WEIGHT CHANGE POST OESOPHAGECTOMY FOR CARCINOMA OF OESOPHAGUS

ABSTRACTObjective: To determine the pattern of weight changes observed in postoperative oesophagectomypatients at the Kenyatta National Hospital and evaluating weight change with selected preoperativevariables.Design: A prospective analysis of post-operative weight change of patients following oesophagectomyutilising body mass index (BMI).Setting: The cardiothoracic unit, Kenyatta National Hospital.Subjects: All patients with oesophageal cancer, with a confirmed histological diagnosis of squamouscell carcinoma and discharged post oesophagectomy.Interventions: Oesophagectomy.Main outcome measure: Changes observed in the BMI during respective clinic visits.Results: Fifty nine patients were enrolled into the study with a mean preoperative weight of50.4 kilograms and mean BMI of 19.4 kg/m2 (± 4.3). Sixty seven point seven percent of patientspreoperatively fell into the underweight category (less than 20kg/m2); normal were 16 patients(27.1%) and overweight included six patients (10.2%). Postoperatively the majority of patientscontinued to loose weight and the overall average BMI at the study endpoint was calculated as18.0 kg/m2 (± 3.2). This value was significantly lower compared with the preoperative value (p =0.004). None of the selected variables showed a significant relationship to the postoperative weightchange pattern observed, though the patients gaining weight postoperatively had an apparentlybetter survival pattern compared to the others. Analysis of the selected variables versus weightchange pattern (gain, stable or weight loss) showed no significant relationships.Conclusion: This study population presented a lower initial preoperative weight compared tosimilar studies from the developed world, with the majority being underweight. The majority ofpatients exhibited a continued postoperative weight loss with only a small number showing anyweight gain. The study unfortunately was not able to demonstrate association of weight changewith any of the selected variables

WARFARIN-RELATED BLEEDING FOLLOWING OPEN HEART SURGERY IN NAIROBI

Objectives: To review anticoagulant-related bleeding in heart valve patients on warfarin atthe Kenyatta National Hospital and to determine the variables associated with anticoagulantrelatedbleeding.Design: A combined retrospective and prospective review of patients operated at theKenyatta National Hospital. Retrospective period from June 1973 to 31st July 1997, whileprospective period from August 1st 1997 to June 1st 2000.Setting: Surgical Outpatient Department, Kenyatta National Hospital, Nairobi.Main outcome measures: Linearised occurrence rate of anticoagulant-related bleeding andthe one- five- and ten- year bleed free rates. Independent risk factors associated withanticoagulant-related bleeding determined using Cox's proportional hazards.Results: Thirty one bleeding episodes were recorded in 150 patients followed up for a totalof 745 patient-years. The risk of occurrence of the first bleed was 16.0% ; while the risk of asubsequent bleed increased thereafter with a 16.7%, 50% and 50% riskafter the first, secondand third bleeds respectively. The linearised rate for minor anticoagulant-related bleed was4.16% per patient per year however, half the bleeds occurred within the first year of valveimplantation or previous bleeding episode. The one-, five- and ten- year bleed free rates forall valves combined were 93%, 85% and 78% respectively. There was no statisticallysignicant difference between the curves comparing the bleed free rates for the first andsecond bleeding episodes (p=0.098). The number of valves implanted, the site of implant andthe time to the occurrence of bleeding were independent risk factors associated with theoccurrence of bleeding (p<.05).Conclusion: The occurrence of anticoagulant-related bleeding is relatively common beingslightly above theinternationally reported range. Most episodes of bleeding will occur withinone year of hospital discharge or the previous bleeding episode. The riskof another bleedingepisode occurring increases with each episode with up to a 50% risk of re-bleed after thesecond bleeding episode. In this study, the number of valves implanted, their position and thetime of occurrence of the bleed were risk factors to the occurrence of bleeding

Editorial: Surgical Audit

No Abstrac

POST-INFARCTION VENTRICULAR SEPTAL DEFECT IN NAIROBI: CASE REPORT

Post infarction ventricular septal defect results from perforation of the ventricular septum secondary to ischaemic injury following myocardial infarction. Ischaemic heart disease till recently was thought to be an uncommon disease in this part of the world, but now more and more cases are being seen as a result of the changes in the life styles of the population in this country and in the developing world in general (1-4).This is a case report of the first case of post infarction ventricular septal defect presenting to surgery for repair in this country

MANAGEMENT PATHWAY FOR CONGENITAL HEART DISEASE AT KENYATTA NATIONAL HOSPITAL, NAIROBI

ABSTRACTBackground: Congenital heart disease (CHD) is a significant cause of death amongst infants. Thetiming of treatment in relation to the natural history of the disease correlates with the treatmentoutcome.Objectives: To determine the age at first suspicion of CHD, the age at confirmation of the diagnosisof CHD and the percentage follow-up at the first post diagnosis out patient clinic and to determinethe influence of patient’s sex, parental income and parental education have on the MP.Design: A five year retrospective study.Setting: Kenyatta National Hospital between January 1st 2000 and December 31st 2004.Subjects: Two hundred and fourteen patients were studied.Results: The overall mean age at referral to a paediatric cardiologist was 16.9 ± 24.4 months[n = 102]. The mean age at which CHD was confirmed by echocardiography was 18.6 ± 25.6 months[n = 202]. The mean age at which CHD was first suspected in patients from the province with thehighest parental income was 9.5±5.1 months [n = 6]. The mean age at which CHD was first suspectedin patients from a province with a significantly lower parent income was 19.1 ± 23.2 months[n = 22], (p = 0. 046). The mean age at which CHD was confirmed in referred male patients was16.0 ± 17.6 months [n=48] and the mean age at which CHD was confirmed in referred female patientswas 18.8 ± 21.7 months [n = 52] (p = 0.25).Conclusion: The mean age at referral to a paediatric cardiologist was 16.9 months. This suggests thata significant number of patients may miss the opportunity to have optimal surgical intervention.Parental income appears to influence the MP, however, the level of parental education and patientsex did not

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran