Displaying 11-20 letters out of 217 published
is it showing the exact picture of igA nephropathy?
I want to highlight few points about the study.First, IgA nephropathy is seen in nearly 40% of renal biopsy specimens of acute glomerulonephritis patients in asia in various study.In this study it is comprising only 8.1% of cases.Second, it is an crossectional study, taking data from the renal biopsy report thus not showing the exact % of acute glomerulonephritis caused by IgA nephropathy.So the finding is quite exaggerated, though 10% of IgA nephropathy patient develop ESRD after 10 year & 20% after 20 years.
Conflict of Interest:
Lifestyle modification is still the main strategy to raise HDL-C
Management of special type of dyslipidemia; Low HDL-C, high TG, Type- B size LDL-P in patients with T2DM is a big challenge for a physician. For primary LDL-C goal, we the physician usually go for stronger statins like atorvastatin or rosuvastatin. Addition of fenofibrate to the above statins to reduce concomitant high TG really reduces TG level but does such combination offer any strong role in reducing mortality in this population ? To increase HDL-C, trials with CETP inhibitors like torcetrapib or anacetrapib failed to reduce CV mortality. Newer CETP inhibitor evacetrapib although leading to increase HDL-C but cardiovascular protection is still under question . We were using extended release nicotinic acid along with statin (ARBITER 6 -HALTS trial) but my practice did not show any significant benefit. Recently, after premature halting of AIM-HIGH trial, efficacy of nicotinic acid also became under question and even increased events of ischemic stroke in this population leading me to change my treatment strategy. Currently no safe drug to increase HDL-C is available. More ever, drug induced increased HDL has no CV benefit. Lifestyle modification is still remaining the best strategy along with statin and if necessary, n-3 to manage dyslipidemia in patients with diabetes and other high risk population.
Ref: 1. Hyperlipidaemia and cardiovascular disease: do fibrates have a role? Current Opinion in Lipidology: August 2011 - Volume 22 - Issue 4 - p 270-276 doi: 10.1097/MOL.0b013e32834701c3 2. Effects of the CETP Inhibitor Evacetrapib Administered as Monotherapy or in Combination With Statins on HDL and LDL Cholesterol. JAMA.2011;306(19):2099-2109. doi:10.1001/jama.2011.1649
Conflict of Interest:
Leadership education in medicine and science
Kouzes and Posner (1) once wrote that "The domain of leaders is the future. The leaders unique legacy is the creation of valued institutions that survive over time. The most significant contribution leaders make is not simply to today's bottom line; it is to the long-term development of people and institutions so they can adapt, change, prosper, and grow."
As Warren and Carnall (2) stated, medical leadership is important for delivering high-quality healthcare to patients and to function across professional boundaries in an environment that is becoming increasingly complex. Physicians are well educated academically and clinically, but training in leadership lags somewhat behind. There also appears to be a gap in leadership capabilities between junior and senior doctors. The authors suggest several approaches to develop the non-technical, often called "softer" skills in physicians, including mentoring by establishing a relationship that will support personal and professional development, coaching to enhance the performance in specific areas, and action learning to solve jointly "real-world" problems that arise at work. There is also formal and informal networking with peers and/or senior leaders, and experiential learning through exposure to new environments, assignments, etc., which trains the individual to work outside their comfort zone. The authors also discuss participation in specific programs, schemes, fellowships, and courses aimed at developing medical leadership skills.
As a scientist, I found myself in a similar situation as many physicians: I did not receive any kind of training in management and leadership during my education. Yet, after graduation with a Ph.D. in microbiology, I was expected to lead a research laboratory, instruct students in the classroom and guide them through their thesis experience, and to professionally interact with administrative staff of the organization as well as representatives of research funding agencies. So, how did I do it? I essentially studied the way how others (e.g., mentors, senior peers, and selected role models from the literature) lead people, then "copied" certain leadership behaviors, and put a "personal touch" on my leadership attempts. I used the principle of "trial and error." Not surprisingly, it did not take me long to realize that this way of leading was a superficial attempt to be effective and to "survive" in the highly competitive field of biomedical science. Most significantly, I lacked authenticity and did not know the tools needed for self-observation and self-discovery. As it turned out, I was not alone in my leadership insecurities as several of my young colleagues expressed similar soft- skill deficiencies.
Since the science curriculum (apparently similar to the medical curriculum) does not include management and leadership courses, I eventually decided to enroll in business graduate programs to formally study this subject matter. I was surprised how much I learned from books and articles, group discussions, and case studies about interpersonal and intercultural communication, management techniques, theories and elements of leadership practice, strategic thinking approaches, ethics in action, and organizational behavior, among many other topics. I realized that what I have learned in business school I could immediately apply to many aspects of my work in science. I greatly improved my understanding of leadership and, I believe, it also made me a more attentive person in private life. I know now that leadership is a process, which means a transactional event that occurs between the leader and followers (3), thus it is a collective activity (4), and undoubtedly a real challenge worth taking on (1). Leadership is a universal phenomenon, it is real and not a figment of the imagination, and it has a substantial effect on organizational outcomes (5). Providing good leadership requires a willingness for continuing learning (6), an understanding of the importance of effective and efficient listening to others (7), and the capability and opportunity for deep introspection and self-reflection (8, 9). One must understand that developing and refining leadership skills takes time and requires from the individual passion, commitment, and endurance.
In hindsight, I wish that I would have taken management and leadership courses much earlier in my scientific career. In this regard, I strongly support the notion that leadership training should become a part of medical and science education. I believe that resources dedicated to leadership education would pay off immediately during the time students spend in medical and graduate school as well as prepare them well for every stage of their professional life. Last, but not least, leadership training can have positive effects on the development of one's personal life.
I would like to conclude my letter with another citation from the book by Kouzes and Posner (1): "Leadership is important not just in your own career and within your own organization. It's important in every sector, in every community, and in every country. We need more exemplary leaders, and we need them more than ever. There is so much extraordinary work to be done. We need leaders who can unite us and ignite us."
1. Kouzes MJ, Posner BZ. The Leadership Challenge. 3rd edn. San Francisco, California: Jossey-Bass, 2002.
2. Warren OJ, Carnall R. Medical leadership: why it's important, what is required, and how we develop it. Postgrad Med J 2011;87:27-32.
3. Northouse PG. Leadership: Theory And Practice. 4th edn. Thousand Oaks, California: Sage Publications, 2007.
4. Noonan SJ. The Elements Of Leadership: What You Should Know. Lanham, Maryland: Scarecrow Press, 2003.
5. Bass BM, Bass R. The Bass Handbook Of Leadership: Theory, Research, And Managerial Applications. 4th edn. New York: Free Press, 2008.
6. Preskill S, Brookfield SD. Learning As A Way Of Leading: Lessons From The Struggle For Social Justice. San Francisco, California: Jossey- Bass, 2009.
7. Treece M. Successful Communication For Business And The Professions. 6th edn. Needham Heights, Massachusetts: Allyn and Bacon, 1994.
8. Cashman K. Leadership From The Inside Out: Becoming A Leader For Life. Provo, Utah: Executive Excellence Publishing, 1998.
9. Palmer PJ. Let Your Life Speak: Listening For The Voice Of Vocation. San Francisco, California: Jossey-Bass, 2000.
Conflict of Interest:
Reply to Reply In reply to De Wets and Bowie's reply to my criticism:
De Wet and Bowie state 1. Our paper makes it very clear that this is a study of primary care records and not of consultations, GPs or of primary care per se.
Reply Although this is true, nowhere does the paper explicitly explain that is looking in primary records for errors across the totality of healthcare. This is not mentioned until page 179 (4th page of article) and then only in passing. The clear assumption is that this is a study of primary care records and is looking for error and harm in primary care and this impression is not overtly refuted in the article.
De Wet and Bowie state 3. The harm rate per number of records and consultations is provided to make the results more meaningful for primary care clinicians who have multiple patient contacts.
Reply No primary care clinician I have spoken to thinks including secondary care events makes the results more meaningful to primary care clinicians. Primary care clinicians want to know what their own error/harm rate is. They do not want secondary care error/harm rates added to their own figures and inflating the 'primary care' error/harm rate.
De Wet and Bowie state 4. Johnstone suggests the harm rate should be expressed as '...47 per 2251 consultations (2.1%)...' We provided this measure i.e. 1 per 48 consultations (a ratio that equates to 2.1%). We could calculate at least six different measures involving the following variables: error, harm, preventability, setting, record and consultation. All provide useful but limited information, none is superior. We focused on harm per record because that is what we judged as most relevant to patient safety.
Reply I have no problem with this, but it must be made explicit and this is not the case in this paper. The paper does not explicitly state that secondary care errors are being included. Spinal surgery errors are mentioned in passing and on page 179 the paper mentions 'procedures in secondary care.' The paper continually mentions primary care, using the tool to provide a 'primary care equivalent'. On page 2 the paper's aims are to 'test a validated trigger tool for the primary-car setting'. It does not mention a secondary care setting. This lack of clarity invalidates this paper.
