Perioperative mortality rates in low-income and middle-income countries: a systematic review and meta-analysis

Introduction The Lancet Commission on Global Surgery proposed the perioperative mortality rate (POMR) as one of the six key indicators of the strength of a country’s surgical system. Despite its widespread use in high-income settings, few studies have described procedure-specific POMR across low-income and middle-income countries (LMICs). We aimed to estimate POMR across a wide range of surgical procedures in LMICs. We also describe how POMR is defined and reported in the LMIC literature to provide recommendations for future monitoring in resource-constrained settings. Methods We did a systematic review of studies from LMICs published from 2009 to 2014 reporting POMR for any surgical procedure. We extracted select variables in duplicate from each included study and pooled estimates of POMR by type of procedure using random-effects meta-analysis of proportions and the Freeman-Tukey double arcsine transformation to stabilise variances. Results We included 985 studies conducted across 83 LMICs, covering 191 types of surgical procedures performed on 1 020 869 patients. Pooled POMR ranged from less than 0.1% for appendectomy, cholecystectomy and caesarean delivery to 20%–27% for typhoid intestinal perforation, intracranial haemorrhage and operative head injury. We found no consistent associations between procedure-specific POMR and Human Development Index (HDI) or income-group apart from emergency peripartum hysterectomy POMR, which appeared higher in low-income countries. Inpatient mortality was the most commonly used definition, though only 46.2% of studies explicitly defined the time frame during which deaths accrued. Conclusions Efforts to improve access to surgical care in LMICs should be accompanied by investment in improving the quality and safety of care. To improve the usefulness of POMR as a safety benchmark, standard reporting items should be included with any POMR estimate. Choosing a basket of procedures for which POMR is tracked may offer institutions and countries the standardisation required to meaningfully compare surgical outcomes across contexts and improve population health outcomes.


Data extraction
The following data will be extracted from all papers using a piloted Excel form 1. Year of publication 2. Study design 3. Start and end dates of study period 4. Country location of participating hospitals 5. Facility type (academic hospital, community hospital, district hospital, mixed hospital types, other) 6. Description of the patient population 7. Type of anesthesia used 8. Definition of POMR employed (including timeframe, numerator, and denominator). 9. Whether or not the study reports HIV status, case urgency, comorbidities, clinical scoring systems, age, and whether or not mortality is adjusted for or stratified on these factors. 10. Names of any clinical scoring systems used. 11. Difficulties raised by authors in data collection, including loss to follow up and other such missing data. 12. Planned versus emergent status of operative cases. A planned surgery is one in which the patient is admitted from his or her place of usual residence at a pre-set date for the purpose of undergoing a surgical procedure. An emergency surgery is one in which the patient undergoes a surgical procedure after being admitted to hospital on an unforeseen date with a potentially life-or limbthreatening disease process. 13. Perioperative mortality rate. Where such a rate is not calculated by authors, but a defined numerator and denominator are reported, it will be imputed as calculated by reviewers. Where studies of operative and nonoperative patients are included, only mortality for patients actually undergoing surgery will be extracted. 14. Surgical specialty. Where studies are limited to a surgical specialty, the single most appropriate specialty will be assigned according to the case mix reported. 15. Procedure or diagnosis name. This is imputed where studies are limited to a single diagnosis or a single procedure.
Specific variables will be extracted in duplicate. These include the procedure or diagnosis name, whether or not the definition of POMR was clearly described, the definition of POMR, case urgency status, whether or not a study was based in a high-risk population (other than age, urgency, or the nature of the procedure or diagnosis), whether the study was based in a specific age category (neonatal, pediatric, or geriatric), and the reported POMR numerator and denominator.
All other variables will be extracted by a single trained data extractor, with regular oversight and review by the lead reviewer (JNK).
The attached data dictionary includes a description of all variables extracted with simplifications and assumptions outlined.

Risk of Bias
On an individual study level, studies risk selection bias (by failing to represent consecutive cases), or detection bias (by failing to provide complete follow-up data). All studies will be assessed for both such biases.
On a review level, publication bias may influence results, however the direction of such bias is unclear. Studies may tend to come from larger centres with more complex patients. This may either overestimate mortality (due to clinical complexity) or underestimate mortality (due to greater resource availability at such centres). Authors may be reticent to publish audit data showing high mortality (for professional or political reasons), or they may publish studies of riskier procedures more frequently (for reasons of academic interest). Such biases will be addressed qualitatively-for example, if studies are primarily identified from urban, academic centres, results may not be generalizable to smaller rural centres.

Data synthesis
The data collected will be analyzed as case-series outcomes (mortality rates), regardless of the underlying study design. We anticipate significant heterogeneity in mortality rates across clinical groups (specific procedures or diagnoses), and even within clinical groups. We will therefore simply provide reported ranges of POMR for a variety of procedures or diagnostic groups.
Analysis Data analysis will be undertaken using Stata 13/IC

PRISMA REQUIREMENTS FOR REPORTING Domain Requirement
Fulfilments in present work Data collection process Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.
Used piloted excel-based form. Updated iteratively as deemed appropriate. Data extracted by trained clinician coders.
Unlikely to seek data/confirmation from primary investigators (too many papers for this to be feasible) Data items List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.