence Based Prognostication - AAHPM Annual Assembly 2007 February 14, 2007 Sinclair, Salacz, Affield   1: Mirimanoff RO, Gorlia T, Mason W, Van den Bent MJ, Kortmann RD, Fisher B, Reni M, Brandes AA, Curschmann J, Villa S, Cairncross G, Allgeier A, Lacombe D, Stupp R.Related Articles, Links Radiotherapy and temozolomide for newly diagnosed glioblastoma: recursive partitioning analysis of the EORTC 26981/22981-NCIC CE3 phase III randomized trial. J Clin Oncol. 2006 Jun 1;24(16):2563-9. PMID: 16735709 [PubMed - indexed for MEDLINE] 2: Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, Belanger K, Brandes AA, Marosi C, Bogdahn U, Curschmann J, Janzer RC, Ludwin SK, Gorlia T, Allgeier A, Lacombe D, Cairncross JG, Eisenhauer E, Mirimanoff RO; European Organisation for Research and Treatment of Cancer Brain Tumor and Radiotherapy Groups; National Cancer Institute of Canada Clinical Trials Group.Related Articles, Links Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med. 2005 Mar 10;352(10):987-96. PMID: 15758009 [PubMed - indexed for MEDLINE] 3: Gaspar L, Scott C, Rotman M, Asbell S, Phillips T, Wasserman T, McKenna WG, Byhardt R.Related Articles, Links Recursive partitioning analysis (RPA) of prognostic factors in three Radiation Therapy Oncology Group (RTOG) brain metastases trials. Int J Radiat Oncol Biol Phys. 1997 Mar 1;37(4):745-51. PMID: 9128946 [PubMed - indexed for MEDLINE] 4: Athanassiou H, Synodinou M, Maragoudakis E, Paraskevaidis M, Verigos C, Misailidou D, Antonadou D, Saris G, Beroukas K, Karageorgis P.Related Articles, Links Randomized phase II study of temozolomide and radiotherapy compared with radiotherapy alone in newly diagnosed glioblastoma multiforme. J Clin Oncol. 2005 Apr 1;23(10):2372-7. PMID: 15800329 [PubMed - indexed for MEDLINE]

Transcript

  • 1. Evidence-Based Prognostication April 2010 Christian Sinclair, MD
  • 2. Contributors
    • Michelle Affield, MD
      • Fellow, Univ of Kansas – Hem/Onc FellowKansas City Hospice & Palliative Care, Kansas City, MO
    • Michael Salacz, MD
      • Saint Luke’s Hospital, Kansas City, MO
      • Assistant Professor, University of Missouri, Kansas City, MO
      • msalacz@saint-lukes.org
    • Christian Sinclair, MD
      • Assoc Fellowship Director & Assoc. Med. Dir., Kansas City Hospice & Palliative Care, KC, MO
      • Medical Director, Palliative Care Team, Providence Medical Center, Kansas City, KS
      • [email_address]
  • 3. Prognosis Links
    • www.pallimed.org
    • http://www.pallimed.org/2007/05/prognosis-links.html
  • 4. Overview
    • Define the benefits and limitations of open frequent prognostication
    • Understand theories for accurate formulation of prognostication
    • Apply prognostic information to clinical scenarios
    • Discover tools for more accurate prognostication
  • 5. Medical Triad Diagnosis Prognosis Therapy
  • 6. A prognosis is an estimation of possible future outcomes of a treatment or a disease process…
  • 7. What is Prognostication?
    • It is not…
      • Fortune Telling
      • Playing God
      • Precognition
      • Divination
  • 8. … founded upon a combination of personal experience, statistics, and validated models
  • 9. Medical Prognostication
    • Role for prognostication
      • Clinical implications
      • Relationship implications
      • Symbolic implications
      • Contextual issues
      • Administrative issues
      • Cost-benefit analysis
      • Futility/bioethics
    • Christakis, Death Foretold
    Christakis Death Foretold 1999 Ethics Policy Research Academics Clinical Prognosis
  • 10. Two Parts to Prognostication
    • Formulation (Foreseeing)
      • Anticipated vs. true
    • Communication (Foretelling)
      • Compassionate
      • To the patient
      • As much as they want to hear
      • Many articles about “Breaking bad news”
  • 11. Theory for Prognostic Model Clinical Findings Individual Prognosis General Prognosis Diagnosis Pathological Findings Psychosocial Factors Co-morbidities Therapy Adapted from Vigano 2000
  • 12. Print separately with above
    • Advantages
    • Flexible
    • Incorporates multiple variables
    • May be aided by models
    • Immediate access
    • Ease of communication
    • ? accuracy vs. modeling
    Clinician’s Prognosis Validated Models
    • Disadvantages
    • ? Accuracy
    • ? Frequency
    • “ Gut feeling”
    • Open to multiple biases
      • Recall bias
      • Anchoring bias
    • Less oversight
    • Difficulty in communication
    • Advantages
    • Greater accuracy
    • Ability to evaluate efficacy
    • More objective
    • Can compare similar cases
    • Disadvantages
    • ? Accuracy to your case
    • ? Applies to groups not individuals
    • Models the past
    • Time lag
    • Not integrated
    • Different biases
  • 13. Error
    • Is the error random?
    • Does a measurable bias exist?
    • In what direction does a bias exist?
    • What is the magnitude of the error?
      • Few studies
        • MD’s are frequently and largely inaccurate
        • But lack describing a source of the error
  • 14. Life Expectancy - 1900
    • 47.3 years (both sexes, all races)
    • Caucasian:
    • All Male Female
      • 47.6 46.6 48.7
    • African-American:
    • All Male Female
    • 33.0 32.5 33.5
    National Center for Health Statistics
  • 15. NHPCO Guideline Study Fox 1999
  • 16. NHPCO Guideline Study Fox 1999 Narrow Inclusion Criteria, n=19 Broad Inclusion Criteria, n=923 Intermediate Inclusion Criteria, n=300 Survived to Hospital Discharge, n=2607
  • 17. Comparison of SUPPORT and MD survival estimates
  • 18. General Findings
    • Repeated estimates may be more accurate
    • Possibly more accurate as death is near
    • Clinician experience may increase accuracy
    • Discipline/specialty may not matter
    • Second opinion effect
  • 19. Prognostic Scales/Tools
    • Palliative Prognostic (PaP) Score
    • Palliative Performance Scale
    • Palliative Prognostic Index
    • Terminal Cancer Prognostic Score
    • Poor Prognostic Indicator
    • Charlson Co-morbidity Index
  • 20. Palliative Prognostic Score
    • Developed in Italy
    • Validated in cancer patients
      • Outpatient and inpatient
    • Used for short-term survival
    Pirovano 1999
  • 21. Palliative Prognostic Score Pirovano 1999, Glare 2004
  • 22. Palliative Performance Scale
    • Quick classification for functional status
    • Based off Karnofsky
    • Used widely in the Hospice & Palliative Care literature/field
  • 23. Image from http://www.victoriahospice.org/pdfs/PPSv2.pdf
  • 24. PPS in Heterogeneous Population Harold 2005
  • 25. PPS in Heterogeneous Population Harold 2005
  • 26. PPS in Heterogeneous Population Harold 2005 Cancer = Black Non-Cancer = Gray
  • 27. PPS in Prognostication Lau 2006 PPS Mean Median Range 60 64 40 6-348 50 51 27 1-287 40 36 17 1-347 30 18 9 1-295 20 6 2 1-81 10 2 1 1-12
  • 28. Palliative Prognostic Index Morita 2001
  • 29. Terminal Cancer Prognostic (TCP) Yun 2001
  • 30. The Future of Prognostication
    • Seattle Heart Failure Model
    • Adjuvant Online
    • HD Mortality Predictor
    • Perception of prognostication as a skill
  • 31. PubMed MESH Search with Limits: English, Human, Core Clinical Journals (Jan 2008) Therapy Diagnosis Prognosis
  • 32. http://depts.washington.edu/shfm/index.php
  • 33. www.adjuvantonline.com
  • 34. REFERENCE:Cohen et al. Predicting Six-Month Mortality for Patients who are on Maintenance Hemodialysis Clin J Am Soc Nephrol. 2009 Dec 3
  • 35.  