De Wet and Bowie state 5. We detected harm that originated in secondary care, which concurs with previous research. (4) We discuss the implications of this and that most 'severe' cases originated in this setting. We do not state that the harm rate of 9.4% is "for" primary care but make it clear that it is the harm rate found in the records, regardless of source of origin or preventability judgements.
Reply Although De Wet and Bowie mention secondary care once in the discussion section on page 179, the rest of the paper talks about harm and error in primary care. The whole paper is about using the trigger tool to detect and quantify error and harm in primary care, not in secondary care.
De Wet and Bowie state 6. Definitions of error and adverse event are outlined in our Methods section. Careful reading of Tables 3 and 4 shows that matching study data are presented for each category using the NCCMERP Error Index employed (which defines near misses, error and harm). We use harm and adverse event interchangeably, which is accepted practice. (5)(6)(7)
Reply I accept this, but harm is regularly used when error should be used. This occurs in the titles of tables 3 and 4. The NCCMERP tool detects error, not just harm, not all errors lead to harm and not all harm is due to error. This suggestsharm is more common than it is. On page 179 is the sentence Most cases of harm were graded as category A-E (temporary harm to a patient requiring an intervention). This is inaccurate as only category E is harm, categories A-D are errors with the potential for harm, but with no actual harm occurring.
De Wet and Bowie state 7. The NCCMERP index was selected in the absence of a universally agreed system and because it is used in hospital care. We did not adapt it to reduce bias. We provide a rationale: "In secondary-care studies, only categories E to I have been used, as they correlate with actual patient harm occurring. We included all categories because we assumed that relatively minor events may be more common in primary care". This assumption was proved correct. We also made the following recommendation: "It may be reasonable to use only categories E to I in future to target patient harm rather than just error".
Reply De Wet and Bowie have misread their own paper, on page 180 they state ' Few adverse events were in categories A-D despite the expectation of high error incidence.' Their assumption was proven wrong not correct.
De Wet and Bowie state 8. Johnstone states that he "almost believes" that we "confuse" these terms "on purpose". This comment is lacking in reason and evidence.
De Wet and Bowie state 10. Johnstone queries the category E harm example in Table 2 (refer also to our No. 6 and 7 responses). Some harm events may arise from normal or evidence-based care. There may be no associated error (as in this example) or obvious error. To illustrate: a patient is appropriately prescribed an antibiotic but develops an allergic reaction. Record review reveals a similar prescription and outcome previously, but no allergy code was added. Arguably, this is preventable harm.(9)
Reply I agree, the second prescription is preventable harm, the first prescription is unavoidable harm.
De Wet and Bowie state 11. Johnstone is factually incorrect in stating that of "...the 47 events in primary care, 11 were in the range of possible harm rather than actual harm". 47 records contained evidence of some harm i.e. categories E (n=39), F (n=6) and G (n=2). We cannot make this clearer.
reply Yet again De Wet and Bowie have misread their own paper and confused primary and secondary care. There are 47 events in primary care and 11 are the category A-D, therefore possible harm not actual harm. Co-incidentally the number of events in categories E-G is also 47, but 11 of these occurred in secondary care.
De Wet and Bowie state 12. Johnstone states that we make a "throwaway comment" in the opening paragraph because we suggest that the evidence cited is "...likely to be an underestimation". Based on the evidence in hospital care (10), we hypothesised that the rate in primary care is greater than currently suggested, which is standard research practice. Our findings support our hypothesis.
Reply I disagree, De Wet and Bowie's findings show that preventable harm in primary care is 1:125 consultations, almost identical to 1:120 consultations which they thought was an underestimation.
De Wet and Bowie state 14. The issue over the "headline figure" being "inflated" from 9.4% to 9.5% (it was rounded to the nearest 0.5%) is external to the debate on the published paper.
Reply Point taken, I will follow this up separately.
De Wet and Bowie state 17. We did not exclude the records of the 94 patients (18.8%) who had no contact with primary care in the 12-month study period. If we now exclude them (which is reasonable), the actual harm rate is 47/406 (11.6%), strongly suggesting we underestimated the 'true' level.
Reply The rate of preventable harm in 1:125 consultations is unaffected whether the these 94 patients are included or excluded.
De Wet and Bowie state 18. We concede that our Abstract should read "...27/64 (42%) of error and harm events were judged preventable..." However, this issue is reported clearly in the main paper.
De Wet and Bowie state 19. We cannot control how others interpret our findings and are always careful to explain the scientific limitations of our study.
