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T, Mbuyi W, Mbuyisa M, Mbwele B, Mehyaoui R, Menkiti I, Mesarieki L, Metali A, Mewanou S, Mgonja L, Mgoqo N, Mhatu S, Mhlari T, Miima S, Milod I, Minani P, Mitema F, Mlotshwa A, Mmasi J, Mniki T, Mofikoya B, Mogale J, Mohamed A, Mohamed A, Mohamed A, Mohamed S, Mohamed S, Mohamed T, Mohamed A, Mohamed A, Mohamed A, Mohamed P, Mohammed I, Mohammed F, Mohammed M, Mohammed N, Mohlala M, Mokretar R, Molokoane F, Mongwe K, Montenegro L, Montwedi O, Moodie Q, Moopanar M, Morapedi M, Morulana T, Moses V, Mossy P, Mostafa H, Motilall S, Motloutsi S, Moussa K, Moutari M, Moyo O, Mphephu P, Mrara B, Msadabwe C, Mtongwe V, Mubeya F, Muchiri K, Mugambi J, Muguti G, Muhammad A, Mukama I, Mukenga M, Mukinda F, Mukuna P, Mungherera A, Munlemvo DM, Munyaradzi T, Munyika A, Muriithi J, Muroonga M, Murray R, Mushangwe V, Mushaninga M, Musiba V, Musowoya J, Mutahi S, Mutasiigwa M, Mutizira G, Muturi A, Muzenda T, Mvwala K, Mvwama N, Mwale A, Mwaluka C, Mwamba J, Mwanga H, Mwangi C, Mwansa S, Mwenda V, 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Roos J, Rorke NF, Roura H, Rousseau F, Rousseau N, Royas L, Roytowski D, Rungan D, Rwehumbiza S, Ryabchiy B, Ryndine V, Saaiman C, Sabwa H, Sadat S, Saed S, Salaheddin E, Salaou H, Saleh M, Salisu-Kabara H, Doles Sama H, Samateh AL, Sam-Awortwi W, Samuel N, Sanduku D, Sani CM, Sanyang L, Sarah H, Sarkin-Pawa A, Sathiram R, Saurombe T, Schutte H, Sebei M, Sedekounou M, Segooa M, Semenya E, Semo B, Sendagire C, Senoga S, Senusi F, Serdyn T, Seshibe M, Shah G, Shamamba R, Shambare C, Shangase T, Shanin S, Shefren I, Sheshe A, Shittu O, Shkirban A, Sholadoye T, Shubba A, Sigcu N, Sihope S, Sikazwe D, Sikombe B, Simaga Abdoul K, Simo W, Singata K, Singh A, Singh S, Singh U, Sinoamadi V, Sipuka N, Sithole N, Sitima S, Skinner DL, Skinner G, Smith O, Smits C, Sofia M, Sogoba G, Sohoub A, Sookun S, Sosinska O, Souhe R, Souley G, Souleymane T, Spicer J, Spijkerman S, Steinhaus H, Steyn A, Steyn G, Steyn H, Stoltenkamp HL, Stroyer S. The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications. Br J Anaesth 2018; 121:1357-1363. [PMID: 30442264 DOI: 10.1016/j.bja.2018.08.005] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Revised: 07/19/2018] [Accepted: 08/06/2018] [Indexed: 10/28/2022] Open
Abstract
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. CLINICAL TRIAL REGISTRATION NCT03044899.
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Shahin Y, Ali A, Luther A, Nicholson JA, Rajendran I, Boal M, Ritchie J. Population-based cohort study of variation in the use of emergency cholecystectomy for benign gallbladder diseases. Br J Surg 2016; 103:1716-1726. [PMID: 27748962 DOI: 10.1002/bjs.10288] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 06/21/2016] [Accepted: 07/06/2016] [Indexed: 01/05/2023]
Abstract
Abstract
Background
The aims of this prospective population-based cohort study were to identify the patient and hospital characteristics associated with emergency cholecystectomy, and the influences of these in determining variations between hospitals.
Methods
Data were collected for consecutive patients undergoing cholecystectomy in acute UK and Irish hospitals between 1 March and 1 May 2014. Potential explanatory variables influencing the performance of emergency cholecystectomy were analysed by means of multilevel, multivariable logistic regression modelling using a two-level hierarchical structure with patients (level 1) nested within hospitals (level 2).
Results
Data were collected on 4744 cholecystectomies from 165 hospitals. Increasing age, lower ASA fitness grade, biliary colic, the need for further imaging (magnetic retrograde cholangiopancreatography), endoscopic interventions (endoscopic retrograde cholangiopancreatography) and admission to a non-biliary centre significantly reduced the likelihood of an emergency cholecystectomy being performed. The multilevel model was used to calculate the probability of receiving an emergency cholecystectomy for a woman aged 40 years or over with an ASA grade of I or II and a BMI of at least 25·0 kg/m2, who presented with acute cholecystitis with an ultrasound scan showing a thick-walled gallbladder and a normal common bile duct. The mean predicted probability of receiving an emergency cholecystectomy was 0·52 (95 per cent c.i. 0·45 to 0·57). The predicted probabilities ranged from 0·02 to 0·95 across the 165 hospitals, demonstrating significant variation between hospitals.
Conclusion
Patients with similar characteristics presenting to different hospitals with acute gallbladder pathology do not receive comparable care.
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