  • 36.  
  • 37. Conclusions
    • Physicians have a duty to prognosticate
      • Accurately, openly, dynamically
    • Prognostication can be scientifically based
    • Tools exist to aid clinical prognostication
    • Prognostication is a skill that can be honed
  • 38. Mortality In Liver Disease
    • Mortality thoroughly studied
    • Organ allocation for liver transplant
    • According to “sickest first”
    • Not location
    • Not waiting times
  • 39. MELD Score
    • M odel for E nd stage L iver D isease
    • 3 factors
      • Bilirubin
      • INR
      • Creatinine
    • 10 { 0.957 Ln(Scr) + 0.378 Ln(Tbil) + 1.12 Ln(INR) + 0.643 }
    • Online calculator (Mayo Clinic)
  • 40.  
  • 41. Three Month Mortality in Hospitalized Patients
    • MELD Score
    • </= 9
    • 10-19
    • 20-29
    • 20-39
    • >/= 40
    • Death Rate
    • 4%
    • 27%
    • 76%
    • 83%
    • 100%
    Kamath 2001
  • 42. Additional Prognostic Factors
    • Low serum sodium ( MELD-Na )
      •  ability to predict 3 & 6 month mortality
    • Na <126
      • independent predictor of wait-list mortality
    Biggins 2005, Ruf 2005
  • 43. Prognostic Factors in Lung Cancer
    • Staging
    • Performance status
    • Weight loss
    • Gender
    • Tumor histology
      • small cell associated with severe disease and debility
    • Suppressor oncogene mutations – p53
    • Oncogene overexpression – c-myc, K-ras, erb-B2
    NCCN Guidelines 2006
  • 44. Prognosis in Lung Cancer
    • Only 15% of all lung cancer patients are alive 5 years after diagnosis
    NCCN Guidelines 2006
  • 45. 5-Year Survival Non-Small Cell Lung Cancer
    • Stage IA 67%
    • Stage IB 57%
    • Stage IIA 55%
    • Stage IIB 38-39%
    • Stage IIIA 23-25%
    • Stage IIIB 3-7%
    • Stage IV 1%
    NCCN Guidelines 2006
  • 46. Survival In Small Cell Lung Cancer
    • Limited Stage
      • Median Survival 15-18 months
      • 2-Year Survival 30-40%
      • 5-Year Survival 10-15%
    • Extensive Stage
      • Median Survival 9-10 months
      • 2-Year Survival < 10%
      • 5-Year Survival rarely reported
    Jahan 2002
  • 47. Malignant Pleural Effusion
    • Indicative of poor prognosis
      • Especially poor if secondary to:
        • GI, lung, or ovarian
    • Survival
      • Average Range 3-6 months
      • Median 4 months
      • 65% mortality in 3 months
      • 80% mortality in 6 months
    Sahn 2001
  • 48. Glioma (Astrocytoma) Survival
    • Glioblastoma = 50% of all gliomas
    Tumor Type 5-Yr (%) 10-Yr (%) Median (y) Pliocytic (1) 91 89 Diffuse (2) 47 39 5 Anaplastic (3) 29 22 2-3 Glioblastoma (4) 3 2 1
  • 49. Results EORTC Greek RT RT+TMZ RT RT+TMZ Median Survival 12.1m 14.6m 7.7m 13.4m % 12m Survival 50% 61% 16% 56% % 18m Survival 21% 39% 5% 25%
  • 50. Median Survival
    • Class III
      • 17 months
      • 32% at 2 yr
    • Class IV
      • 15 months
      • 19% at 2 yr
    • Class V
      • 10 months
      • 11% at 2 yr
    Mirimanoff 2006
  • 51. Brain Metastases Survival Treatment Survival No primary treatment 1 month Steroids 2-3 months Whole Brian Radiation 3-6 months Surgery/SRS 6-12 months
  • 52. Brain Mets Prognosis
    • Median Survival
      • Group 1
        • 7.1 months
      • Group 2
        • 4.2 months
      • Group 3
        • 2.3 months
    Gaspar 1997
  • 53. Prostate Cancer
    • Gleason Score
    • PSA Level
    American Cancer Society, www.cancerresearch.uk Stage Description 5-Yr Survival 1 Small local 98% 2 Large local 65% 3 Outside prostate 60% 4 Bladder, bone or LN 30% (mean 2y)
  • 54. 5-Year Cancer Survival Rates ACS 2007 Guidelines   All Stages Local Reg Distant   % % % % Breast 89 98 83 26 Colon 64 90 68 10 Esophagus 16 34 17 3 Kidney 66 90 62 10 Larynx 64 84 50 14 Liver 11 22 7 3 Lung 15 49 16 2 Melanoma 92 99 65 15 Oropharynx 59 81 52 26   All Stages Local Reg Distant   % % % % Ovary 45 93 69 30 Pancreas 5 20 8 2 Prostate 99.9 100 -- 33 Stomach 24 62 22 3 Testis 96 99.5 96 70 Thyroid 97 99.7 97 56 Bladder 81 94 46 6 Cervix 72 92 56 15 Uterine 83 96 67 23
  • 55. Amyotrophic Lateral Sclerosis
    • NHPCO guidelines available (not validated)
    • Event based decline model
      • Loss of Ambulation
      • Lower vital capacity = vent support
    • Older age = higher mortality
    • Bulbar signs = higher mortality
      • Median time (Dx->death) = 20 months
    Zoccolella, S et al. 2008
  • 56. Amyotrophic Lateral Sclerosis
    • Median survival from first symptoms
      • 28 months
    • Median survival from ALS diagnosis
      • 16 months
    • 4-year survival rate 30%
    • No validated prognostic tools
    Zoccolella, S et al. 2008
  • 57. Trauma
    • Multiple prognostic tools
      • Traumatic Brain Injury – Online
        • http://www.crash2.lshtm.ac.uk/Risk%20calculator/index.html
        • Risk of 14 d mortality and unfavorable 6 month outcome
        • Based on:
          • Country
          • Age
          • GCS
          • Pupils
          • Extracranial injury
          • CT Scan findings
    MRC CRASH Trial Collaborators, 2008
  • 58. Predicting Death From Debility
    • No easy method
    • International Classification of Functioning, Disability and Health
      • Body Functions & Structures
      • Activities and Participation
      • Environmental Factors
      • Personal Factors
    • Palliative Performance Scale
    Kinzbrunner 1996
  • 59. Congestive Heart Failure
    • 2 Prognostic Tools available
      • EFFECT
      • Seattle Heart Failure Model
    • NHPCO Criteria Available
    • Event based prediction models
    • Sudden death/arrythmias confound most predictions
  • 60. Predicting Outcome From Hypoxic-Ischemic Coma
    • First comprehensive multivariate approach
    • Newly constructed, empirically derived guidelines
    • First few days after a cardiac arrest or similar global hypoxic-ischemic insult
    • Good vs. poor outcome
    Levy 1985
  • 61. Signs Related to ± Recovery
    • 0/52 patients initially lacking pupillary reflex ever became independent
    • At 3 days
      • absent or posturing motor responses were incompatible with future independence
    • At initial exam
      • most favorable sign - incomprehensible speech
    Levy 1985
  • 62. Hypoxic-Ischemic Coma
    • At day 1:
      • Confused or inappropriate speech
      • Orienting spontaneous eye movements
      • Normal OC or OV responses
      • Obedience to commands
    • Each of the above associated with at least 50% chance of gaining independence
    Levy 1985
  • 63. Variables Predicting Poor Outcome
    • 100% specific in all studies (no good outcome if factors were present)
      • Absence of pupillary light reflex on the day 3