Reply Fair point, but the authors can control how the authors interpret and explain their study. This is not directly related to retracting this paper but on 10th June Bowie gave a power-point presentation titled 'Patient Safety and the GPST' . The presentation states 'The NES Trigger Tool... may enable you to measure the preventable harm rate.. which you can monitor and reduce overtime.' Although they include secondary events, it is hard for primary care clinicians to reduce errors in secondary care, eg pain after a spinal operation. Had De Wet and Bowie applied this sentence to their own paper, they would have reported the preventable harm rate in primary care as 0.8% not 9.4%
De Wet and Bowie state Screening medical records for undetected harm events only provides a single perspective. The process cannot capture 'acts of omission' that lead to harm nor are findings likely to correlate with data from patients, incident reporting systems, significant event analyses, complaints, litigation claims and so on. (11)(12)(13) The patient safety problem is highly likely to be greater than can be deduced from screening medical records, even when we account for source of origin and preventability judgements.
Reply I agree that Patient Safety is a major issue and should be taken immensely seriously. However I do not believe it helps anyone to portray the problem as greater than it is. I believe this paper has inaccuracies and gives the impression of a 9.4% harm rate in primary care when the actual figure could be better described as preventable harm occurs in 1:125 consultations in primary care (0.8%).
Conflict of Interest:
Thank you for the opportunity to respond to Dr Chris Johnstone's comments on our 2009 publication.(1)
1. Our paper makes it very clear that this is a study of primary care records and not of consultations, GPs or of primary care per se.
2. There is no "common method of measuring rates of harm" in primary care (2) as Johnstone states. We refer to research on medical error and the consultation (3) in our Introduction to demonstrate evidence of a 'problem', not to indicate our intended data analysis method.
3. The harm rate per number of records and consultations is provided to make the results more meaningful for primary care clinicians who have multiple patient contacts.
4. Johnstone suggests the harm rate should be expressed as '...47 per 2251 consultations (2.1%)...' We provided this measure i.e. 1 per 48 consultations (a ratio that equates to 2.1%). We could calculate at least six different measures involving the following variables: error, harm, preventability, setting, record and consultation. All provide useful but limited information, none is superior. We focused on harm per record because that is what we judged as most relevant to patient safety.
5. We detected harm that originated in secondary care, which concurs with previous research. (4) We discuss the implications of this and that most 'severe' cases originated in this setting. We do not state that the harm rate of 9.4% is "for" primary care but make it clear that it is the harm rate found in the records, regardless of source of origin or preventability judgements.
6. Definitions of error and adverse event are outlined in our Methods section. Careful reading of Tables 3 and 4 shows that matching study data are presented for each category using the NCCMERP Error Index employed (which defines near misses, error and harm). We use harm and adverse event interchangeably, which is accepted practice. (5)(6)(7)
7. The NCCMERP index was selected in the absence of a universally agreed system and because it is used in hospital care. We did not adapt it to reduce bias. We provide a rationale: "In secondary-care studies, only categories E to I have been used, as they correlate with actual patient harm occurring. We included all categories because we assumed that relatively minor events may be more common in primary care". This assumption was proved correct. We also made the following recommendation: "It may be reasonable to use only categories E to I in future to target patient harm rather than just error".
8. Johnstone states that he "almost believes" that we "confuse" these terms "on purpose". This comment is lacking in reason and evidence.
9. Johnstone states that because most 'serious' harm originated in secondary care he believes this is "Hardly a major problem for primary care". There are over 300 million consultations annually in UK primary care. (8) A hypothetical harm rate between 0.1% and 5% (even if only half was preventable and most low impact) is of concern to patients, clinicians and the public.
10. Johnstone queries the category E harm example in Table 2 (refer also to our No. 6 and 7 responses). Some harm events may arise from normal or evidence-based care. There may be no associated error (as in this example) or obvious error. To illustrate: a patient is appropriately prescribed an antibiotic but develops an allergic reaction. Record review reveals a similar prescription and outcome previously, but no allergy code was added. Arguably, this is preventable harm.(9)
11. Johnstone is factually incorrect in stating that of "...the 47 events in primary care, 11 were in the range of possible harm rather than actual harm". 47 records contained evidence of some harm i.e. categories E (n=39), F (n=6) and G (n=2). We cannot make this clearer.
12. Johnstone states that we make a "throwaway comment" in the opening paragraph because we suggest that the evidence cited is "...likely to be an underestimation". Based on the evidence in hospital care (10), we hypothesised that the rate in primary care is greater than currently suggested, which is standard research practice. Our findings support our hypothesis.
13. We have no knowledge of those "who would like to demean general practice for their own ends" or of any current or planned "...unnecessary change on GPs..." that is being "imposed" because of our small preliminary study. It is not an academic matter.
14. The issue over the "headline figure" being "inflated" from 9.4% to 9.5% (it was rounded to the nearest 0.5%) is external to the debate on the published paper.
15. At no point is it inferred, directly or indirectly, "...how awful GPs are..."
16. Johnstone accuses us of having an "agenda" to "...inflate harm in general practice" when we (and the six other clinical reviewers) only ever reported harm in the medical records. No evidence to support this statement is offered.
17. We did not exclude the records of the 94 patients (18.8%) who had no contact with primary care in the 12-month study period. If we now exclude them (which is reasonable), the actual harm rate is 47/406 (11.6%), strongly suggesting we underestimated the 'true' level.
18. We concede that our Abstract should read "...27/64 (42%) of error and harm events were judged preventable..." However, this issue is reported clearly in the main paper.
19. We cannot control how others interpret our findings and are always careful to explain the scientific limitations of our study.
Screening medical records for undetected harm events only provides a single perspective. The process cannot capture 'acts of omission' that lead to harm nor are findings likely to correlate with data from patients, incident reporting systems, significant event analyses, complaints, litigation claims and so on. (11)(12)(13) The patient safety problem is highly likely to be greater than can be deduced from screening medical records, even when we account for source of origin and preventability judgements.
Carl de Wet MBChB MRCGP MMed (Fam)
Paul Bowie PhD
(1) de Wet C, Bowie P. The preliminary development and testing of a global trigger tool to detect error and patient harm in primary-care records. Postgrad Med J 2009 Apr;85(1002):176-180.
(2) Wetzels R, Wolters R, van Weel C, et al. Mix of methods is needed to identify adverse events in general practice: a prospective observational study. BMC Fam Pract 2008;9:35.
(3) Sandars J, Esmail A. The frequency and nature of medical error in primary care: understanding the diversity across studies. Fam Pract 2003 Jun;20(3):231-236.
(4) Forster AJ, Murff HJ, Peterson JF, et al. The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med 2003 Feb 4;138(3):161-167.
(5) Elder NC, Pallerla H, Regan S. What do family physicians consider an error? A comparison of definitions and physician perception. BMC Fam Pract 2006;7:73.
(6) Grober ED, Bohnen JM. Defining medical error. Can J Surg 2005 Feb;48(1):39-44.
(7) Yu KH, Nation RL, Dooley MJ. Multiplicity of medication safety terms, definitions and functional meanings: when is enough enough?. Qual Saf Health Care 2005 Oct;14(5):358-363.
(8) Department of Health. Departmental Report 2008. Department of Health: 2008.
(9) Gurwitz JH, Field TS, Harrold LR, et al. Incidence and preventability of adverse drug events among older persons in the ambulatory setting. JAMA 2003 Mar 5;289(9):1107-1116.
(10) Landrigan CP, Parry GJ, Bones CB, et al. Temporal trends in rates of patient harm resulting from medical care. N Engl J Med 2010 Nov 25;363(22):2124-2134.
(11) Kuzel AJ, Woolf SH, Gilchrist VJ, et al. Patient reports of preventable problems and harms in primary health care. Ann Fam Med 2004 Jul-Aug;2(4):333-340.
(12) Thomas EJ, Petersen LA. Measuring errors and adverse events in health care. J Gen Intern Med 2003 Jan;18(1):61-67.
(13) Field TS, Gurwitz JH, Harrold LR, et al. Strategies for detecting adverse drug events among older persons in the ambulatory setting. J Am Med Inform Assoc 2004 Nov-Dec;11(6):492-498.
Conflict of Interest:
Peripartum cardiomyopathy: current understanding, comprehensive management review and new developments
We read with interest a review on peripartum cardiomyopathy (PPCM) by Pyatt and Dubey (1) that has recently been published in your journal. Reviewing the epidemiology of PPCM, the authors conclude that, "PPCM appears not to have a hereditary association", and this erroneous assertion is supported by the citation of three references.(2,3,4) However, all three of the papers cited, actually emphasise the current thinking that PPCM does indeed have heretidary and/or genetic underpinnings. We have recently demonstrated in a series of South African families with familial dilated cardiomyopathy (DCM) that PPCM can present as part of the spectrum of familial DCM.(5) Similarly, in 90 Dutch families with familial DCM, van Spaendonck-Zwarts and colleagues have found that PPCM may be the initial presentation of familial DCM and identified previously undiagnosed DCM in the families of PPCM patients who did not show full recovery.(6) In the US, 45 cases of PPCM were identified from 530 pedigrees of familial DCM, and in 19 PPCM cases offered molecular genetic screening the causative mutations were isolated in 6 patients.(7) Furthermore, familial clustering was noted in 23 (55%) of the 42 unrelated cases of PPCM in this study. In an editorial titled 'Birthing the Genetics of Peripartum Cardiomyopathy' Anderson and Horne argue that "PPCM may develop as a result of a complex interaction of pregnancy associated factors against a susceptible genetic background".(8)
We have previously reviewed the role of genetics in the aetiopathogenesis of PPCM.(9) Genetic susceptibility may account for up to a third of cases of PPCM. In a series of 17 PPCM patients, Pierce and colleagues found 3 (18%) to have a definite family history of PPCM.(4) Likewise, there have been many reports of familial clustering of PPCM, (10 -13) clearly showing that the disease can have a hereditary association.
Nevertheless, while genetic susceptibility seems to play a role in the development of PPCM, the majority of cases of PPCM do not have a family history of the disease, and other environmental and biological factors have been postulated to play a role (including inflammatory, infectious, autoimmune, metabolic, hormonal and biochemical factors).(9) The high incidence of PPCM in certain communities, (14) suggests that a common genetic founder mutation cannot be excluded, however. Within populations there is scope for variable genetic susceptibility, as well as incomplete penetrance and variable expression of the causative mutations, as with other forms of DCM.(15) It is clearly the interaction of pathogenic and modifier genes with pregnancy-specific environmental, clinical and biological factors that determines the final common expression of PPCM.
The picture painted by the family and molecular studies has implications for the management of patients with PPCM. First, in every patient with PPCM, the construction of a 3- to 5-generation pedigree is essential to exclude familial DCM. Second, clinical screening of first degree relatives is required in order to exclude cases of undiagnosed familial DCM. Finally, the management of PPCM requires a multidisciplinary team of physicians, obstetricians and medical geneticists in order to achieve optimal care.
1. Pyatt JR, Dubey G. Peripartum cardiomyopathy: current understanding, comprehensive management review and new developments. Postgrad J Med 2011; 87: 34-39.
2. Pearson GD, Veille JC, Rahimtoola S, et al. Peripartum cardiomyopathy: National Heart, Lung, Blood Institute and Office of Rare Diseases (National Institutes of Health). Workshop recommendations and review. JAMA 2000; 283: 1183-1188.
3. Witlin AG, Mabie WC, Sibai BM. Peripartum cardiomyopathy: an ominous diagnosis. Am J Obstet Gynecol 1997; 176: 182-188.
4. Pierce JA, Price BD, Joyce BW. Familial occurrence of postpartal heart failure. Arch Intern Med 1963; 111: 651-655.
5. Ntusi NBA, Wonkam A, Shaboodien G, et al. Frequency and clinical genetics of familial dilated cardiomyopathy in Cape Town: Implications for the evaluation of patients with unexplained cardiomyopathy. S Afr Med J 2011; 101: 394-398.
6. van Spaendonck-Zwarts KY, van Tintelen JP, van Veldhuisen DJ, et al. Peripartum Cardiomyopathy as a Part of Familial Dilated Cardiomyopathy. Circulation 2010; 121: 2169-2175.
7. Morales A, Painter T, Li R, et al. Rare variant mutations in Pregnancy-Associated or Peripartum Cardiomyopathy. Circulation 2010; 121: 2176-2182.
8. Anderson JL, Horne BD. Birthing the Genetics of Peripartum Cardiomyopathy. Circulation 2010; 121: 2157-2159.
9. Ntusi NBA, Mayosi BM. Peripartum cardiomyopathy: a systematic review. Int J Cardiol 2009; 131: 168-179.
10. Massad LS, Reiss CK, Mutch DG, Haskel EJ. Familial peripartum cardiomyopathy after molar pregnancy. Obstet Gynecol 1993; 81: 886-888.
11. Pearl W. Familial occurrence of peripartum cardiomyopathy. Am Heart J 1995; 129: 421-422.
12. Voss EG, Reddy CV, Detrano R, et al. Familial dilated cardiomyopathy. Am J Cardiol 1984; 54: 456-457.
13. Fett JD, Sundstrom BJ, Etta King M et al. Mother-daughter peripartum cardiomyopathy. Int J Cardiol 2002; 86: 331-332.
14. Ntusi NBA, Mayosi BM. Epidemiology of heart failure in sub- Saharan Africa. Expert Rev Cardiovasc Ther 2009; 7: 169-180.
15. Sliwa K, Hilfiker-Kleiner D, Petrie MC, et al. Current state of knowledge on aetiology, diagnosis, management, and therapy of peripartum cardiomyopathy: a position statement from the Heart Failure Association of the European Society of Cardiology Working Group on peripartum cardiomyopathy. Eur J Heart Fail 2010; 12: 767-778.
Conflict of Interest:
Neurological and cognite changes in frailty older adults
We agree with the authors of this wide and accurate review that persons while they grow old have anatomic and physiological changes in central and peripheral nervous systems, as well as, in cognitive domain expressing in the interview and physical exam of the elderly. But, frequently, the doctors have difficulties to determine where and when the physiological end and the pathological begin in a proper older adult.
We know today that neurological and cognitive changes are included in the clinical features of frailty, conceptualized as a physiological syndrome characterized by decreased reserve and reduced resistance to stressors, resulting from cumulative decline across physiological systems resulting in 'vulnerability to adverse outcomes.'(1).
These bad results are the followings: increased risk for acute diseases (in particular, infections), falls and its consequences (damage, fractures), hospitalization, institutionalization, disability, dependence and death (2, 3).
Sarcopenia (loss of skeletal muscle mass) constitutes one determinant of frailty syndrome. The observed age-related decrease in muscle cross- sectional area seems to be the result of a decrease in the size of type 2 muscle fibers compared with that of type 1 muscle fibers and also from loss of muscle fiber number. This process is believed to be consistent with a progressive denervation and reinnervation process secondary to a chronic neuropathic process (4).
Furthermore, many authors consider that cognitive impairment is one of the most important components of frailty, and also, that mild cognitive impairment, named as "benign forgetfulness", is not as benign as it seems, because many older adults with this condition develop Alzheimer's Disease in the course of years (5).
Thus, we consider that neurological and cognitive changes detected in the elderly cannot be taken lightly, we must be aware for its further evolution and not resignation to assume to ageing per se.
Julio C. Romero, Angel J. Romero
1. Ferrucci L, Guralnik JM, Studenski S, Fried LP, Cutler GB Jr, Walston JD. Interventions on Frailty Working Group. Designing randomized, cotrolled trials aimed at preventing or delaying functional decline and disability in frail older persons: a consensus report. J Am Geriatr Soc 2004; 52(4): 625-34.
2. Daniels R, Van Rassum E, De Witle L, Van der Hervel W. Frailty in older age: concepts and relevance for occupational and physical therapy. Phys Occup Ther Geriatr 2008; 27(2): 81-95.
3. Romero AJ. Frailty: and emerging geriatric syndrome. Medisur 2010; 8(6): 81-90.
4. Thomas DR. Sarcopenia. Clin Geriatr Med 2010; 26: 331-346.
5. Mayeux R. Early Alzheimer Disease. N Engl J Med 2010; 362: 2194-201.
Conflict of Interest:
Inappropriate use of medical abbreviations
In the first few weeks of my medical internship, one intern was in the habit of writing "DOA" in his admitting histories and physicals. He was eventually confronted by the senior resident who asked for an explanation. It was quite simple. DOA, after all, stood for "day of admission". Didn't everyone know this? I still chuckle at the memory.
Conflict of Interest:
Are there errors in error papers?
Postgraduate Medical Journal, BMA House, Tavistock House, London WC1H 9JR
30 June 2011
A 2009 paper by de Wet and Bowie in the Postgraduate Medical Journal(1) has recently been used by its authors' employer to suggest that, "A recent pilot study reviewing a random selection of primary care electronic medical records found a harm rate of 9.5%".(2) Not only is this interpretation of the paper inaccurate, there are errors contained within the paper which require scrutiny.
The de Wet and Bowie paper was designed to 'develop and test a trigger tool to detect patient harm'. The paper frequently confuses records and consultations. There were 500 records and 2,251 consultations included in the study. The 9.4% (not 9.5% as quotedii) harm rate comes from 47 episodes per record, and not per consultation (the more common method of measuring rates of harm and used by the authors in their opening paragraph). Avoiding this confusion would mean the rate of harm is 47 per 2,251 consultations (2.1%).
The authors appear to have difficulty differentiating between primary and secondary care. The trigger tool is designed to detect errors and harm in primary care records. The authors interpret these as errors and harm resultant from primary care, however the tool actually detects errors in both primary and secondary care. Of the 64 episodes of error, adverse event and/or harm discovered in the 2,251 primary care consultations, 17 occurred in secondary care. Thus, the error, adverse event and/or harm rate would more accurately be reported as 47 per 2,251 primary care consultations (or one episode per 47.8 consultations - 2.1% compared to the headline figure of 9.4%).
