| Literature DB >> 33426387 |
Shepherd Kajawo1,2,3, Udeme Ekrikpo2,4, Mothusi Walter Moloi2,3, Jean Jacques Noubiap5, Mohamed A Osman6, Ugochi S Okpechi-Samuel7, Andre Pascal Kengne8, Aminu K Bello6, Ikechi G Okpechi2,3,6.
Abstract
INTRODUCTION: Kidney biopsy is an important tool for making diagnoses and for assessing the drug treatment requirements and disease prognosis in the management of kidney diseases. There are variations in the rate of complications associated with kidney biopsies across countries, and this depends on various clinical and technical factors. The aim of this study is to report on complications associated with kidney biopsy performed in low- and middle-income countries.Entities:
Keywords: bleeding; complications; kidney biopsy; low-to-middle-income countries; needle biopsy; ultrasound-guided biopsy
Year: 2020 PMID: 33426387 PMCID: PMC7783578 DOI: 10.1016/j.ekir.2020.10.019
Source DB: PubMed Journal: Kidney Int Rep ISSN: 2468-0249
Figure 1Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart. AJOL, African Journals Online.
General characteristics of included studies
| Authors, reference | Country | Region | Income group | Year | Setting | Mean age (yr) | Female (%) | Patients (n) | Biopsies (n) | Technique | Operator | Needle type | Needle size | Quality score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Tuladhar | Nepal | South Asia | LIC | 2014 | Inpatient | NR | 56 | 75 | 75 | USS-PM | Neph + Rad | Automated | 16G, 18G | Moderate |
| Ghimire | Nepal | South Asia | LIC | 2014 | Inpatient | 30.3 ± 12.5 | 56 | 75 | 75 | USS-PM | Neph trainee | Automated | 16G, 18G | Moderate |
| Manandhar | Nepal | South Asia | LIC | 2016 | Inpatient | 31.3 ± 11.9 | 56 | 75 | 75 | USS-PM | Neph + Rad | Automated | 16G, 18G | Moderate |
| Pokhrel | Nepal | South Asia | LIC | 2019 | Inpatient | 33.0 | 59 | 37 | 37 | USS-PM | Neph trainee | Automated | 18G | Moderate |
| Pokhrel 2 | Nepal | South Asia | LIC | 2019 | Inpatient | 33.9 | 37 | 38 | 38 | USS-RT | Neph trainee | Automated | 18G | Moderate |
| Abdou | Senegal | SSA | LIC | 2003 | Inpatient | 28 | 44.3 | 115 | 115 | USS-RT | NR | NR | NR | Low |
| Aatif | Morocco | M/East + N/Afr | LMIC | 2012 | Inpatient | 40.4 ± 15 | 37.3 | 161 | 171 | Blind | NR | Automated | NR | Moderate |
| Zajjari | Morocco | M/East + N/Afr | LMIC | 2015 | Inpatient | 44.8 ± 17.9 | 33.8 | 130 | 130 | USS-PM | NR | Automated | 16G | Moderate |
| Sobh | Egypt | M/East + N/Afr | LMIC | 1988 | Inpatient | NR | 34.2 | 120 | 78 | Fluoroscopic | NR | NR | NR | Low |
| Hachicha | Tunisia | M/East + N/Afr | LMIC | 1987 | Inpatient | 36.7 | 53.3 | 30 | 30 | Blind | NR | Non-automated | NR | Low |
| Hachicha 2 | Tunisia | M/East + N/Afr | LMIC | 1987 | npatient | 33.4 | 66.7 | 30 | 30 | USS-RT | NR | Non-automated | NR | Low |
| Nadium | Sudan | SSA | LMIC | 2013 | Inpatient | 34.6 ± 18 | 40 | 83 | 83 | USS-PM | NR | Non-automated | 16G, 18G | Moderate |
| Musa | Sudan | SSA | LMIC | 1980 | Inpatient | 24.4 | 31.1 | 61 | 61 | Blind | NR | Non-automated | NR | Low |
| Obineche | Nigeria | SSA | LMIC | 1982 | Inpatient | 21 | 24.4 | 90 | 105 | Blind | Neph | Non-automated | NR | Low |
| Krishna A | India | South Asia | LMIC | 2018 | inpatient | 31.5 | 34.8 | 270 | 270 | USS-RT | NR | Automated | NR | Moderate |
| Prakash | India | South Asia | LMIC | 1994 | Inpatient | 32 | 10.5 | 305 | 320 | Blind | NR | Non-Automated | NR | Moderate |
| Prasad | India | South Asia | LMIC | 2015 | Inpatient | 35.7 ± 15.6 | 31 | 2138 | 2138 | USS-RT | Neph + Rad | Automated | 16G, 18G | High |
| Yesudas | India | South Asia | LMIC | 2010 | Inpatient | 41.1 | 31.1 | 74 | 74 | USS-RT | Neph + Rad | Automated | 18G, 20G | Moderate |
| Sakhuja | India | South Asia | LMIC | 1990 | Inpatient | NR | NR | 150 | 150 | USS-PM | NR | Non-automated | NR | Moderate |
| Golay | India | South Asia | LMIC | 2013 | Inpatient | 28.9 | 46.5 | 403 | 403 | USS-RT | Neph trainee | Automated | 16G, 18G | Moderate |
| Arora | India | South Asia | LMIC | 2012 | Inpatient | NR | NR | 50 | 50 | USS-PM | NR | Automated | 16G, 18G | Moderate |
| Ahmed | Pakistan | South Asia | LMIC | 2003 | Inpatient | 26.9 | 30 | 40 | 40 | USS-PM | NR | Automated | 18G | Moderate |
| Azmat | Pakistan | South Asia | LMIC | 2017 | Inpatient | 41.7 ± 8.6 | 62.8 | 220 | 220 | USS-RT | Neph | Automated | 14G | High |
| Mansoor | Pakistan | South Asia | LMIC | 2016 | Outpatient | 45.5 ± 11 | 17 | 100 | 100 | USS-RT | Rad | NR | NR | High |
| Yaqub | Pakistan | South Asia | LMIC | 2017 | Inpatient | 41 ± 16 | 42.3 | 433 | 433 | USS-RT | Neph | Automated | 16G, 18G | Moderate |
| Habas | Libya | M/East + N/Afr | UMIC | 2016 | Outpatient | 34 ± 1.8 | 57.6 | 118 | 118 | USS-RT | Neph | Automated | 16G | Moderate |
| Mishra | Libya | M/East + N/Afr | UMIC | 2011 | Outpatient | NR | 73.3 | 86 | 86 | USS-RT | Rad | Automated | 16G | Moderate |
| Ghnaimat | Jordan | M/East + N/Afr | UMIC | 1999 | Inpatient | 29.1 | 37.7 | 191 | 191 | USS-PM | Neph | Non-automated | NR | Moderate |
| Chen | China | E/Asia + Pacific | UMIC | 1993 | Inpatient | NR | NR | 1000 | 1000 | USS-PM | NR | NR | NR | High |
| Hu | China | E/Asia + Pacific | UMIC | 2016 | inpatient | 33 ± 12 | 54 | 2639 | 2639 | USS-RT | Neph | NR | NR | High |
| Tao | China | E/Asia + Pacific | UMIC | 2008 | Inpatient | NR | NR | 1262 | 1262 | USS-PM | NR | NR | NR | High |
| Wang | China | E/Asia + Pacific | UMIC | 2015 | Inpatient | 40 ± 15.4 | 39.3 | 1342 | 1314 | USS-PM | NR | Automated | 16G | High |
| Xu | China | E/Asia + Pacific | UMIC | 2017 | Inpatient | 40.5 ± 16.3 | 48.9 | 3577 | 3577 | USS-RT | NR | Automated | 16G,18G | High |
| Pongsittisak W | Thailand | E/Asia + Pacific | UMIC | 2019 | Inpatient | 44 | 52 | 100 | 100 | USS-PM | Neph trainee | Automated | 16G | High |
| Pongsittisak W 2 | Thailand | E/Asia + Pacific | UMIC | 2019 | Inpatient | 39 | 60 | 104 | 104 | USS-RT | Neph trainee | Automated | 16G | High |
| Kanjanabuchi | Thailand | E/Asia + Pacific | UMIC | 2005 | Inpatient | 37 ± 14.2 | 69.8 | 506 | 506 | USS-RT | NR | NR | NR | Moderate |
| Covic | Romania | Europe | UMIC | 2006 | Inpatient | 38.5 ± 15.2 | 48.5 | 635 | 635 | USS-RT | NR | NR | NR | Moderate |
| Trajceska L | Macedonia | Europe | UMIC | 2019 | Inpatient | 47.8 ± 15.5 | 39 | 342 | 345 | USS-RT | NR | Automated | 16G | High |
| Kovacevic | Serbia | Europe | UMIC | 1996 | Inpatient | NR | 23.7 | 558 | 582 | USS-PM | NR | Non-automated | NR | Moderate |
| Munoz | Mexico | Lat Am/Car | UMIC | 2010 | Inpatient | 34.4 ± 14.2 | 70.5 | 623 | 623 | USS-RT | Neph + Rad | Automated | 16G | High |
| Gonzalez-Michaca | Mexico | Lat Am/Car | UMIC | 2000 | NR | 37.7 ± 13.1 | 66.9 | 840 | 1005 | USS-RT | Neph trainee | Automated | 16G | High |
| Kruger | South Africa | SSA | UMIC | 2011 | Inpatient | 41.5 | 50.9 | 112 | 112 | USS-RT | Rad | Automated | 16G | Moderate |
E/Asia + Pacific, East Asia and Pacific; LIC, low-income country; Lat Am/Car, Latin America and the Caribbean; LMIC, low- and middle-income country; M/East + N/Afr, Middle East and North Africa; Neph, nephrologist; NR, not reported; Rad, radiologist; SSA, sub-Saharan Africa; UMIC, upper- and middle-income country; USS-PM, pre-marking technique with ultrasound; USS-RT, real time ultrasound.
Quality score: high, 1−3; moderate, 4–6; low, 7–10.
Figure 2Overall complications grouped by biopsy technique.
Figure 3Funnel plot assessing publications bias (with pseudo 95% confidence interval [CI]).
Figure 4Major complications grouped by biopsy technique. CI, confidence interval.
Rates of major complications of percutaneous native kidney biopsy
| No. of studies | No. of procedures | No. of complications | Complication rate (%) | |
|---|---|---|---|---|
| Macroscopic hematuria | 34 | 15,630 | 231 | 1.48 |
| Major hematoma | 36 | 17,992 | 464 | 2.40 |
| Nephrectomy | 33 | 16,427 | 7 | 0.04 |
| Blood transfusion | 32 | 15,561 | 38 | 0.24 |
| Angiographic/surgical interventions | 36 | 16,234 | 35 | 0.22 |
| Infections | 35 | 15,635 | 18 | 0.12 |
| Death | 39 | 19,500 | 2 | 0.01 |
Figure 5Minor complications. CI, confidence interval.