      • Absence of motor response to pain on the day 3
      • Bilateral absence of cortical response to median nerve SSEP (somatosensory evoked potential) < 1 week
    • One variable was 100% specific in 5/6 studies
      • Burst-suppression or iso-electric pattern on EEG
      • within the first week
    Zandbergen 1998
  • 64. Cardiac Arrest As Cause of Coma
    • Survival for pre-hospital cardiac arrest
      • 2 to 33%
    • Survival for inpatient cardiac arrest
      • 0 to 29%
    • Meaningful neurological recovery
      • 10-30%
    Booth 2004
  • 65. Hypoxic-Ischemic Coma Post-Cardiac Arrest
    • 11 studies
    • 1914 patients
    • Determine precision and accuracy of the clinical exam
    • Poor neurological outcome was 77%
    Booth 2004
  • 66. Hypoxic-Ischemic Coma Post-Cardiac Arrest
    • No clinical findings
      • Strongly predicted good neurological outcome
    • No pupillary or corneal reflex at 24 hours and no motor response at 72 hours
      • extremely small chance of neurologic recovery
    • No clinical signs immediately after cardiac arrest accurately predicted outcome
    Booth 2004
  • 67. Poor Prognostic Factors In Severe Stroke
    • Most powerful predictors of death and poor outcome
      • Persistent coma
      • Absent pupillary or corneal reflexes at day 2 or 3
    • Further variables associated with poor outcome
      • Co-morbidities
      • Midline shift
      • Fever
    • Poor outcome specifically in hemorrhagic stroke
      • Volume of blood and intraventricular hemorrhage
      • Hydrocephalus
      • Hypertension
    Holloway 2005
  • 68. Favorable Prognostic Factors In Severe Stroke
    • More favorable outcome (both types)
      • Intubation for seizure or pulmonary reason
      • Younger age
      • Minimal co-morbidities
      • Spouse at home
      • Early neurological recovery
      • Lower body temp
    Holloway 2005
  • 69. PEG Tube
    • In patients with stroke who required PEG tube
      • 6 month mortality is nearly 50%
      • Mortality increases to 80% by 3 years
      • 78% who survived to 6 months had severe disability
    Holloway 2005
  • 70. Tracheostomy
    • Of patients who required tracheostomy and survived 1 year:
      • 18% had minimal or no disability
      • 26% had moderate disability
      • 56% had severe disability
    Holloway 2005
  • 71. Stroke Syndromes Associated With Poor Outcome
    • Higher mortality
      • Pontine hemorrhage with hyperthermia
      • Basilar artery occlusion with coma and apnea
    • Severe disability
      • Large MCA infarcts
      • Pontine strokes resulting in locked-in syndrome
    Holloway 2005
  • 72. Dementia
    • No statistical correlation:
        • Between guidelines or components and 6 month survival
    • Statistically significant:
      • Greater age
      • Greater functional impairment
      • Anorexia
    Schonwetter 2003, Mitchell 2004
  • 73. Dementia – MDS-12
    • ADL > 28 = 1.9
    • Male =1.9
    • Cancer = 1.7
    • O 2 in last 14d = 1.6
    • CHF =1.6
    • SOA = 1.5
    • Total score = 0-19
    • <25% meals = 1.5
    • Unstable med cond = 1.5
    • Bowel incont = 1.5
    • Bedfast = 1.5
    • 83yo+ = 1.4
    • Asleep >50% = 1.4
    Mitchell 2004
  • 74. Dementia - MDS-12 AUROC for >6 (0.64) was better than FAST 7c (0.51) Mitchell 2004 Total Risk Score Mortality Estimate @ 6m 0 9% 1-2 10% 3-5 23% 6-8 40% 9-11 57% >12 70%