The authors also frequently confuse harm, error and adverse event. They use the NCCMERP index for categorizing harm. However the first four categories, A,B,C and D only represent potential harm, not actual harm. This is not made clear in the titles of Tables 3 and 4, both of which mention harm, but not error or adverse event, suggesting all the episodes were of harm, not just errors or adverse events which did not lead to harm. This confusion between error, adverse event and harm is so common in the paper one could almost believe it was on purpose. Incidentally, the paper itself points out that all but 8 episodes of harm were of the lowest level and of this 8, 5 were in secondary care. The only 'severe' episode of harm also occurred in secondary care. Hardly a major problem for primary care, but not clearly explained in the headline figure of 9.4%.
So returning to the 47 events in primary care, 11 were in the range of possible harm rather than actual harm. There were only 36 events which actually led to harm, 36/2,251 consultations, or one per 62.5 consultations in primary care (1.6%). Table 4 points out that 27 episodes of harm were preventable. Eighteen of these occurred in primary care and nine in secondary care. Therefore, of the 36 events in primary care which led to actual harm, only 18 were preventable and cannot be described as an error (e.g. a patient reasonably given a statin for heart disease who develops abnormal LFTs is described as an episode of unavoidable harm). So the error rate in primary care which led to harm is more accurately 18 per 2,251 primary care consultations, or one per 125 primary care consultations (0.8%). Interestingly, this is very similar to the 1 per 120 consultations mentioned in the article's opening paragraph, but which the authors seem to think 'is likely to be an underestimation'. The authors do not give their reasoning behind this throwaway comment and they fail to mention that their very own paper supports the complete opposite view.
In addition to the blatant misrepresentation of the data described above, the paper also contains a mistake in the opening Results section. It says "...an adverse event was found in 47 records... Of these, 27 were judged to be preventable (42%)". In fact 27/47 is 57.4% and not 42%. I think that authors mean 27 of all 64 episodes were preventable but they appear to have confused records with consultations, again.
I think I have shown that the paper has inaccuracies, is confused about records and consultations, primary and secondary care, error, harm and adverse event and the difference between unavoidable and preventable. The headline figure of 9.4% has already been inflated to 9.5% by a respected organisation and the employers of the original paper.(2) This figure is being used and repeated in conversations with politicians, managers and a variety of organisations who would like to demean general practice for their own ends. It is possible, using the same data, to say that avoidable harm only occurs in 1 in 125 consultations. I believe the authors have an agenda to inflate harm in general practice as substantiated by their comment at the end of the first paragraph.
I am a hardworking GP and I do not need to be told how awful GPs are, especially when it is based on erroneous, biased articles. I do not want to go to meetings to hear this 9.4% figure used to impose further unnecessary change on GPs. The paper is not worthy of your publication. Therefore I would be grateful if you would withdraw this paper at the earliest opportunity.
A really pissed off GP
The Barony Practice, Northcroft St, Paisley, PA3 4AD
1. de Wet C, Bowie P. The preliminary development and testing of a global trigger tool to detect error and patient harm in primary-care records. Postgraduate.Medical Journal 2009; 85(1002): 176-180.
2. An introduction to Safety Climate [accessed at http://www.knowledge.scot.nhs.uk/media/CLT/ResourceUploads/23626/SC%20overview%20for%20practices%20MASTERCOPY.pdf on 30th June 2011].
Conflict of Interest:
I am a GP in the West of Scotland. I am paid sessional work by NHS Education Scotland. I am not sure if these count.
Making the most of medical communities.
The identification of leadership as a key skill for doctors is a positive step, however have we undervalued the medical community's assets when considering the development of medical leadership?
Green Templeton College is a graduate college in Oxford, specialising in subjects relating to human welfare and social, economic and environmental well-being in the 21st century. GTC has taken a more local approach to management and leadership, making use of the diverse college community to provide a middle road between a broad compulsory training and intensive course for the high flyers. We have launched a programme for doctors in training who are interested in developing their management and leadership skills. Optional Saturday morning workshops are provided free of charge; informal talks, participative workshops and facilitated case studies are steered by doctors and managers linked with the college, aiding the sharing of skills and knowledge among those interested.
Feedback has been positive, creating a wish-list remarkably similar to that described by Warren and Carnall, including "softer skills", career planning events, case studies, formation of a case book, opportunities for shadowing, mentoring and extended projects or management electives. We plan to expand this programme to regular monthly workshops, demonstrating that this demand can be met within an existing community.
The explosion of the leadership culture through the medical world has brought many valuable strategies from the sphere of management, but should we take a step back and value what we have already? Commercial leadership courses, action learning and coaching have their role, however it might be worth recognising what we already do well and to focus on sharing the mix of skills, so often found in medical communities, more effectively.
Conflict of Interest:
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