  • 75. Delirium
    • 109/393 (28%) palliative care patients
    • Confusion Assessment Method (CAM)
    • Median survival (95%CI)
      • Delirium – 21d (16-27)
      • No Delirium – 39d (33-49)
    • 70% accuracy for 30d survival
      • Delirium + PaP
    Caraceni 2000
  • 76. ICU Admission With COPD
    • COPD
      • 61% required invasive mechanical ventilation
      • Expected hospital mortality – 30%
      • Actual hospital mortality – 15%
      • APACHE-II and # of organ failures
        • Independent predictors of hospital outcome
    Afessa 2002
  • 77. Mechanical Ventilation
    • 902 ICU Vent patients
    • Young vs. old (70y cut-off)
      • 28d survival rate
      • < 70yo – 75%
      • >70 yo – 50%
    Ely 2002
  • 78. Delirium & Ventilation
    • Mechanical ventilation
      • Higher 6-month mortality rates
        • 34% vs. 15%, P =.03
        • Spent 10 days longer in the hospital (P<.001)
    Ely 2004
  • 79. Ventilator Withdrawal
    • 75 heterogeneous ventilated patients
    • Median survival (range)
      • 35 min (1-890min)
    • Average meds
      • 16 mg/h opioid
      • 7.5 mg/h benzodiazepine
    • Every 1mg increase in benzo…
      • 13 min longer survival (p=0.015)
    Chan 2004
  • 80. Tracheostomy
    • 521 patients in ICU requiring mech vent
    • 51 (10%) received trach
    • Mortality less with trach
      • 14% vs. 27% (p=0.48)
    • Longer vent and hospitalization
    • 44 survivors of hospital
      • 86% alive 30d post hospital
    Kollef 1999
  • 81. Chronic Kidney Disease
    • Stage 5 (<15mL/min)
      • 1 year survival – 80% (>65y = 65%)
      • 2 year survival – 65%
      • 5 year survival – 38%
    • Multiple independent predictors
      • Albumin
      • Functional status
    Beddhu 2000
  • 82. Acute Renal Failure/HD Withdrawal
    • In the ICU
      • Mortality 50-65%
    • Septic
      • Mortality – 75%
    • Bone Marrow Transplant
      • Mortality – 85%
    • Range 1-20d
      • Mean 8d
    Cohen 2006
  • 83. Artificial Nutrition & Hydration
    • Improved survival
      • PVS
      • Extreme short-bowel syndrome
      • Bulbar amyotrophic lateral sclerosis.
      • Acute phase of a stroke or head injury
      • Patients receiving short-term critical care
    • Observational data lacking on survival after W/D of artificial nutrition and/or hydration
    Casarett 2005
  • 84. Opioid Use
    • National Hospice Outcomes Project
      • PoPCRN coordinated study
    • 13 hospices, 1300+ patients
    • Significant association with shorter survival:
        • Higher opioid dose
        • Cancer diagnosis
        • Unresponsiveness
        • Pain of <5 on a 0-10 scale
    Portenoy 2006
  • 85. Opioid Use
    • But….
      • None of them explained more than 10% of the variation
    Portenoy 2006
  • 86. Recommended Readings
    • Death Foretold: Prophecy and Prognosis in Medical Care by Nicholas A. Christakis
    • The Terminal Phase, Chapter 18. Oxford Textbook of Palliative Medicine , 3 rd ed. 2004
    • Predicting survival in patients with advanced disease, Chapter 2.4. Oxford Textbook of Palliative Medicine , 3 rd ed. 2004
    • Storm Watchers by John D. Cox
    • Stone P, Lund S. Predicting prognosis in patietns with advanced cancer . Ann Oncol 2006.
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